While researchers use descriptive statistics to summarize data sets, they use inferential statistics to determine whether differences actually exist in the populations from which samples were drawn. For instance, suppose you find that the mean ratings of how much women want to have fun after work varied with the number of hours the women worked. How different do these means need to be between each exper-imental group and the control group for you to conclude that they reflect real dif-ferences in the larger population of women, all of whom work different numbers of hours? Recall that we use samples from a population when we conduct research;
then, depending on what we find in our study, we generalize our findings back to the population from which we sampled. Researchers use inferential statistics to decide
inferential statistics A set of procedures used to make judgments about whether differences actually exist between sets of numbers.
if the differences in sample means reflect differences in the populations from which they were drawn. How does this work? Assume for a moment that the number of hours women work does not influence their ratings of how much they want to have fun. Even so, if you measure the ratings made by women who work different num-bers of hours, just by chance there will be some variability in the mean ratings made by the women in the different groups.We use statistical techniques to determine if the differences among the sample means are (probably) chance variations or whether they reflect differences in the populations.
The principle is the same as for how many heads appear when you flip a coin ten times: On average, the number will be five or close to it, but every now and then, just by chance, you will get no heads or ten heads.Therefore, when you are comparing two means, inferential statistics tell you how probable the outcome would be if there were no differences between the ratings made by participants in the two groups.This is the general logic researchers use to determine whether the differences between the groups represent real differences in the populations from which the groups were drawn.
When the results obtained from a study would be very unlikely to occur if there really were no differences among the groups of subjects, the researchers conclude that the results are statistically significant. How unusual do the results have to be for researchers to conclude that they are statistically significant? The coin-flipping example should help explain this concept. Suppose you and a friend stop for coffee every day, and your friend suggests that he will flip a coin each day to decide who pays. Heads means you pay; tails means he pays.The first day, he flips heads; the second day, he flips heads again. How many coin flips would it take before you asked him if he was using a fair coin? Few people would be willing to accuse a friend of cheating after three heads in a row. But what about five or six heads in a row? Generally accepted standards deter-mine how unusual a result must be before we say it is statistically significant: It would have to occur less than 5 percent of the time if no other factors affect the results. In this case, if the coin is fair, there is a greater than 5 percent chance of flipping three heads in a row (12.5 percent) but a less than 5 percent chance of flipping five heads in a row (3.125 percent). Similarly, in the example above, if the women in the no-work group rated their desire to have fun as a 2 (mean rating for the group) and those in the 10-hour work group rated their desire to have fun as a 9, we would use statisti-cal methods to determine if this outcome would occur less than 5 percent of the time if the groups really were the same in all other respects. If the data meet this statistical test, we would say the results are statistically significant.
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S U M M I N G U PHow Are Data Analyzed and Evaluated?
Data analysis begins with descriptive statistics, which summarize the data. Measures of central tendency indicate statistical averages across sets of numbers, whereas the standard deviation indicates how widely numbers are distributed about an aver-age. Correlations describe the relationship between two variables: positive, negative, or none. Inferential statistics show whether the results of a study were due to the effect of one variable on another or whether the results were more likely due to chance.
M E A S U R I N G U P
1. When researchers want to summarize in a single number all the data they collect, they compute a measure of central tendency. Here are hypothetical data for a study in which 10 women in a sample indicated how many
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hours they worked that day and then used a rating scale to indicate how much they wanted to have fun. The rating scale ranged from 1 (“not at all”) to 10 (“I want to have fun more than anything else in the world”). For each set of data, compute the mean, median, and mode.
Now, using a grid like the one in Figure 2.24, draw a scatterplot of the data in question 1. When you are finished, look at the plot and decide if it represents a positive, a negative, or no (linear) correlation between these two variables. Explain what the scatterplot is showing, in your own words.
2. Which is an accurate description of the rationale for inferential statistics?
a. When the means of two sample groups are significantly different, we still need to compute a mean value for each population before we can con-clude that the groups really are different.
b. When the means of two sample groups are significantly different, we can be fairly certain that we did not make any mistakes in our research.
c. When the means of two sample groups are significantly different, we can be certain that the data are not correlated.
d. When the means of two sample groups are significantly different, we can infer that the populations the groups were selected from are different.
C O N C LU S I O N
This chapter has presented the major issues involved in designing and conduct-ing research in psychological science. However, the ideas discussed here are most important when research is evaluated. The quality of research matters whether or not you have conducted the experiments yourself. Every day, the media report some new major finding, such as the link between height and self-esteem and salary discussed above. Should you believe a report and perhaps change your daily life as a result? Should you ignore new and potentially important data, because they came from a flawed study? To make educated decisions in this domain, as well as in your everyday experiences, requires understanding the way good psy-chological science is conducted, an understanding that in turn requires good crit-ical thinking skills.
