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Introduction to Quantitative Research Methods

Lab Assignment D

Due date, submission, and instructions

Please submit the assignment in Quercus in one document that contains all assignment parts. Please read the detailed instructions about the expected content and formatting of these lab assignments in the document Lab assignment instructions available on Quercus.

Learning Objectives

In these exercises, you will:

•    Practice how to interpret bivariate regression analysis, including the regression slope, the constant, the correlation coefficient rand the coefficient of determination

Data

You may use either the GSS or the Canadian Community Health Survey for this assignment.

Exercise 1 (20% of mark)

You may find the SPSS DEMONSTRATION 13.2 at the end of Chapter 13 in the section “You Are the Researcher” (p. 447) useful for this section.

Read through the entire directions before you choose variables. Note that you will need to make a causal argument, and one of your interval-ratio variables will be a dependent variable in both analyses. Using either the GSS or Canadian Community Health Survey Dataset, you will select one nominal variable that has more than two categories (non-dichotomous) and two interval-ratio variables.

a)   Use the Descriptives command to get means and standard deviation for two interval ratio variables. Discuss these descriptive findings in a couple of sentences. (Hint: You did something similar back on Lab A). Include the table in your answer.

b)   Use the Frequencies command to get the frequency tables for your nominal variable. Discuss the distribution of the nominal variable and write a couple of sentences about what the distribution means in real-world terms. (Hint: You did something similar back on Lab A). Include the table in your answer.

c)   Transform your nominal variable into a new dichotomous variable, with “0” representing “No” and “1” representing “Yes.” Make sure this new variable has an easy-to-remember name! Then create a two-way frequency table for your old nominal variable and your new nominal variable to make sure the transformation worked; include the table in your answer.

(See next page for Exercises 2 and 3)

Exercise 2 (40% of mark)

Examining Theory: X=Nominal, Y=Interval/Ratio

a)   Generate acausal theory about your nominal variable and your interval/ratio variable. Which one is likely to cause the other, and why? Define x andy. [Note: this should be approximately two sentences; one to explain which one is likely to cause the other, and one to explain why. If you are having trouble coming up with a relatively plausible theory, you may want to select different variables]

b)   Calculate the correlation coefficient. Report the output and interpret the correlation coefficient (one sentence).

c)   Run the OLS regression. Report the output, and interpret the regression coefficient and intercept (one sentence for each)

d)   Interpret R-Squared

e)   Test your theory using all six steps from the video lecture and reading notes. When the regression output gives you what you need, you do not need to calculate it out by hand; simply report what you found from the regression output above.

f)    Based on the tests of statistical significance and measures of effect size (correlation coefficient, regression coefficient, and R-squared), evaluate your theory. Do not write more than 3 or 4 sentences.

Exercise 3 (40% of mark)

Examining Theory: X= Interval/Ratio, Y=Interval/Ratio

a)   Generate a causal theory about your two interval/ratio variables, using the same dependent variable as in the previous section. Which one is likely to cause the other, and why? Define x andy. [Note: this  should be approximately two sentences; one to explain which one is likely to cause the other, and one to explain why. If you are having trouble coming up with a relatively plausible theory, you may want to select different variables.]

b)   Calculate the correlation coefficient. Report the output and interpret the correlation coefficient (one sentence).

c)   Run the OLS regression. Report the output, and interpret the regression coefficient and intercept (one sentence for each)

d)   Interpret R-Squared

e)   Test your theory using all six steps from the video lecture and reading notes. When the regression output gives you what you need, you do not need to calculate it out by hand; simply report what you found from the regression output above.

f)    Based on the tests of statistical significance and measures of effect size (correlation coefficient, regression coefficient, and R-squared), evaluate your theory. Do not write more than 3 or 4 sentences.