Final Examination

The following information should assist you with your preparations for the final examination for the course. The final examination will be a “take-home” style test, meaning that you will have access to the exam on Monday, November 16, 2020 at 12:00am ET and the last day to upload your responses will be Friday, November 20, 2020 at 4:00pm ET. Please note that this document is simply a guide, and exam questions may touch on material that was covered during the semester but not indicated on this guide.

Topics and Areas of Study for the Examination:

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· Conceptualization of variables

· Operationalization of variables

· Units of analysis

· The differences between (advantages and disadvantages) probability and nonprobability sampling.

· The key elements of probability sampling.

· The differences between samples and populations and what these differences mean for sampling design and data analysis

· Details about the design and construction of survey questionnaires (scales, indexes)

· Strengths and weaknesses of survey research and the advantages and disadvantages of various survey techniques

· Differences between independent and dependent variables

· Steps for developing a proposal, as outlined by Babbie

· The differences between qualitative and quantitative data

· Types of sampling designs

· How to construct research questions, hypotheses and null hypotheses

· The role of research literature on variable definitions and variable selection

· Levels of measurement

· Descriptive statistics (mean, mode, median) and variability (range, standard deviation, and variance)

· Understanding the conditions and assumptions for when and why we would use the Pearson product-moment correlation coefficient. Also, how to interpret the SPSS output for Pearson’s r.

· The differences between tests of significance, Type I, and Type II errors

· Understand the conditions and assumptions for when to use a one-sample z test. Also, how to interpret the SPSS output.

· Understand the conditions and assumptions for when to use t-test for independent groups and related groups. Also, how to interpret the SPSS output.

· Understand the conditions and assumptions for when to use a simple ANOVA (also known as an F test). Also, how to interpret the SPSS output.

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