Statistics homework help
To test the importance of these factors, Dr. Beeper administers a set of questionnaires to 100 randomly selected firsttime, fulltime freshmen college students (50 male and 50 female) that attended the Freshmen Orientation in the Fall of 2016, at Newton Young University (NYU) in Nebraska.
Measures:
Institutional Commitment (IC) represents the importance that students place on graduating from the college they are currently attending. Institutional Commitment was measured with fiveitem questionnaire. Each item was rated on a 0, 1, or 2 scale. The possible range of scale scores are zero to 10, where values close to zero indicate little to no importance, and values close to 10 indicate high importance.
Goal Commitment (GC) represents the importance that students place on obtaining a college degree. Goal Commitment was also measured with fiveitem questionnaire. Each item was rated on a 0, 1, or 2 scale. The possible range of scale scores are zero to 10; where values close to zero indicated little to no importance to obtaining a college degree, and values close to 10 indicated a high importance to graduating from college.
Academic Aptitude was represented as scores on both the SATMath and the SATVerbal tests. SAT scores for all participants were obtained from high school transcripts.
Hours works, represents the anticipated number of hours the student expected to work throughout the semester.
Finally, Yeartoyear persistence was determined by examining the enrollment records for the sample of 100 students. A student that was registered for registered for the Fall 2017 classes was classified as a “Persister”, and given a code of 1, a student that did not reenroll for classes at NYU, or any other college/university (based on followup phone interviews) was considered a “Nonpersister”, and was given a code of 0. Therefore, the SPSS variable Persist has two levels, 0 and 1.
The assignment is, using the attached SPSS data file, conduct a binary logistical regression analysis in which IC, GC, SATMath, SATVerbal, and Hours Worked are the predictor. variables (covariates in SPSS), and the variable Persist is the outcome (DV in SPSS). Use my sample summary as a model for your summary.
The specific elements of the assignment are:
1) Create a Null and Alternative Hypotheses for the Logistical Regression Analysis
2) State the Goals of the analysis
3) Summarize the results and interpret findings the overall model (for example the Chi Square results, Nagelkerke RSquare or Cox Snell RSquare).
4) Summarize and interpret the results for each predictor; and present, summarize and interpret the results for each significant predictor (i.e., B, Wald’s test, df, p and OR (ExpB). Interpret the significant OR using the effect size conventions I posted in last week’s (8) discussion board.
5) Include and refer to the appropriate tables within the summary.
Please read my sample summary see what statistics to report, and how to report and interpret them in correct APA style, as well as the tables to include.
You’ll see that in my sample summary I also include ttests. You may want to conduct ttests that compare “persisters” and nonpersisters, on the predictor variables (covariates). Please note that the ttest are optional, and will have no impact on your grade whether you include them or not. The ttest are very informative about the bivariate relationship between the predictor variables (covariates in SPSS) and the binomial outcome (DV in SPSS) .
Please note that you are not required to conduct the ttests, or to compute and report Cohen’s d.
Here’s the syntax for my sample summary.
TTEST GROUPS=BO(0 1)
/MISSING=ANALYSIS
/VARIABLES=teachsat ressat wkoverld
/CRITERIA=CI(.95).
LOGISTIC REGRESSION VARIABLES BO
/METHOD=ENTER teachsat ressat wkoverld
/PRINT=GOODFIT CI(95)
/CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5).

Week5CollegePersistence.sav

APASummaryforLogisticalRegression_2_pratice5.pdf