Research Design and Statistical Analysis - 4th Ed 2006

Table of Contents

Unit I: Research Fundamentals

1 ...

Scientific Knowing

Science as a Way of Knowing 1-4

Objectivity 1-4

Precision 1-4

Verification 1-5

Empiricism 1-5

Goal: Theories 1-5

The Scientific Method 1-6

Types of Research 1-6 Historical Research 1-7 Primary sources 1-7 Secondary sources 1-7 Criticism 1-7 Examples 1-8 Descriptive Research 1-8 An Example 1-8 Correlational Research 1-9 An Example 1-9 Experimental Research 1-9 An Example 1-10

Ex Post Facto Research 1-10

An Example 1-10

Evaluation 1-10

An Example 1-11

Research and Development 1-11

An Example 1-11

Qualitative Research 1-11

Faith and Science 1-12

Suspicion of Science By the Faithful 1-12

Suspicion of Religion By the Scientific 1-13

There Need Be No Conflict 1-13

Summary 1-14

Vocabulary 1-15

Study Questions 1-15

Sample Test Questions 1-15

2 ...

Proposal Organization

The Introductory Statement 2-3

Preface i-1

Preliminaries

The Statement of the Problem 2-3

Purpose of the Study 2-4

Synthesis of Related Literature 2-4

Significance of the Study 2-6

The Hypothesis 2-6 Method 2-7 Population 2-7 Sampling 2-8 Instrument 2-8 Limitations 2-9 Assumptions 2-10 Definitions 2-10 Design 2-11

Procedure for Collecting Data 2-12

Analysis 2-12

Procedure for Analyzing Data 2-12

Testing the Hypotheses 2-13

Reporting the Data 2-13

Reference Material 2-13

Appendices 2-13

Bibliography, or Cited Sources 2-14

Practical Suggestions 2-14

Personal Anxiety 2-14

Professionalism in Writing 2-15

Clear Thinking 2-15

Unified Flow 2-15

Quality Library Research 2-15

Efficient Design 2-15

Accepted Format 2-15

Summary 2-16

Vocabulary 2-16

Study Questions 2-16

Sample Test Questions 2-17

3 ...

Empirical Measurement

3-1

Variables and Constants 3-1

Independent Variables 3-2 Dependent Variables 3-2 Measurement Types 3-2 Nominal Measurement 3-2 Ordinal Measurement 3-2 Interval Measurement 3-2 Ratio Measurement 3-3

Data Type Summary 3-3

Operationalization 3-3 Definitions 3-4 An Example 3-4 Another Example 3-5 Operationalization Questions 3-6 Summary 3-6 Vocabulary 3-7 Study Questions 3-7

Sample Test Questions 3-7

4 ...

Getting On Target

4-1

The Problem Statement 4-1

Characteristics of a Problem 4-1

Limit scope of your study 4-1

Meaningfulness 4-2

Clearly written 4-2

Examples of Problem Statements 4-2

Association Between Two Variables 4-2 Association of several variables 4-2

Difference Between Two Groups 4-3

Differences Between More Than Two Groups 4-3

The Hypothesis Statement 4-4

The Research Hypothesis 4-4

Association Between Two Variables 4-4 Association of several variables 4-5

Difference Between Two Groups 4-5

Differences Between More Than Two Groups 4-6

The Directional Hypothesis 4-6

The Non-directional Hypothesis 4-7

The Null Hypothesis 4-7

Revision Examples 4-8 Example 1 4-8 Comments 4-8 Suggested revision 4-8 Example 2 4-8 Comments 4-8 Suggested revision 4-9 Example 3 4-9 Comments 4-9 Suggested revision 4-9 Example 4 4-9 Comments 4-9 Suggested revision 4-10 Example 5 4-10 Comments 4-10 Dissertation Examples 4-10 Regression Analysis 4-10

Correlation of Competency Rankings 4-11

Factorial Analysis of Variance 4-11

Chi-Square Analysis of Independence 4-11

5 ...

Introduction to Statistical Analysis

5-1

Statistics, Mathematics, and Measurement 5-1

Descriptive Statistics 5-2

Inferential statistics 5-2

Statistics and Mathematics 5-2

Statistics and Measurement 5-2

A Statistical Flow Chart 5-4

Question One: Similarity or Difference? 5-4

-1- Question Two: Data Types in Similarity Studies 5-4 -2- Question Two: Data Types in Difference Studies 5-4

-3- Interval or Ratio Correlation 5-4

-4- Ordinal Correlation 5-5 -5- Nominal Correlation 5-5 -6- Interval/Ratio Differences 5-6 -7- Ordinal Differences 5-7 Summary 5-7 Vocabulary 5-7 Study Questions 5-8

Sample Test Questions 5-8

6 ...

Synthesis of Related Literature

6-1

A Definition 6-1

Synthetic Narrative 6-1

Preliminaries

Related to Your Study 6-2

The Procedure for Writing the Related Literature 6-2

Choose One or More Databases 6-2

E.R.I.C. 6-2

RIE 6-2

CIJE 6-2

Psychological Abstracts 6-3

Dissertation Abstracts 6-3

Choose Preliminary Sources 6-3

Thesaurus of ERIC Descriptors 6-3

Education Index 6-3

Citation Indexes 6-3

Smithsonian Science Information Exchange 6-4

Mental Measurements Yearbook 6-4

Measures for Psychological Measurement 6-4

Select Key Words 6-4

Searching the literature 6-5

Searching manually 6-5

Searching by Computer 6-5

Select Articles 6-6

Analyze the Research Articles 6-7

An Organizational Notebook 6-7

Prioritizing Articles 6-7

Selecting Notes and Quotes with References 6-8 Reorganize Material by Key Words 6-8 Write a Synthesis of Related Literature 6-8

Revise the Synthesis 6-8

Summary 6-9

Vocabulary 6-9

Study Questions 6-9

Sample Test Questions 6-10

7 ...

Populations and Sampling

7-1

The Rationale of Sampling 7-1

The Population 7-1

Sampling 7-1

Biased Samples 7-2

Randomization 7-2

Steps in Sampling 7-2

Identify the Target Population 7-2

Identify the Accessible Population 7-2

Determine the Size of the Sample 7-3

Accuracy 7-3

Cost 7-3

The Homogeneity of the Population 7-3

Other Considerations 7-4

Sample Size Rule of Thumb 7-4

Select the Sample 7-4

Types of Sampling 7-4

Simple Random Sampling 7-4

Systematic Sampling 7-5

Stratified Sampling 7-6

Cluster sampling 7-6

Inferential Statistics A Quick Look Ahead 7-7

The Case Study Approach 7-8

Historical Case Studies of Organizations 7-8

Observational Case Studies 7-8

Oral Histories 7-8

Situational Analysis 7-8

Clinical case study 7-8

Summary 7-9

Study Questions 7-9

Sample Test Questions 7-10

8 ...

