Concepts: Choosing the appropriate statistic, generating a research hypothesis, hypothesis testing, data analysis in SPSS, statistical significance, writing results
Choose one of the data sets provided. See the description of each data set.
Familiarize yourself with the data set. Determine your independent and dependent variables, their scales of measurement, and your null and research hypotheses. You will use this information to justify the ideal analysis and the analysis that you ultimately choose to run.
Describe the ideal analysis. You might come up with ideas for analysis that are beyond what you’ve learned in this class (e.g., ANOVA and multiple regression; you know what these are, but you don’t have the background to run, interpret and report on these analyses).
Decide on a type of analysis you will run (t-test, ANOVA, correlation & regression, or chi-square)
Complete the analyses in SPSS
Go into SPSS and generate appropriate descriptive statistics. For example, frequency distributions for each variable, and measures of central tendency, variability, and correlations among variables, if applicable.
Use SPSS to test the null hypothesis. Include measures of effect size and any post hoc tests as needed, depending on your data and the analyses chosen.
Save the output as <YOURNAMEPROJECT2. SPV> and upload
Determine if you should reject the null hypothesis or not.
Write Up. Submit a 2-3 page (12-font) description of the Analysis including this content:
Provide a rationale for the analysis that you chose.
State the assumptions required for the analysis.
Report the results using APA style (see examples from class lectures). Include descriptive statistics and the hypothesis test.
Briefly discuss if your results are significant or not as well as the size of the treatment effect.
PSYCH 381: Project 2 Rubric
0 Incorrect, or poorly conducted
Accurate determination of independent, and dependent variables
Accurate scales of measurement
Null and Research hypotheses are logically
correct and clearly stated
Rationale for data analysis is correct
Appropriate descriptive statistics are examined
Hypothesis test is done correctly
Effect size is determined (also post hoc tests if applicable) and reported
Statistical assumptions are accurate
Write up is comprehensive, but not repetitive, and adheres to APA style
Write-up is clear and well written