Number of Rating of how much they
hours worked want to have fun
5 5
5 6
8 7
6 6
4 10
6 5
2 4
10 7
8 9
3 5
Mean ⫽ Mean ⫽
Median ⫽ Median ⫽
Mode ⫽ Mode ⫽
So what determines good science? Quality research stems from sound metho-dology and good questions. A number of factors need to be considered. Is a good theory guiding the design of the research? Were the method and level of analysis appropriate for the question of interest? Does the study have adequate operational definitions for the variables involved? Have the researchers presented their results as though the results show a causal relationship between two vari-ables, even though an experiment was not performed? If an experiment was per-formed, was it carefully designed and well controlled, or might potential confounds have been overlooked? Did the researchers randomly assign partici-pants to different experimental groups? How large was the sample, and were the participants representative of the population of interest? Was the research cultur-ally sensitive, or did the researchers make the mistake of assuming that people in all cultures would respond the same way? These fundamental questions under-score the necessity of being a critical, well-informed research evaluator. If you cannot answer these questions when reading about a study, you cannot properly evaluate whether you should believe the results or the way those results have been interpreted.
TEST PREP ARATION
What Is Scientific Inquiry?
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The Scientific Method Depends on Theories, Hypotheses, and Research:Scientific inquiry relies on objective methods and empirical evidence to answer testable questions. Interconnected ideas or models of behaviour (theories) yield testable predictions (hypotheses), which are tested in a systematic way (research) by collecting and evaluating evi-dence (data).•
Unexpected Findings Can Be Valuable:Unexpected (serendipitous) discoveries sometimes occur, but only researchers who are prepared to recognize their importance will benefit from them.What Are the Types of Studies in Psychological Research?
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Descriptive Studies Involve Observing and Classifying Behaviour:Researchers observe and describe naturally occurring behaviours to pro-vide a systematic and objective analysis.
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Correlational Designs Examine How Variables Are Related:Correlational studies are used to examine how variables are naturally related in the real world, but cannot be used to establish causality or the direction of a relationship (which variable caused changes in another variable). Correlational reasoning occurs in many contexts, so readers need to be able to recognize correlational designs in everyday contexts, not just when reading research reports.
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An Experiment Involves Manipulating Conditions:In an experi-ment, researchers control the variations in the conditions that the par-ticipant experiences (independent variables) and measure the outcomes (dependent variables) to gain an understanding of causality. Researchers need a control group to know if the experiment had an effect.•
Random Assignment Is Used to Establish Equivalent Groups:Researchers sample participants from the population they want to study (e.g., all women who work).They use random sampling when everyone in the population is equally likely to participate in the study, a condition that rarely occurs.To establish causality between an intervention and an outcome, all participants must be equally likely to be in the experi-mental group or the control group, to control for pre-existing group differences.
What Are the Data Collection Methods of Psychological Science?
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Observing Is an Unobtrusive Strategy:Data collected by observa-tion must be defined clearly and collected systematically. Bias may occur in the data because the participants are aware they are being observed or because of the observer’s expectations.•
Case Studies Examine Individual Lives and Organizations:A case study, one kind of descriptive study, examines an individual or an organization. An intensive study of an individual or organization canbe useful for examining an unusual participant or unusual research question. Interpretation of a case study, however, can be subjective.
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Asking Takes a More Active Approach:Surveys, questionnaires, and interviews can be used to directly ask people about their thoughts and behaviours. Self-report data may be biased by the respondents’desire to present themselves in a particular way (e.g., smart, honest).
Culturally sensitive research recognizes the differences among people from different cultural groups and from different language backgrounds.
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Response Performance Measures Information Processing:Measuring reaction times and reaction accuracy and asking people to make stimulus judgments are methods used to examine how people respond to psychological tasks.
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Body/Brain Activity Can Be Measured Directly: Electro-physiology (often using an electroencephalograph, or EEG) measures the brain’s electrical activity. Brain imaging is done using positron emis-sion tomography (PET), magnetic resonance imaging (MRI), and func-tional magnetic resonance imaging (fMRI). Transcranial magnetic stimulation (TMS) disrupts normal brain activity, allowing researchers to infer the brain processing involved in particular thoughts, feelings, and behaviours.•
Research with Animals Provides Important Data: Research involving nonhuman animals provides useful, although simpler, models of behaviour and of genetics. The purpose of such research may be to learn about animals’ behaviour or to make inferences about human behaviour.•
There Are Ethical Issues to Consider:Ethical research is governed by a variety of principles that ensure fair and informed treatment of participants.How Are Data Analyzed and Evaluated?