Collecting Dependable Data

8-1

Validity 8-1 Content Validity 8-2 Predictive Validity 8-2 Concurrent Validity 8-2 Construct Validity 8-3 Reliability 8-3 Coefficient of Stability 8-4

Coefficient of Internal Consistency 8-4

Coefficient of Equivalence 8-5

Reliability and Validity 8-5

Answer 1: A Test Must be Reliable in Order to be Valid 8-5 Answer 2: A Test Can be Valid Even If It Isn’t Reliable 8-5

Objectivity 8-6

Summary 8-7

Vocabulary 8-7

Study Questions 8-8

Sample Test Questions 8-8

Unit II: Research Methods

9 ...

Observation

9-1

The Problem of the Observation Method 9-1

Obstacles to Objectivity in Observation 9-2

Personal Interest 9-2

Early decision 9-2

Personal characteristics 9-3

Practical Suggestions for Avoiding these Problems 9-3

Definition 9-3

Familiar Groups 9-3

Unfamiliar Groups 9-3

Observational Limits 9-3

Manual versus Mechanical Recording 9-3

Interviewer Effect 9-3 Debrief Immediately 9-4 Participant Observation 9-4 Undercover Observation? 9-4 Observational Checklist 9-4 Summary 9-4 Example 9-4 Vocabulary 9-5 Study Questions 9-5

Sample Test Questions 9-5

10 ...

Survey Research

10-1

Preliminaries

Disadvantages 10-2

Rate of return 10-2

Inflexibility 10-3

Subject motivation 10-3

Verbal behavior only 10-3

Loss of control 10-3 Types of questionnaires 10-3 Guidelines 10-4 Asking questions 10-4 Understandable format 10-4 Clear instructions 10-4

Demographics at the end 10-4

The Interview 10-5 Advantages 10-5 Flexibility 10-5 Motivation 10-5 Observation 10-5 Broader Application 10-5

Freedom from mailings 10-5

Disadvantages 10-6 Time 10-6 Cost 10-6 Interviewer effect 10-6 Interviewer variables 10-6 Types of Interviews 10-6 Guidelines 10-6 Recording responses 10-6 Interview skills 10-7 Demographics 10-7 Alternative modes 10-7

Developing the Survey Instrument 10-7

Specify Survey Objective 10-7

Write Good Questions 10-7

Evaluate and Select the Best Items 10-7

Format the Survey 10-8

Write Clear Instructions 10-8

Pilot Study 10-8

Summary 10-8

Examples 10-8

Vocabulary 10-9

Study Questions 10-10

Sample Test Questions 10-10

11 ...

Developing Tests

11-1

Preliminary considerations 11-1

The Emphases in the Material 11-1

Nature of Group being Tested 11-2

The Purpose of the Test 11-2

Writing items 11-2

Objective Tests 11-2

The True-False Item 11-2

Advantages 11-2

Disadvantages 11-3

Writing True-False items 11-3

Avoid specific determiners 11-3

Absolute answer 11-3

Avoid double negatives 11-3

Use precise language 11-3

Avoid direct quotes 11-4

Watch item length 11-4

Avoid complex sentences 11-4

Use more false items 11-4

Multiple Choice Items 11-4

Writing Multiple Choice Items 11-4

Pose a singular problem 11-5

Avoid repeating phrases in responses 11-5

Minimize negative stems 11-5

Make responses similar 11-5

Make responses mutually exclusive 11-5 Make responses equally plausible 11-5

Randomly order responses 11-5

Avoid sources of irrelevant difficulty 11-5

Eliminate extraneous material 11-5

Avoid “None of the Above” 11-6

Supply Items 11-6

Advantages 11-6

Disadvantages 11-6

Writing Supply Items 11-6

When to use supply items 11-6

Limit blanks 11-6

Only one correct answer 11-6

Blank important terms 11-6

Place blank at the end 11-7

Avoid irrelevant clues 11-7

Avoid text quotes 11-7

Matching Items 11-7

Advantages 11-7

Disadvantages 11-7

Writing Matching Items 11-7

Limit number of pairs 11-7

Make option list longer 11-7

Only one correct match 11-8

Maintain a central theme 11-8

Keep responses simple 11-8

Make the response option list systematic 11-8

Specific instructions 11-8

Essay Tests 11-8

Open-Ended Items 11-8

Advantages 11-8

Disadvantages 11-9

Writing essay items 11-9

Use short-answer essays 11-9

Write clear questions 11-9

Develop a grading key 11-9

Item analysis 11-9

Rank Order Subjects By Grade 11-10

Categorize Subjects into Top and Bottom Groups 11-10

Compute Discrimination Index 11-10

Revise Test Items 11-10

Summary 11-10

Examples 11-10

Vocabulary 11-13

Study Questions 11-14

Sample Test Questions 11-14

Sample Test 11-15

12 ...

Developing Scales

12-1

The Likert Scale 12-2

Define the attitude 12-2

Determine related areas 12-2

Write statements 12-2

Positive examples 12-3

Negative examples 12-3

Create an item pool 12-3

Validating the items 12-3

Preliminaries

Formatting the Scale 12-4

Write instructions 12-4

Scoring the Likert scale 12-4

The Thurstone Scale 12-4

Develop item pool 12-5

Compute item weights 12-5

Rank the items by weight 12-6

Choose Equidistant Items 12-6

Formatting the Scale 12-6

Administering the Scale 12-6

Scoring 12-6 Q-Methodology 12-6 Semantic Differential 12-7 Delphi Technique 12-7 Summary 12-8 Vocabulary 12-8 Study Questions 12-8

Sample Test Questions 12-8

Sample Thurstone Scale 12-9

Sample Thurstone Scale (with weights) 12-10

13 ...

Experimental Designs

13-1

What Is Experimental Research? 13-1

Internal Invalidity 13-2 History 13-2 Maturation 13-2 Testing 13-2 Instrumentation 13-3 Statistical regression 13-3 Differential selection 13-3 Experimental mortality 13-4

Selection-Maturation Interaction of Subjects 13-4

The John Henry Effect 13-4

Treatment diffusion 13-4

External Invalidity 13-4

Reactive effects of testing 13-5

Treatment and Subject Interaction 13-5

Testing and Subject Interaction 13-5

Multiple Treatment Effect 13-5

Summary 13-5

Types of Designs 13-6

True Experimental Designs 13-6

Pretest-Posttest Control Group 13-6

Posttest Only Control Group 13-6

Solomon Four-Group 13-7

Quasi-experimental Designs 13-7

Time Series 13-7

Nonequivalent Control Group Design 13-8

Counterbalanced Design 13-8

Pre-experimental Designs 13-9

The One Shot Case Study 13-9

One-Group Pretest/Posttest 13-9

Static-Group comparison 13-10

Summary 13-10

Vocabulary 13-10

Study Questions 13-11

Unit III: Statistical Fundamentals

14 ...

