Semiconductor (MFIS) FeFET:
2.6 Depolarization, Charge Injection and Trapping Effects:
UNIT 2: ANALYSING QUANTITATIVE DATA
Coding can be a simple clerical task when the data are recorded as numbers on well-organized record sheets, but it is very difficult when, for example, a researcher wants to code answers to open-ended survey questions into numbers in a process similar to latent content analysis.
Researchers use a coding system and a code-book for data coding. The coding system is a set of rules stating that certain numbers are assigned to variable attributes. For example, a researcher codes males as 1 and females as 2. Each category of variable and missing information needs a code. A codebook is a document (i.e. one or more pages) describing the coding system and the location of data for variables in a format that computers can use.
When you code data, it is very important to create a well-organized, detailed codebook or make multiple copies of it. If you do not weigh down the details of the coding system or if you misplace the codebook, you have lost the keys of the data and will have to recode the new data over again.
A researcher transfers information from questionnaires, recording sheets, or similar raw data forms into a format for computers in four ways: code sheets, direct entry, optical scan sheets, and CATI. First, she can use graph paper or special grid forms for computers (called transfer or code sheets) by writing code numbers in squares that correspond to a row and column location, then typing it into a computer. Secondly, she can sit at a computer and directly type in the data.
After very careful coding, a researcher checks the accuracy of coding, or
“cleans” the data. A researcher may code a 10 to 15 percent random sample of the data a second time. If no coding errors appear, she proceeds. If she finds errors, she rechecks mail coding.
Researchers verify coding after the data are in a computer in two ways.
Possible code cleaning (or wild code checking) involves checking the categories of all variables for impossible codes. For example, respondent sex is coded I = Male, 2 = Female. Finding a 4 for a case in the field for the sex variable indicates a coding error. A second method, contingency cleaning (or consistency checking), involves cross-classifying two variables and looking for logically impossible combinations. For example, education is cross-classified by occupation. If a respondent is recorded as never having passed the eighth grade and also is recorded as being a legitimate medical doctor, the researcher checks for a coding error.
A researcher can modify data after they are in a computer. She cannot use more refined categories than were used when collecting the original data, but she can combine or group information. For example, she can group ratio-level income data into five ordinal categories. Also, she can combine information from several indicators to create a new variable or add the responses to several questionnaire items into an index score.
3.1.1 Computers and Social Research
What is a Computer?Computers have revolutionized social research and are now a standard tool in social research. Researchers who analyze quantitative data use a computer. Just as people operate certain machines (e.g. telephones, televisions, automobiles), so they can perform specific tasks more efficiently (e.g. talk to someone across the country, watch programs, travel.
Researchers use computers to perform specialized tasks, e.g. organize data, calculate statistics, write reports) much more effectively and efficiently.
This section cannot teach you how to use computers. That requires hands on assistance and instruction tailored to the specific computer system you will be using. Instead, it gives you a general background on computers, some basic terminology, and explains how computers are used in quantitative research.
Early Computers: By today’s standards, the early computers of the 1960s were very large, very expensive, and very slow. They could cost as much as
$1 million, and were the size of a dozen large refrigerators, consumed huge quantities of electricity, had to be kept in special rooms under controlled temperature conditions and were constantly maintained by a team of technicians. Nevertheless, these large computers called mainframe computers were more accurate, handled more information and could precisely perform complex calculations much faster than the older card- sorting or calculating machines combined. In addition, they could “read”
and follow complex instructions called computer programs.
By the 1970s, mainframe computers had become cheaper and much more powerful. Colleges, government agencies and companies still use mainframe computers for analyzing large amounts of data. Modern mainframe computers are extremely powerful and can be used by many people at the same time thorough time-sharing. This means that the computer is so powerful and fast that it can do many different tasks for many people simultaneously. Researchers who use complex statistics that
involves many calculations with dozens of variables and very large data sets (e.g. a million cases) still use mainframes.
3.1.2 How Computers Help the Social Researcher
Computers are a necessity for today’s quantitative social researcher. Social researchers use mainframe or microcomputers for many purposes: to write reports, to organize large amounts of data and to compare statistical measures. Computers help them perform these tasks much faster and with much greater accuracy than is possible by hand. Without the appropriate computer a researcher cannot analyze data from a large-scale research project or calculate complicated statistics. Although a person must invest time in learning how to use computers, the investment saves an enormous amount of time later when it is used. A trained researcher with the proper computer can do in minutes what once took a year to do by hand.
The electronic apparatus (boxes, switches, machines, wires) of the computer is called hardware. This is to distinguish it from software, the electronic messages that computers can read, including computer programs (e.g.
instructions that computers read and follow). A researcher needs both hardware and software to use a computer. Without the correct software, hardware can do nothing. and various kinds of statistics.
3.1.3 Results with one Variable Frequency Distribution
The word statistics has several meanings. Statistics can mean a set of collected numbers (e.g., numbers telling how many people live in a city). It can mean a branch of applied mathematics used to manipulate and summarize the features of numbers. Social researchers use both types of statistics. Here, we focus on the second type – ways to manipulate and summarize numbers that represent data from a research project.
4.0 CONCLUSION
You learned about organizing quantitative data to prepare them for analysis, and analyzing those (organizing data into charts or tables, or summarizing them with statistical measures). Researchers use statistical analysis to test hypotheses and answer research questions.
Beginner researchers sometimes feel they have done something wrong if their results do not support a hypothesis. There is nothing wrong with rejecting a hypothesis. The goal of scientific research is to produce
hypotheses. Hypotheses are theoretical guesses based on limited knowledge;
they need to be tested. Excellent-quality research can find that a hypothesis is wrong, and poor-quality research can support a hypothesis. Good research depends on high quality methodology, not on supporting a specific hypothesis.
5.0 SUMMARY
We have seen how data must first be coded and then analyze using univariate or bivariate statistic. Bivariate relationship might be spurious, so controlled variables and multivariate analysis are often necessary. We have also learnt some basics about the use of computers in social research and about inferential statistics.
Good research means guarding against possible errors or obstacles to true inferences from data to the social world. Errors can enter into the research process and affect results at many places: research design, measurement, data collection, coding, calculating statistics and constructing tables, or interpreting results. Even if a researcher can design, measure, collect, code and calculate without error, another step in the research process remains. It is to interpret the tables, charts and statistics and answer the question:
“What does it all mean?” The only way to assign meaning to facts, charts, tables or statistics is to use theory.
6.0 TUTOR MARKED ASSIGNMENT (TAM)
1. What is a codebook and how is it used in research?2. How do researchers clean data and check their coding?
7.0 REFERENCES/FURTHER READINGS
Achen, Christopher H. (1982); Interpreting and Using Regression; Beverly Hills, CA: Sage.
Andrews, Frank M., et al (1981); A Guide for Selecting Statistical Techniques for Analyzing Social Science Data; Ann Arbor; Institute
of Social Research, University of Michigan.
Blalock, Hubert M. (Jr); (1979); Social Statistics, 2nd ed. New York;
McGraw-Hill.
Zeisel, Hans (1985); Say it with Figures, 6th ed; New York: Harper & Row.