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Good Research Requires Valid, Reliable, and Accurate Data:Data must be meaningful (valid) and their measurement reliable (i.e., consistent and stable) and accurate.
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Descriptive Statistics Provide a Summary of the Data:Measures of central tendency and variability are used to describe data.•
Correlations Describe the Relationships between Variables:A correlation is a descriptive statistic that describes the strength and direc-tion of the reladirec-tionship between two variables. Correladirec-tions close to zero signify weak relationships; correlations near ⫹1.0 or ⫺1.0 signify strong relationships.•
Inferential Statistics Permit Generalizations:Inferential statistics allow us to decide whether differences between two or more groups are probably just chance variations (suggesting that the populations the groups were drawn from are the same) or whether they reflect true dif-ferences in the populations being compared.■ P R A C T I C E T E S T
1.Which of the following is a technique that increases scientists’ confi-dence in the findings from a given research study?
a. amiable skepticism
b. operationalization of variables c. replication
d. serendipity
For the following five questions, imagine you are designing a study to investi-gate whether deep breathing causes students to feel less stressed. Because you are investigating a causal question, you will need to employ experimental research.
For each step in the design process, indicate the most scientifically sound decision.
2.Which hypothesis is stronger? Why?
a. Stress levels will differ between students who engage in deep breathing and those who do not.
b. Students who engage in deep breathing will report less stress than those who do not engage in deep breathing.
3.Which sampling method is strongest? Why?
a. Obtain an alphabetical list of all students enrolled at the universi-ty. Invite every fifth person on the list to participate in the study.
b. Post a note to your Facebook and MySpace accounts letting friends know you would like their help with the study. Ask your friends to let their friends know about the study, too.
c. Post fliers around local gyms and yoga studios inviting people to participate in your study.
4.Which set of conditions should be included in the study? Why?
a. All participants should be given written directions for a deep breathing exercise.
b. Some participants should be given written directions for a deep breathing exercise; some participants should be given a DVD with demonstrations of deep breathing exercises.
c. Some participants should be given written directions for a deep breathing exercise; some participants should be given no instruc-tions regarding their breathing.
5.How should participants be chosen for each condition? Why?
a. Once people agree to participate in the study, flip a coin to decide if each will be in the experimental or control condition.
b. Let participants select which condition they would like to be in.
6.Which operational definition of the dependent variable, stress, is stronger? Why?
a. Stress is a pattern of behavioural and physiological responses that match or exceed a person’s abilities to respond in a healthy way.
b. Stress will be measured using five questions asking the participant to rate his or her stress level on a scale from 1 to 10, where 1 equals “not at all stressed” and 10 equals “as stressed as I’ve ever been.”
For the following three questions, imagine you want to know whether students at your university talk about politics in their day-to-day lives.To inves-tigate this issue, you would like to conduct an observational study and need to make three design decisions. For each decision, recommend the most appropriate choice.
7.Should you conduct the study in a lab or in a natural setting (e.g., in the campus dining hall)? Why?
8.Should you use written descriptions of what is heard or a running tally of prespecified categories of behaviour? Why?
9.Should participants know you are observing them? Why?
10.Indicate which quality of good data is violated by each description.
Response options are “accuracy,” “reliability,” “validity.”
a. A booth at the local carnival announces the discovery of a new way to assess intelligence.The assessment method involves inter-preting the pattern of creases on one’s left palm.
b. At the end of a long night of grading, a professor reads what he believes to be the last essay in the pile. He assigns it a grade of 80%.When he goes to write the grade on the back of the paper, he realizes he has already graded this paper earlier in the evening—and only gave it a 70% the first time around.
c. A five-year-old counts the jelly beans in a jar, often skipping over numbers ending in 8 (e.g., 8, 18, 28).
1.Identify a song lyric that makes a claim about human behaviour.
Elaborate and/or refine this claim, focusing the question in a way that addresses a goal of empirical inquiry: description, prediction, identifying causes, or making explanations. Clearly label the goal most relevant to your question.
2.Locate a claim about human behaviour in a newspaper or magazine or on the Internet. Evaluate the claim using at least three ideas from this chapter. Some ideas from the chapter that lend themselves to this sort of analysis are validity, reliability, accuracy, central tendency, vari-ability, descriptive studies, correlational studies, experiments, random assignment, control group, ethics.
The answer key for all the Measuring Up exercises and the Practice Tests can be found at the back of the book.