Basic Math Skills

14-1

Mathematical Symbols 14-1

Arithmetic Operators 14-1

Square (2_{) 14-1}

Square Root (√) 14-2

The Sum Symbol (Σ) 14-2

Parentheses and Brackets 14-2

Using Letters as Numbers 14-3

Mathematical Concepts 14-3

Fractions 14-3

Negative numbers 14-4

Percents and Proportions 14-4

Exponents 14-4 Simple Algebra 14-4 Summary 14-6 Vocabulary 14-6 Study Questions 14-6

15 ...

Distributions and Graphs

15-1

Creating An Ungrouped Frequency Distribution 15-1

Creating a Grouped Frequency Distribution 15-2

Calculate the Range 15-2

Compute the Class Width 15-2

Determine the Lowest Class Limit 15-3

Determine the Limits of Each Class 15-3

Group the Scores in Classes 15-3

Graphing Grouped Frequency Distributions 15-4

X- and Y-axes 15-4 Scaled Axes 15-4 Histogram 15-4 Frequency Polygon 15-5 Distribution Shapes 15-5 Distribution-Free Measures 15-6 Summary 15-6 Vocabulary 15-6 Study Question 15-6

Sample Test Questions 15-7

16 ...

Central Tendency and Variation

16-1

Measuring Central Tendency 16-1

The Mode 16-1

The Median 16-1

The Arithmetic Mean 16-2

Central Tendency and Skew 16-3

Measures of Variability 16-3

Range 16-3

Average Deviation 16-4

Standard deviation 16-5

Deviation Method 16-5

Raw Score Method 16-6

Equal Means, Unequal Standard Deviations 16-7

Parameters and Statistics 16-8

Preliminaries Sample Statistics 16-9 Estimated Parameters 16-9 Standard (z-) Scores 16-10 Summary 16-12 Example 16-12 Vocabulary 16-13 Study Questions 16-14

Sample Test Questions

16-15

17 ...

The Normal Curve and Hypothesis Testing

17-1

The Normal Curve 17-1

The Normal Curve Table 17-2

The Normal Curve Table in Action 17-3

Level of Significance 17-6

Criticial Values 17-6

One- and Two-Tailed Tests 17-6

Sampling Distributions 17-7

The Distinction Illustrated 17-8

Using the z-Formula for Testing Group Means 17-9

Computing Probabilities of Means 17-9

Summary 17-10

Example 17-10

Vocabulary 17-11

Study Questions 17-11

Sample Test Questions

17-13

18 ...

The Normal Curve: Error Rates and Power

18-1

Type I and Type II Error Rates 18-1

Decision Table Probabilities 18-2

Normal Curve Areas 18-2

Increasing Statistical Power 18-4

Increase α 18-4

Increase µ1 - µ2 18-4

Decrease the Standard Error of the Mean 18-5

Decrease s 18-5

Increase n 18-5

Like Fishing for Minnows 18-6

Statistical Significance and Practical Importance 18-6

Summary 18-6

Vocabulary 18-7

Study Questions 18-7

Sample Test Questions 18-7

Unit IV: Statistical Procedures

19 ...

One Sample Parametric Tests

19-1

The One-Sample z-Test 19-1

The One-Sample t-Test 19-2

The t-Distribution Table 19-2

Computing t 19-3

Confidence Intervals 19-4

A z-Score Confidence Interval 19-4

A t-Score Confidence Interval 19-5

Vocabulary 19-5

Study Questions 19-5

Sample Test Questions 19-6

20 ...

Two Sample t-Tests

20-1

Descriptive or Experimental? 20-1

t-Test for Independent Samples 20-2

The Standard Error of Difference 20-3

Example Problem 20-3

t-Test for Correlated Samples 20-5

Effect of Correlated Samples 20-5

The Standard Error of Difference 20-6

Example Problem 20-6

The Two Sample Confidence Interval 20-8

Summary 20-8

Examples 20-8

Vocabulary 20-10

Study Questions 20-10

Sample Test Questions 20-11

21 ...

One-Way Analysis of Variance

21-1

Why Not Multiple t-tests? 21-1

Computing the F-Ratio 21-3

Sums of Squares 21-3

Degrees of Freedom 21-4

Variance Estimates 21-4

The F-Ratio 21-4

The F-Distribution Table 21-5

The ANOVA Table 21-5

An Example 21-5

Multiple Comparison Procedures 21-6

Procedures Defined 21-6

The Least Significant Difference 21-6 The Honestly Significant Difference 21-7

Multiple Range Tests 21-7

Fisher-Protected Least Significance Difference 21-7

Procedures Computed 21-7 (F)LSD 21-8 HSD 21-8 SNK 21-9 Summary 21-10 Examples 21-10 Vocabulary 21-11 Study Questions 21-11

Sample Test Questions 21-13

22 ...

Correlation Coefficients

22-1

The Meaning of Correlation 22-1

Correlation and Data Types 22-2

Pearson’s Product Moment Correlation Coefficient (rxy) 22-3

Spearman’s rho Correlation Coefficient (rs) 22-5

Other Important Correlation Coefficients 22-6

Point Biserial Coefficient 22-6

Rank Biserial Coefficient 22-6

Phi Coefficient (rf) 22-7

Kendall’s Coefficient of Concordance (W) 22-7

Preliminaries

Summary 22-8

Vocabulary 22-8

Study Questions 22-8

Sample Test Question 22-9

23 ...

Chi-Square Procedures

23-1

The Chi Square formula 23-1

The Goodness of Fit Test 23-2

Equal Expected Frequencies 23-2

The Example of a Die 23-2

Computing the Chi Square 23-2

Testing the Chi Square Value 23-3

Translating into English 23-3

Proportional Expected Frequencies 23-3

The Example of Political Party Preference 23-3 Computing the Chi Square Value 23-3

Testing the Chi Square 23-4

Translate into English 23-4

Eyeball the Data 23-4

Chi-Square Test of Independence 23-4

The Contingency Table 23-5

Expected Cell Frequencies 23-5

Degrees of Freedom 23-6

Application to a Problem 23-6

Party Preference Revisited 23-7

Strength of Association 23-8

Contingency Coefficient 23-8

Cramer’s Phi 23-9

Cautions in Using Chi-Square 23-9

Small expected frequencies 23-9

Assumption of Independence 23-10 Inclusion of Non-Occurrences 23-10 Summary 23-11 Example 23-11 Vocabulary 23-12 Study Questions 23-12

Sample Test Questions 23-12

Unit V: Advanced Statistical Procedures

24 ...

Non-Parametric Statistics for Ordinal Differences

24-1

The Rationale of Testing Ordinal Differences 24-2

Wilcoxin Rank-Sum Test (W_s) 24-2

Computing the Wilcoxin W 24-3

The Wilcoxin W Table 24-3

The Mann-Whitney U Test 24-3

Computing the Mann-Whitney U 24-3

The Mann-Whitney U Table 24-4

Wilcoxin Matched-Pairs Test (T) 24-4

Computing the Wilcoxin T 24-4

The Wilcoxin T Table 24-5

Kruskal-Wallis H Test 24-5

Computing the Kruskal-Wallis H 24-5

Using the Chi-Square Table with Kruskal-Wallis H 24-6

Summary 24-6

Example 24-6

Vocabulary 24-8

Study Questions 24-8

25 ...

