Psy 2020 Experimental I: Applied Statistics Lab 4: t-tests Dr. Obrecht Lindemann Overview The datafile contains data from two different studies. Each study's data should be analyzed using one of the t-tests. First you'll need to determine which t-test to use, and then analyze the data and explain what you found. Study descriptions Dataset 1: College students stated whether they were male or female, and reported the number of speeding tickets they received in the past year. (Hint: students are in either the male group or the female group; this tells you whether the variable sex is between or within subjects) Dataset 2: Participants with a Bachelor's degree reported their annual income. The mean income of adults in the United States overall is = $41,027. Dataset 1: Sex and speeding tickets 1) Which t-test should be used to analyze whether sex predicts number of speeding tickets? (single sample, repeated measures/within subjects, or independent samples/between subjects) 2) State the independent variable (IV). 3) State the dependent variable (DV). 4) State the Null hypothesis (H0): 5) Run your t-test (see the SPSS guide at the bottom of the document for instructions). How many speeding tickets did males and females get on average? a. ???? ???????????????????? = b. ???? ???????????????????????????? = 6) Next, type your results in APA format (t(df)=x.xx, p=.xx, d=.xx): (Note, use the "Two-sided p" for your p-value in the Equal variances assumed row)

7) Explain what your results mean. If you reject the null, be sure to include the direction of the result, i.e., explain which sex generally speeds more. Mention whether you have a small, medium, or large effect size (d .2 or -.2 small; d .5 or -.5 medium; d .8 or -.8 large). 8) Finally, use Excel to make a graph of your two group means (See instructions at the bottom of this document, and/or my lab tutorial). Dataset 2: Income with a Bachelor's degree 1) Which t-test should be used to analyze whether people with a Bachelor's degree earn a different amount of money compared to the general population ( = $41,027)? (single sample, repeated measures/within subjects, or independent samples/between subjects) 2) State the independent variable (IV). 3) State the dependent variable (DV). 4) State the Null hypothesis (H0): 5) Run your t-test. Run your t-test (see the SPSS guide at the bottom of the document for instructions). How much money does a person with a Bachelor's degree make on average? a. ???? ???????????????????????? ???????????? ???????????????????????????????? = 6) Next, type your results in APA format (t(df)=x.xx, p=.xx, d=.xx): (Note, use the "Two-sided p" for your p-value in the Equal variances assumed row) 7) Explain what your results mean. If you reject the null, be sure to include the direction of the result. Mention whether you have a small, medium, or large effect size (d .2 or -.2 small; d .5 or -.5 medium; d .8 or -.8 large). SPSS guide for t-tests Single sample t-test: -AnalyzeCompare Means and ProportionsOne-Sample t-test -DV goes in the Test Variable box -Type into the Test Value box and hit OK. Repeated measures/paired-sample/within Ss t-test: -Data from a given S are given across a single row -AnalyzeCompare Means and Proportions Paired Samples t-test -Select and click the arrow button to move both levels of the IV over into the paired variables box; hit OK

Independent samples/between Ss t-test: -Levels of the IV are coded in a single column -AnalyzeCompare Means and Proportions Independent Samples t-test -The IV (the nominal variable) is the "grouping variable"; after putting it in you must define the groups (enter in the two values that correspond to the two groups listed in the data sheet, e.g. 1 and 2) -Make sure Estimate effect sizes is checked and hit OK Graph Guide in Excel Open Excel. Type in your group means and label them; see example: Men Women 3.5 3.2 (Note: you probably won't type in Men and Women, but use the labels that make sense for your variable.) Highlight all four cells (the two means with their labels), and click the Insert tab. Click on the picture of the bar graph (2D column, clustered column). Then customize your graph (update your chart title, remove background lines, add X and Y axes labels). When you click on your graph you'll see a + sign; this lets you add axis labels and more.