Data Analysis Assignment.
The first set of questions is short essay. Please write your answers out in complete sentences (paragraph format).
1. What is covariation? How does it differ from correlation?
2. What is the purpose of a simple one-way tabulation? Three uses of a one-way tabulation come to mind – list two of them.
3. Give the definition of ANOVA in your own words and why/when would you want to use ANOVA in research? How does it differ from a t-test?
4. Explain regression analysis in your own words and describe when you would want to use it. What is the difference between simple regression and multiple regression?
The rest of the questions require the analysis of the Santa Fe Data set within SPSS.
5. Santa Fe Grill owners believe one of their competitive advantages is that the restaurant is a fun place to eat. Run a bivariate correlation analysis between X13 - Fun place to eat and X22 - Satisfaction to test this hypothesis. Report the Pearson Correlation statistic and test it for significance at the .01 level . Do you accept or reject the null hypothesis – fun place to eat does not affect satisfaction? What is your interpretation of this statistical finding?
6. Run a one-way ANOVA to test if there is a difference in means for frequency of eating at the restaurant (X25) among customer groups based on the number of children living in their homes (X33). Report the F statistic and test it for significance at the .05 level. Do you accept or reject the null hypothesis – there is no difference among customer groups with regards to number of children in the homes when it comes to how frequent these customers eat at the restaurant? What is your interpretation of the ANOVA results? Run the post hoc Sheffe Test to assess the group differences. What is your interpretation of Sheffe Test results?
7. Test the following 5 independent variables (X12 – friendly employees, X13 – fun place to eat, X14 – large size portions, X15 – fresh food, and X20 – proper food temperature) using a linear regression analysis to gain more insight into their influences upon X24 – likely to recommend the restaurant. Report the adjusted R square value. Discuss the adjusted R Square value with regards to explained and unexplained variances in the model. What is the F statistic and is the model statistically significant at the .05 level? Which of the 5 predictors has the most influence upon X24 - likely to recommend? Which of the 5 predictors has the least influence upon X24 - likely to recommend?