Factorial and Multivariate Analysis of Variance

25-1

Two-Way ANOVA 25-2

The Meaning of Interaction 25-2

Types of Interaction 25-3

No Interaction 25-3

Ordinal Interaction 25-3

Disordinal Interaction 25-3

Sums of Squares in Two-Way ANOVA 25-3

The Two-Way ANOVA Table 25-4

Three-way ANOVA 25-5

Analysis of Covariance 25-6

Adjusting the SS Terms 25-6

Uses of ANCOVA 25-7

Example Problem 25-7

Multivariate Analysis of Variance 25-9

Summary 25-10

Example 25-10

Vocabulary 25-13

Study Questions 25-13

Sample Test Questions 25-14

26 ...

Regression Analysis

26-1

The Equation of a Line 26-2

Linear Regression 26-3

The Linear Regression Equation 26-3

Computing a and b 26-3

Drawing the Regression Line on the Scatterplot 26-4

Errors of Prediction (e) 26-4

Standard Error of Estimate 26-5

Multiple Linear Regression 26-6

Raw Score Regression Equation 26-6

Standardized Score Regression Equation 26-6

Multiple Correlation Coefficient 26-6

Multiple Regression Example 26-7

The Data 26-7

The Correlation Matrix 26-7

The Multiple Regression Equation 26-7

The Essential Questions 26-8

Multiple Regression Printout 26-8

Section One 26-8

Section Two 26-9

Section Three 26-10

Focus on the Significant Predictors 26-10

Multiple Regression Equations 26-11

Summary 26-12

Example 26-12

Vocabulary 26-14

Study Questions 26-14

Sample Test Questions 26-15

Unit VI: EvaluatingResearch Proposals

27 ...

Guidelines for Evaluating Research Proposals

27-1

Research Proposal Checklist 27-1

Front Matter 27-1

Preliminaries

The Method 27-2

The Analysis 27-2

General 27-3

Appendices:

Answer Key to Sample Test Questions

A1

Word List

A2

Critical Value Tables

A3

Dissertations and a Thesis

A4

1-1

Student 1: "I use the King James Version because that's the translation I grew up using.

Everybody in our church back home uses it."

Student 2: "I use the New King James because my pastor says it offers the best of beauty and modern scholarship."

Student 3: "I've prayed about what version to use. I like the Amplified Version because it is so clear in its language. It just feels right."

Student 4: " I've tried five or six different translations for devotional reading and for preparation for teaching in Sunday School. After evaluating each one, I've come back again and again to the New International Version. It's the best translation for me." Student 5: "The essense of Bible study is understanding the message, whatever

transla-tion we may use. Therefore, I use different translations depending on my study goals."

Student 6: "I use the New King James because most of my congregation is familiar with it. In a recent survey, I found that 84% of our members use the KJV or NKJV." Each of these students reflect a different basis for knowing which translation to use. Which student most closely reflects your view? How did you come to know what you know?

Ways of Knowing

As we begin our study of research design and statistical analysis, we need to understand the characteristics of scientific knowing, and how this kind of knowing differs from other ways we learn about our world. We will first look at five non-scien-tific ways of knowing: common sense, authority, intuition/revelation, experience, and deductive reasoning. Then we'll analyze the scientific method, which is based on induc-tive reasoning.

1

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Scientific Knowing

Ways of Knowing

Science as a Way of Knowing

The Scientific Method

Types of Research

Research Design and Statistical Analysis in Christian Ministry I: Research Fundamentals

Common Sense

Common sense refers to knowledge we take for granted. We learn by absorbing the customs and traditions that surround us—from family, church, community and nation. We assume this knowledge is correct because it is familiar to us. We seldom question, or even think to question, its correctness because it just is. Unless we move to another region, or go to school and study the views of others, we have nothing to challenge our way of thinking. It's just common sense!

But common sense told us that “the earth is flat” until Columbus discovered other-wise. Common sense told us that “dunce caps and caning are effective student motiva-tors” until educational research discovered the negative aspects of punishment. Common sense may well be wrong.

Authority

Authoritative knowledge is an uncritical acceptance of another’s knowledge. When we are sick, we go to the doctor to find out what to do. When we need legal help, we go to a lawyer and follow his advice. Since we can not verify the knowledge on our own, we must simply choose to accept or reject the expert's advice. It would be foolish to argue with a doctor's diagnosis, or a lawyer's perception of a case. This is the meaning of "uncritical acceptance" in the definition above. The only recourse to accepting the expert's knowledge is to get a second opinion—from another expert.

As Christians, we believe that God’s Word is the authority for our life and work. The Living Word—the Lord Himself—within us confirms the Truth of the Written Word. The Written Word confirms our experiences with the Living Word. Scripture is a valid source of authoritative knowledge.

However, we spend a lot of time discussing Scriptural interpretations. Our discus-sions often deteriorate into conflicts about “my pastor’s” interpretations. We use our own pastor’s interpretation as authoritative because of the influence he has had in our own life. (We can substitute any authoritative person here, such as a father or mother, Sunday School teacher, or respected colleague.)

But is the authority is correct? Authoritative knowing does not question the source of knowledge. Yet differing authorities cannot be correct simultaneously. How do we test the validity of an authority’s testimony?

Intuition/Revelation

Intuitive knowledge refers to truths which the mind grasps immediately, without need for proof or testing or experimentation. The properly trained mind “intuits” the truth naturally. The field of geometry provides a good example of this kind of knowing. Let’s say I know that Line segment A is the same length as line segment B. I also know that Line segment B is the same length as line segment C. From these two truths, I immediately recognize that Line segments A and C are equal. Or, in short hand,

IF A=B and B=C, THEN A=C

I do not need to draw the three lines and measure them. My mind immediately grasps the truth of the statement.

Revelation is knowledge that God reveals about Himself. I do not need test this knowledge, or subject it to experimentation. When Christ reveals Himself to us, we know Him in a personal way. We did not achieve this knowledge by our own efforts, but merely received the revelation of the Lord. We cannot prove this knowledge to others, but it is bedrock truth to those who've experienced it. Problems arise, however,

1-3

Experience

Experiential knowledge comes from “trial and error learning.” We develop it when we try something and analyze the consequences. You've probably heard comments like these: “We've already tried that and it failed.” Or another: “We’ve found that holding Vacation Bible School during the third week of August, in the evening, is best for our church.” The first is negative. The speaker is saying there's no need to try that ministry or program again, because it was already tried. The second is positive. This church has tried several approaches to offering Vacation Bible School and found the best time for them. Their “truth” may not apply to any other church in the association, but it is true for them. They’ve tried it and it worked. . .or it didn’t.

Much of the promotion of new church programs comes out of this framework. We say, “This program is being used in other churches with great success” (which means our church can have the same experience if we use this program). How do we evaluate program effectiveness? What is success? How do we measure it?

