Guidelines for project.

Perform an independent-sample t test for your Final Project. These Study Notes contain two items:

1. A sample APA-style table for reporting t test results. Note that while the measure of effect included here is η ² , you could choose to report d instead. Further, the table could be adapted for results reporting a related-samples t test. Typically, you will use a table only when it is more concise than using text. Thus, the table below reports results for a series of t tests. You are not required to include such a table in your Final Project as you are conducting only one analysis.

A sample write-up for what is required for the Final Project. Note that this write-up uses variables not included in the data set and serves only as an example. Also note that you need not follow this format word for word; in fact, you are encouraged not to do so. There are many ways to report results in a scientific, APA-appropriate style.

SAMPLE TABLE

Table X

Results of t -Tests Comparing Younger and Older Adults

Variable df t η ² p

Hours worked each week 48 3.98 .45 <.001

# of Child Care Activities 49 3.72 .20 <.001

Satisfaction with Life 49 -2.92 .27 .005

SAMPLE WRITE-UP FOR FINAL PROJECT

The research question examined was: "Is there a difference in life satisfaction between young and older adults?" The hypotheses tested were:

H ₀ : µ _young = µ _older

H ₁ : µ _young ≠ µ _older

The statistical assumptions for the independent-samples t -test include the following: (a) each data point in the sample is independent, (b) the data in each of the two populations are normally distributed, and (c) the two populations have equal variances. The results of the test were statistically significant, t (48) = -2.92, p = .005. Thus the null hypothesis is rejected; there is a difference in life satisfaction scores between the groups. Older adults ( M = 4.52, SD = 1.53) reported greater life satisfaction than young adults ( M = 3.32, SD = 1.38). (Note: for a measure of effect size, you can choose d, or η ² . An example of each is given below. Do not report both, as this would be redundant information. Note also that SPSS does not "give" you a measure of effect size. The formulas may be found on page 169 in the course text, Using SPSS for Windows and Macintosh ). The measure of effect size, as indexed by η ² was .15, indicating a large effect; 15% of the variance in life satisfaction scores was accounted for by age group. The measure of effect size, as indexed by d , was .82, thus indicating a large effect between age groups and life satisfaction scores. The 95% confidence interval for the difference in means was .37 to 2.03 points. Thus, the results of the test found that older and young adults differed significantly on life satisfaction scores and that difference between the groups was large, with older adults reporting more life satisfaction than young adults.

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