Problem Set 2: Pearson’s correlation (7 pts) Research Scenario: Is there a positive relationship between grit and GPA in high school seniors? A researcher examined this issue by having students beginning their senior year of high school complete a grit inventory using a Likertbased scale (range 1 – 7), where higher numbers indicate more “grit”. GPA was selfreported (scale 0 – 4.0). Enter the data shown here into SPSS to assess whether there is a positive relationship between grit and GPA.

Problem Set 3: OneWay Randomized ANOVA (7 pts) The following are data from a hypothetical study of eating patterns among people in different occupations. Bus drivers, school teachers, and administrators completed an eating pattern survey. The following data is each participant’s mean Junk Food score, with higher numbers indicating more consumption of junk food (interval scale of measurement). Select the appropriate statistical analysis to answer whether there is a difference among these three groups in terms of eating patterns.

Problem Set 4: OneWay Repeated Measures ANOVA (7 pts) Research Scenario: A savvy business owner wanted to assess whether the type of fragrance influenced the amount of money spent. He tried peppermint, lavender, male cologne, and a floral perfume in his four stores. Amount of money spent (in hundreds) is reported for each type of fragrance. Conduct a oneway repeated measures ANOVA to determine whether fragrance influences total amount of money spent.

Part 3 – CUMULATIVE can include theoretical, handcalculations, and use of SPSS over any concepts covered thus far. 
No Cumulative Portion this week – this will start next week and can be over any concepts covered thus far.
DONE!Submit this assignment by 11:59 p.m. (ET) on Sunday of Module/Week 1. 
SOLUTION 2: NULL HYPOTHESIS H0:
ALTERNATIVE HYPOTHESIS Ha:
LEVEL OF SIGNIFICANCE=0.05
Correlation coefficient= 0.523
P value=0.028
Since P value SMALLER than the 0.05 there is significant positive correlation between GRIT and GPA.
Coefficient of determintion R squarred= (0.523)^2= 0.2735
Interpretation: R2= 0.2735 indicates that the model explains 27.35% of the variability of the response data around its mean.
NOTE: AS PER Q&A GUIDELINES I HAVE DONE THE FIRST PLEASE REPOST THE REST. THANK YOU.
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