Deductive Reasoning

Deductive reasoning moves thinking from stated general principles to specific elements. We develop general over-arching statements of intent and purpose. Then we deduce from these principles specific actions we should take. Determine “world view” first. Then make daily decisions which logically derive from this perspective.

When we take the Great Commission as our primary mandate, we have framed a world view for ministry. That is, “Whatever we do, we will connect it to reaching out and baptizing (missions and evangelism), teaching (discipleship and ministry).” Now, how do we do it? We deduce specific programs, plans, and procedures for carrying out the mandate. We eliminate programs that conflict with this mandate.

How do we arrive at this “world view?” Are our over-arching principles correct? Have we interpreted them correctly? Correct action rises or falls on the basis of two things. First, correct action depends on the correctness of our world view. Secondly, correct action depends on our ability to translate that view into practical ministry steps.

Inductive Reasoning

Inductive reasoning moves thinking from specific elements to general principles.

Inductive Bible study analyzes several passages and then synthesizes key concepts into the central truth. Science is inductive in its study of a number of specifics and its use of these results to formulate a theory. The truths derived in this way are temporary and open to adjustment when new elements are discovered. Knowledge gained in this way is usually related to probabilities of happenings. We have a high degree of confidence that combining “X” and “Y” will produce effect “Z.” Or, we learn that “B” and “C” are seldom found in combination with “D.”

I can demonstrate probability by using matches. Picture yourself at the kitchen table with 100 matches. You pick up the first one. What is the probability it will light when you strike it? Well, you have two possibilities: either it will or it won’t. So the probability is 50% (1 event out of 2 possibilities). You strike it and it lights. Pick up the

Research Design and Statistical Analysis in Christian Ministry I: Research Fundamentals second match. The probability is 0.50 that it will light: (1 event out of two possibilities: Yes or No.) But cumulatively, out of two matches (first and second), one lit. One out of two is 50%. So the probability of the second match lighting is 50%, because 1 of 2 have already lit. You strike it and it lights.

Pick up the third match. Again, the third match taken alone has “p = 0.50” of lighting (read ‘probability equals point-five-oh’). However, taking all three matches together, two of the three have lit and the probability is 2/3 (“p = 0.66”) that the third

match will light. It does.

Now, pick up the fourth match. The probability is 3/4 (p=0.75) that it will light, taking all four matches together.

What about the 100th match, given that the 99 previous matches have all lit? The probability is 0.50 for this particular match (yes, no), but p = 0.99 taking all matches together. The probability is very high! Yet we cannot absolutely guarantee it will light.

This is the nature of inductive logic, and inductive logic is the basis of scientific knowledge. By definition, science does not deal with absolute Truth. Science seeks knowledge about processes in our world. Researchers gather information through observation. They then mold this information into theories. The scientific community tests these theories under differing conditions to establish the degree to which they can be generalized. The result is temporary, open-ended truth (I call it little-t truth to distin-guish it from absolute Truth). This kind of truth is open for inquiry, further testing, and probable modification. While this kind of knowing can add nothing to our faith, it is very helpful in solving ministry problems.

Science as a Way of Knowing

Scientific knowing is based on precise data gathered from the natural world we live in. It builds a knowledge base in a neutral, unbiased manner. It seeks to measure the world precisely. It reports findings clearly so that others can duplicate the studies. It forms its conclusions on empirical data. Let’s look at these ideals more closely.

Objectivity

Human beings are complex. Personal experiences, values, backgrounds, and beliefs make objective analysis difficult unless effort is made to remain neutral. Optimists tend to see the positive in situations. Pessimists see the negative. But scientists look for objective reality — the world as it is — uncolored by personal opinion or feelings.

Scientific knowing attempts to eliminate personal bias in data collection and analy-sis. Honest researchers take a neutral position in their studies. That is, they do not try to prove their own beliefs. They are willing to accept empirical results contrary to their own opinions or values.

Precision

Reliable scientific knowing requires precise measurement. Researchers carry out experiments under controlled, narrow conditions. They carefully design instruments to be as accurate as possible. They evaluate tests for reliability and validity. They use pilot projects (trial runs of procedures) to identify sources of extraneous error in measure-ments. Why? Because inaccurate measurement and undefined conditions and unreli-able instruments and extraneous errors produce data that is worthless. Every score has two parts: the true measure of the subject, and an unknown amount of error. We can represent this as Objectivity Precision Verification Empiricism Goal: Theories

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Score = True Measure + Error

Think of two students who are equally prepared for an exam. When they arrive in class, one is completely healthy and the other has the flu. They will likely score differ-ently on the exam. In this case, illness introduces an error term into the second student's score.

When we gather data in a haphazard, disorderly way, error interferes with the true measure of the variable. Like static on a television screen, the error masks the true picture of the data. Analysis of this noisy data will provide a numerical answer which is suspect. Accurate measurement is a vital ingredient in the research process.

Verification

Science analyzes world processes which are systematic and recurring. Researchers report their findings in a way that allows others to replicate their studies — to check the facts in the real world. These replications either confirm or refute the original findings. When researchers confirm earlier results, they verify the earlier findings. Research reports provide readers the background, specific problem(s) and hypotheses of studies. Also included are the populations, definitions, limitations, assumptions, as well as procedures for collecting and analyzing data. Writers do this intentionally so others can evaluate the degree that findings can be generalized, and perhaps, replicate the study.

Empiricism

The root of “empiricism” (Greek, empeirikos) refers to the “employment of empirical methods, as in science,” or “derived from observation or experiment; verifiable or provable by means of observation or experiment.”1 _{Science uses the term to underscore} the fact that it bases its knowledge on observations of specific events, not on abstract philosophizing or theologizing. These carefully devised observations of the real world form the basis of scientific knowledge. Therefore, the kinds of problems which science can deal with are testable problems.

Empirical data is gathered by observation. Basic observations can be done with the naked eye and an objective checklist (see Chapter 9). But observations are also made with instruments such as an interview or questionnaire (Chapter 10), a test (Chapter 11), an attitude scale (Chapter 12), or a controlled experiment (Chapter 13). Scientific knowing cares less about philosophical reasoning than it does the rational collection and

analysis of factual data relevant to the problem to be solved.

Goal: Theories

The goal of scientific research is theory construction, the development of theories which explain the phenomena under study, not the mere cataloging of empirical data. The inductive process of scientific knowing begins with the specifics (collected data) and leads to the general (theories). What causes cancer? What makes it rain? How does man learn? What is the best way to relieve anxiety? What effect do children have on marital satisfaction?

Most ministerial students want pragmatic answers to pragmatic problems in the ministry. In the past ten years [during the 1980’s] there have been a rash of studies

1_{"Empiricism," "empirical." The American Heritage Dictionary, 3rd ed., Version 3.0A, WordStar International,} 1993.

