## Exercises:

- RESEARCH_METHODS_1RM - Research Design
- RESEARCH_METHODS_2RM - Sampling
- RESEARCH_METHODS_3RM - Measurement
- RESEARCH_METHODS_4RM - Data Collection (Survey Research)
- RESEARCH_METHODS_5RM - Hypotheses and Hypothesis Testing
- RESEARCH_METHODS_6RM - Introduction to Data Analysis
- RESEARCH_METHODS_7RM - Central Tendency and Dispersion
- RESEARCH_METHODS_8RM - Graphs and Charts
- RESEARCH_METHODS_9RM - Crosstabulation
- RESEARCH_METHODS_10RM - Chi Square
- RESEARCH_METHODS_11RM - Measures of Association
- RESEARCH_METHODS_12RM - Spuriousness
- RESEARCH_METHODS_13RM - Writing Research Reports

Author: Ed Nelson

Department of Sociology M/S SS97

California State University, Fresno

Fresno, CA 93740

Email: ednelson@csufresno.edu

© The Author, 2017

These thirteen exercises were written for an introductory research methods course. The first exercise focuses on the research design which is your plan of action that explains how you will try to answer your research questions. Exercises two through four focus on sampling, measurement, and data collection. The fifth exercise discusses hypotheses and hypothesis testing. The last eight exercises focus on data analysis.

These exercises use one of the Monitoring the Future Surveys (i.e., the 2015 survey of high school seniors in the United States). This data set is part of the collection at the Inter-university Consortium for Political and Social Research at the University of Michigan. The data are freely available to the public and you do not have to be a member of the Consortium to use the data. If you are a student, faculty member or staff at a university or college that belongs to the ICPSR, you will have access to all the archive’s data holdings. If you are not, then you will only have access to public-use data. Fortunately, the Monitoring the Future Surveys were funded for public access so you have access to this study regardless of your status.

We’re going to use SDA (Survey Documentation and Analysis) to analyze the data which is an online statistical package written by the Survey Methods Program at UC Berkeley and is available without cost wherever one has an internet connection. A weight variable is automatically applied to the data set so it better represents the population from which the sample was selected.

The exercises can be downloaded as Word (.docx) files. Included with these exercises is a more detailed set of notes for the instructor and an introduction to SDA for students.

The exercises were written so each exercise is independent of the others and any one exercise can be used even if the other exercises are not used. Because the exercises were written to stand alone there is often duplication across the exercises. If you use several of the exercises together you may want to edit them to remove this duplication or add material of your own.

These exercises are not a comprehensive treatment of the statistical techniques covered. They do not discuss how to compute most of the statistics. You may want to add some of this information to the exercises.

You have permission to use these exercises and to revise them to fit your needs. I would appreciate receiving a copy of your revision so I can see how the exercises are being used. If you find any errors in the exercise, please email me and I will correct them. I would also like to hear from you about your experiences using the exercises. Please contact me for more information.

Each exercise has a set of keywords which are listed below. There is also a spreadsheet showing the methodological and statistical terms covered in each exercise which will help you find appropriate exercises.

The following files can be downloaded:

Keywords for the Exercises

- RESEARCH_METHODS_1RM: research design, research questions, scientific approach, population, sample, non-probability sampling, probability sampling, proportional stratified random sample, disproportional stratified random sample, simple random sample, cluster sample, sampling error, sample size, concept, theoretical definition, operational definition, empirical, data collection, data, observation, questioning, survey research, coverage error, nonresponse error, measurement error, data analysis, univariate analysis, bivariate analysis, multivariate analysis, statistics, causality
- RESEARCH_METHODS_2RM: research design, population, sample, sampling, probability of selection, statistic, parameter, inference, probability sample, non-probability sample, volunteer sample, instant poll, simple random sample, random numbers, random number generator, sampling error, stratified random sample, proportional stratified random sample, disproportional stratified random sample, cluster sample, sampling error, sample size
- RESEARCH_METHODS_3RM: concept, measurement, measure, indicant, reliability, consistency, test-retest, equivalence, validity, face validity, predictive validity, content validity, precision
- RESEARCH_METHODS_4RM: error, sampling error, coverage error, non-response error, measurement error,
- RESEARCH_METHODS_5RM: hypothesis, theory, research question, measure, indicant, variable, hypothesis testing, quantitative data analysis, qualitative data analysis, statistic,
- RESEARCH_METHODS_6RM: univariate analysis, bivariate analysis, multivariate analysis, levels of measurement, nominal measure, ordinal measure, interval measure, ratio measure, research question, research design, sampling, measurement, data collection, central tendency, dispersion, skewness, kurtosis, chart, concept, measure, indicant, variable, mutually exclusive, exhaustive, equal units of measurement, missing value
- RESEARCH_METHODS_7RM: central tendency, mode, median, mean , bar chart, nominal measure, ordinal measure, interval measure, ratio measure, skew, peaks, dispersion, range, standard deviation, variance, coefficient of relative variation
- RESEARCH_METHODS_8RM: chart, pie chart, bar chart, stacked bar chart, line chart
- RESEARCH_METHODS_9RM: crosstabulation, univariate analysis, bivariate analysis, independent variable, dependent variable, column percent, rule for computing percents, rule for interpreting percents, sampling error, multivariate analysis
- RESEARCH_METHODS_10RM: crosstabulation, nominal measure, ordinal measure, chi square, independent variable, dependent variable, column percent, sampling, sampling error, research hypothesis, null hypothesis, degrees of freedom, observed value, expected value
- RESEARCH_METHODS_11RM: measure of association, independent variable, dependent variable, asymmetric measure, symmetric measure, nominal measure, ordinal measure, dichotomy, contingency coefficient, cramer's v, chi square, somer's d, tau-b, tau-c, gamma
- RESEARCH_METHODS_12RM: univariate analysis, bivariate analysis, multivariate analysis, spuriousness, control variable, sampling error, partial table, chi square, measure of association, sampling error, recoding
- RESEARCH_METHODS_13RM: research report, abstract, endnote, footnote, plagiarism