Research Design and Statistical Analysis in Christian Ministry I: Research Fundamentals relating some variable to church growth. The pragmatic question is “How do I make my church grow?” But Christian research goes deeper. It looks beyond the surface of ministry programming to the social, educational, psychological, and administrative dynamics of church life and work. Each of these areas have many theories and theorists giving advice and explanation. Are these views valid for Christian ministry? Can you modify these theories for effective use in church ministry? Seek a solid theoretical base for your proposal.

The Scientific Method

The scientific method is a step-by-step procedure for solving problems on the basis of empirical observations. Here are the major elements:

1. Begin with a “felt difficulty.” What is your interest? What questions do you want answered? How might a theory be applied in a specific ministry situation? What conflicting theories have you found? The felt difficulty is the beginning point for any study (but it has no place in the proposal).

2. Write a formal “Problem Statement.” The Problem establishes the focus of the study by

stating the necessary variables in the study and what you plan to do with them (see Chapter 4).

3. Gather literature information. What is known? Before you plan to do a study of your

own, you must learn all you can about what is already known. This is done through a literature search and results in a synthesis of recent findings on the topic (see Chap 6). 4. State hypothesis. On the basis of the literature search, write a hypothesis statement that

reflects your best tentative solution to the Problem (see Chapter 4).

5. Select a target group (population). Who will provide your data? How will you find

subjects for your study? Are they accessible to you? (see Chapter 7)

6. Draw one or more samples, as needed. How many samples will you need? What kind of sampling will you use? (see Chapter 7).

7. Collect data. What procedure will you use to actually collect data from the subjects?

Develop a step-by-step plan to obtain all the data you need to answer your questions (see Chapters 9-13).

8. Analyze data. What statistics will you use to analyze the data? Develop a step-by-step

plan to analyze the data and interpret the results (see Chapters 14-25).

9. Test the null, or statistical, hypothesis. On the basis of the statistical results, what

deci-sion do you make concerning your hypothesis? (see Chapters 16-26).

10. Interpret the results. What does the statistical decision mean in terms of your study?

Translate the findings from “statistics” to English. (see Chapters 16-26)

The scientific method provides a clear procedure for empirically solving problems. In chapter 2 we introduce you to the structure of a research proposal. As you read the chapter, notice how the elements of the proposal follow the steps of the scientific method. Refer back to this outline in order to understand the links between the

scien-Felt Difficulty Problem Literature Hypothesis Population Sample(s) Collect Analyze Test Interpret

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Types of Research

Under the umbrella of scientific research, there are several types of studies you can do. These types differ in procedure — what they entail — and outcome — what they accomplish. Here are four major and three minor types of research from which you may choose.

Historical Research

Historical research analyzes the question “what was?” It studies documents and relics in order to determine the relationship of historic events and trends to present-day practice.

Primary sources

A source of information is primary when it is produced by the researcher. Reports written by researchers who conduct studies are “eye witness” accounts, and are pri-mary sources of information on the results. Other examples of pripri-mary sources are autobiographies and textbooks written by authors who conduct their own research. Use primary sources as the major source of information in the Related Literature section of your proposal. Primary sources take two forms: documents and relics.

Documents. Society creates documents to expressly record events. They are objective and direct. Documents provide straightforward information. Average Bible Study attendance listed on the Annual Church Letters on file in the state convention office is more likely to be accurate than numbers given from memory by ministers of education in local churches. However, information contained in documents may be incorrect. The documents may have been falsified, or word meanings in the documents may have changed.

Relics. Society creates relics simply by living. Relics are artifacts left by commu-nities and cultures in the past. People did not create these objects to record information as is the case with documents. Therefore, information conveyed by relics requires interpretation. The historical researcher reconstructs the meaning of relics in the context of their time and place.

Secondary sources

A source of information is secondary when it is a second-hand account of research.

Secondary sources may take the form of summaries, news stories, encyclopedias, or textbooks written by synthesizers of research reports. While secondary sources provide the bulk of materials used in term papers, you should use them only to provide a broad view of your chosen topic. As already stated, emphasize the use of primary sources in your Synthesis of Related Literature.

Criticism

The term “criticism” has a decidedly negative connotation to most of us. A critical person is one who finds fault, depreciates, or puts down someone or something. The term comes from the Greek krino, to judge. Webster defines “criticism” as the “art, skill, or profession of making discriminating judgments and evaluations, especially of literary or other artistic works."2 _{Criticism can therefore refer to praise as well as depreciation. A}

Historical Descriptive Correlational Experimental Ex Post Facto Evaluation Research/Dev

Research Design and Statistical Analysis in Christian Ministry I: Research Fundamentals Christian may cringe when he hears someone speaks of using “higher criticism” to study Scripture. It sounds as if the scholar is criticizing -- berating, slandering, putting down -- the Bible. The term actually means that scholars objectively analyze language, culture, and comparative writings to determine the authenticity of the work. Who wrote Hebrews? Paul? Apollos? Peter? Scholars apply the systematic tools of content analy-sis and “literary criticism” to determine the answer. Criticism takes two major forms: External criticism and internal criticism.

External criticism. External criticism answers the question of genuineness of the object. Is the document or relic actually what it seems to be? What evidence can we gather to affirm the authenticity of the object itself? For example, is this painting really a Rembrandt? Was this letter really written by Thomas Jefferson? External criticism focuses on the object itself.

Internal criticism. Internal criticism answers the question of trustworthiness of the object. Can we believe what the document says? What ideas are being conveyed? What does the writer mean by his words, given the culture and time period he wrote? Internal criticism focuses on the object’s meaning.

Examples

Historical research is not merely the collection of facts from secondary sources about an historic event or process. It is the objective interpretation of facts, in line with parallel events in history. The goal of historical research is to in explain the underlying causes of present practices. Most of the historical dissertations written by our students have focused on former deans and faculty members. Dr. Phillip H. Briggs studied the contributions of Dr. J. M. Price, Founder and Dean of the School of Religious Educa-tion.3 _{Dr. Robert Mathis analyzed the contributions of Dr. Joe Davis Heacock, Dean of} the School of Religious Education, 1950-1973.4 _{Dr. Carl Burns evaluated the} contribu-tions of Dr. Leon Marsh, Professor of Foundacontribu-tions of Education, School of Religious Education, Southwestern Seminary, 1956-1987.5 _{Dr. Sophia Steibel analyzed the Life} and Contributions of Dr. Leroy Ford, Professor of Foundations of Education, 1956-1984.6 Dr. Douglas Bryan evaluated the contributions of Dr. John W. Drakeford, Professor of Psychology and Counseling.7

Descriptive Research

Descriptive research analyzes the question “what is?” A descriptive study collects data from one or more groups, and then analyzes it in order to describe present condi-tions. Much of this textbook underscores the tools of descriptive research: survey by questionnaire or interview, attitude measurement, and testing. A popular use of de-scriptive research is to determine whether two or more groups differ on some variable of interest.

3_{Phillip H. Briggs, “The Religious Education Philosophy of J. M. Price,” (D.R.E. diss., Southwestern} Baptist Theological Seminary, 1964).

4_{Robert Mathis, “A Descriptive Study of Joe Davis Heacock: Educator, Administrator, Churchman,”} (Ed.D. diss., Southwestern Baptist Theological Seminary, 1984)

5_{Carl Burns, “A Descriptive Study of the Life and Work of James Leon Marsh,” (Ed.D. diss.,} South-western Baptist Theological Seminary, 1991)

6_{Sophia Steibel, “An Analysis of the Works and Contributions of Leroy Ford to Current Practice in} Southern Baptist Curriculum Design and in Higher Edcuation of Selected Schools in Mexico,” (Ed.D. diss., Southwestern Baptist Theological Seminary, 1988)

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An Example

The goal of descriptive research is to accurately and empirically describe differences between one or more variables in selected groups. Dr. Dan Southerland studied differ-ences in ministerial roles and allocation of time between growing and plateaued or declining Southern Baptist churches in Florida.6 _{Specified roles were pastor, worship}

leader, organizer, administrator, preacher and teacher.7 _{The only role which showed} significant difference between growing and non-growing churches was the amount of time spent serving as “organizer,” which included “vision casting, setting goals, leading and supervising change, motivating others to work toward a vision, and building groupness.”8

Correlational Research

Correlational research is often presented as part of the descriptive family of meth-ods. This makes sense since correlational research describes association between vari-ables of interest in the study. It answers the question “what is” in terms of relationship among two or more variables. What is the relationship between learning style and gender? What is the relationship between counseling approach and client anxiety level? What is the relationship between social skill level and job satisfaction and effectiveness for pastors? In each of these questions we have asked about an association between two or more variables.

Correlational research also includes the topics of linear and multiple regression

which uses the strengths of associations to make predictions. Finally, correlational analysis includes advanced procedures like Factor Analysis, Canonical Analysis, Dis-criminant Analysis, and Path Analysis — all of which are beyond the scope of this course.

An Example

The goal of correlational research is to establish whether relationships exist be-tween selected variables. Dr. Robert Welch studied selected factors relating to job satisfaction in staff organizations in large Southern Baptist Churches.9 _{He found the} most important intrinsic factors affecting job satisfaction were praise and recognition for work, performing creative work and growth in skill. The most important extrinsic factors were salary, job security, relationship with supervisor, and meeting family needs.10 _{Findings were drawn from 579 Southern Baptist ministers in 153 churches.}11

Experimental Research

Experimental research analyzes the question “what if?” Experimental studies use carefully controlled procedures to manipulate one (independent) variable, such as

6_{Dan Southerland, “A Study of the Priorities in Ministerial Roles of Pastors in Growing Florida} Baptist Churches and Pastors in Plateaued or Declining Florida Baptist Churches,” (Ed.D. diss., Southwest-ern Baptist Theological Seminary, 1993)

7_{Ibid., 1} 8_{Ibid., 2}

9_{Robert Horton Welch, “A Study of Selected Factors Related to Job Satisfaction in the Staff} Organiza-tions of Large Southern Baptist Churches,” (Ed.D. diss., Southwestern Baptist Theological Seminary, 1990)

Research Design and Statistical Analysis in Christian Ministry I: Research Fundamentals Teaching Approach, and measure its effect on other (dependent) variables, such as Student Attitude and Achievement. Manipulation is the distinguishing element in experimental research. Experimental researchers don’t simply observe what is. They

manipulate variables and set conditions in order to design the framework for their observations. What would be the difference in test anxiety across three different types of tests? Which of three language training programs is most effective in teaching foreign languages to mission volunteers? What is the difference between Counseling Approach I and Counseling Approach II in reducing marital conflict?

In each of these questions we find a researcher introducing a treatment (type of test, training program, counseling approach) and measuring an effect. Experimental

Research is the only type which can establish cause-and-effect relationships between independent and dependent variables. See Chapter 13 for examples of experimental designs.

An Example

The goal of experimental research is to establish cause-effect relationships between independent and dependent variables. Dr. Daryl Eldridge analyzed the effect of know-ledge of course objectives on student achievement in and attitude toward the course.12 He found knowledge of instructional objectives produced significantly higher scores on the Unit I exam (mid-range cognitive outcomes) but not on the Unit III exam (knowl-edge outcomes). Knowl(knowl-edge of objectives did produce significantly higher scores on the postcourse attitude inventory.13

Ex Post Facto Research

Ex Post Facto (which translates into English as “after the fact”) research is similar to experimental research in that it answers the question, “what if?” But in ex post facto designs, nature — not the researcher — manipulates the independent variable. In studying the effects of brain damage on the attitudes of children toward God, it would be immoral and unethical to randomly select two groups of children, brain damage one of them, and then test for differences!

But in an ex post facto approach the researcher defines two populations: normal children and brain-damaged children. Nature has applied the treatment of brain dam-age. The experiment is done “after the fact” of the brain damaged condition. Experi-mental studies involving juvenile delinquency, AIDS, cancer, criminal or immoral behavior and the like all require an Ex Post Facto approach.

An Example

The goal of ex post facto research is to establish cause-and-effect relationships between independent and dependent variables “after the fact” of manipulation. An example of Ex Post Facto research would be “An Analysis of the Difference in Social Skills and Interpersonal Relationships Between Congenitally Deaf and Hearing College Students.” Congenital deafness in this case is the treatment already applied by nature.

Evaluation

Evaluation is the systematic appraisal of a program or product to determine if it is accomplishing what it proposes to do. It is the application of the scientific method to the

12_{Daryl Roger Eldridge, “The Effect of Student Knowledge of Behavioral Objectives on Achievement} and Attitude Toward the Course,” (Ed.D. diss., Southwestern Baptist Theological Seminary, 1985)

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The danger in choosing an evaluation type study for dissertation research is the

political ramifications which come if the evaluation proves embarrassing to the church or agency conducting the program. Program leaders may not appreciate negative evaluations and apply pressure to modify results. This distorts the research process. Suppose you choose to evaluate a new counselor orientation program at a highly visible counseling network — and you find the program substandard. Will this impact your ability to work with this agency as a counselor? Or suppose you want to compare Continuous Witness Training (CWT) with Evangelism Explosion (EE) as a witness training program. What are the implications of your finding one program much better than the other?

An Example

The goal of evaluation research is to objectively measure the performance of an existing program in accordance with its stated purpose. An example of this type of study would be “A Critical Analysis of Spiritual Formation Groups of First Year Stu-dents at Southwestern Baptist Theological Seminary.” Program outcomes are measured against program objectives to determine if Spiritual Formation Groups accomplish their purpose.

Research and Development

Research and Development (“R&D”) is the application of the scientific method in

creating a new product: a standardized test, or program, or technique. R&D is a cyclical process in which developers (1) state the objectives and performance levels of the

product, (2) develop the product, (3) measure the results of the product's performance, and (4) (if the results of the treatment do not meet the stated levels) revise the materials for further testing. “Cyclical process” means that the materials are revised and tested until they perform according to the standards set at the beginning of the product's development.

An Example

The goal of research and development is the production of a new product which performs according to specified standards. Dr. Brad Waggoner developed an instru-ment to measure “the degree to which a given church member manifests the functional characteristics of a disciple.”14

Two pilot tests using this original instrument produced Cronbach Alpha reliability coefficients of 0.9745 and 0.9618, demonstrating its ability to produce a reliable mea-surement of a church member's functional characteristics of a disciple.15_{In 1998, this}

instrument was incorporated into MasterLife materials produced by LifeWay Christian Resources (SBC).16

14_{Brad J. Waggoner, “The Development of an Instrument for Measuring and Evaluating the} Disciple-ship Base of Southern Baptist Churches,” (Ed.D. diss., Southwestern Baptist Theological Seminary, 1991)

15_{Ibid., 118}

16_{Report of joint development between Lifeway and the International Mission Board (SBC) at the 1998} Meeting of the Southern Baptist Research Fellowship.

Research Design and Statistical Analysis in Christian Ministry I: Research Fundamentals

Qualitative Research

In 1979 the faculty of the School of Religious Education at Southwestern created a teaching position for research and statistics. Their desire was for this position to give emphasis to helping students understand research methods and procedures for statisti-cal analysis. It was further the desire that doctoral research become more objective and scientific, less philosophical and historical. In 1981, after two years of interviews and discussions, Religious Education faculty voted, and the president approved, my elec-tion to their faculty to provide this emphasis. This textbook, and the dissertaelec-tion ex-amples it contains, are products of 25 years of emphasis on descriptive, correlational and experimental research -- most of which is quantitative or statistical in nature.

In recent years interest has grown in research methods which focus more on the issue of quality than quantity.A qualitative study is an inquiry process of understand-ing a social or human problem, based on buildunderstand-ing a complex, holistic picture, formed with words, reporting detailed views of informants, and conducted in a natural set-ting.17 _{Dr. Don Ratcliff, in a 1999 seminar for Southwestern doctoral students,} sug-gested the following as the most common qualitative research designs: ethnography, field study, community study, biographical study, historical study, case study, survey study, observation study, grounded theory and any combination of the above.18

Grounded theory is a popular choice of qualitative researchers. It originated in the field of sociology and calls for the researcher to live in and interact with the culture or people being studied. The researcher attempts to derive a theory by using multiple stages of data collection, along with the process of refining and inter-relating categories of information.19

Qualitative research is subjective, open-ended, evolving and relies on the ability of the research to reason and logically explain relationships and differences. Dr. Marcia McQuitty, Professor of Childhood Education in our school, has become our resident expert in qualitative designs. I continue to focus on quantitative research, which is, in comparison, objective, close-ended (once problem and hypothesis is established), structured and relies on the ability of the research to gather and statistically analyze valid and reliable data to explain relationships and differences.

Faith and Science

What is the relationship between faith and science? Are faith and science enemies? Can ministers use scientific methodology to study the creation and retain a fervent faith in the Creator. I believe we can -- and should. But care must be taken to consciously mark out the boundaries of each. There is a difference between faith-knowing and scientific knowing, and that difference sometimes explodes into conflict — a conflict fueled by both sides. First we'll look at the suspicion of science by the faithful. Then we'll consider the suspicion of religion by scientists.

Suspicion of Science By the Faithful

Anselm wrote in the 10th century, “I believe so that I may understand.” In other words, commitment and faith are essential elements in gaining spiritual understanding.

17_{Randy Covington, “An Investigation into the Administrative Structure and Polity Practiced by the} Union of Evangelical Christians - Baptists of Russia,” (Ph.D. proposal, Southwestern Baptist Theological Seminary, 1999), 20 paraphrasing John W. Creswell, Research Design: Qualitative and Quantitative

Ap-proaches (Thousand Oaks, CA: Sage Publications, ,1994), 1-2

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Blaise Pascal wrote in the 17th century, “The heart has reasons which are unknown to reason.... It is the heart which is aware of God and not reason. That is what faith is: God perceived intuitively by the heart, not by reason.” The truth of Christ comes by living it out, by risking our lives on Him, by doing the Word. We grow in our know-ledge of God through personal experience as we follow Him and work with Him. We believe in order to understand spiritual realities. This approach to knowing is private and subjective. Such belief-knowing resents an anti-supernatural skepticism of open-minded inquiry. More than that, some scientists consider the scientific method to be their religion. Their “belief in evolution” may be a justification for their unbelief in God.

Science is helpful in learning about our world, but it makes a poor religion. So the faithful view science and its adherents with suspicion.

Sometimes, however, the suspicion of science by the religious has less to do with faith than it does political power. In the Middle Ages, the accepted view of the universe was geocentric (“earth-center”). The moon, the planets, the sun (located between be-tween Venus and Mars) and the stars were believed to rotate about the earth in perfect circles. This view had three foundations: science, philosophy and the Church.

Greek science ( Ptolemy) and Greek philosophy (Aristotle) supported a geocentric view of the universe. The logic was rock solid for centuries: Man is the pinnacle of creation. Therefore, the earth must be the center of the universe.

The Roman Catholic Church taught that the geocentric view was Scriptural, based on Joshua 10:12-13.

“Joshua said to the LORD in the presence of Israel: 'O sun, stand still over Gibeon, O moon, over the Valley of Aijalon.' So the sun stood still, and the moon stopped, till the nation avenged itself on its enemies, as it is written in the Book of Jashar. The sun stopped in the middle of the sky and delayed going down about a full day.”

For the sun and moon to stand still, the Church fathers reasoned, they would have to be circling the earth.

Then several scientists began their skeptical work of actually observing the move-ments of the planets and stars.Copernicus, a Polish astronomer, created a 15th century revolution in astronomy when he published his heliocentric (“sun-center”) theory of the solar system. He theorized, on the basis of his observations and calculations, that the earth and its sister planets revolved around the sun in perfect (Aristotelian) circles.

Keplar later demonstrated that the solar system was indeed heliocentric, but that the planets, including earth, orbited the sun in elliptical, not circular, paths. The Roman Catholic Church attacked their views because they displaced earth from its position of privilege, and opened the door to doubt in other areas. But Poland is a long way from Rome (it was especially so in the 15th century!), and so Copernicus and Keplar re-mained outside the Church's reach.

Galileo is the father of modern Physics and did his work in Italy in the 16th and 17th centuries. He studied the work of Copernicus and Keplar, and built a telescope in order to more closely observe the planets. In 1632, he published the book Dialogue Concerning the Two Chief World Systems: Ptolemaic and Copernican, in which he supported a heliocentric view of the solar system. He was immediately attacked by Church au-thorities who continued to espouse a geocentric world view. Professors at the Univer-sity of Florence refused to look through Galileo's telescope: they did not believe his theory, so they refused to observe. Very unscientific! Galileo, under threat of being burned at the stake, recanted his findings. It was not until October 1992 that the Roman