The scenario here is to related to “satisfaction” is one of the common quality measures for all types of organizations. While many organizations focus on patient/customer satisfaction (another component of quality measurement), we are using employee job satisfaction for this course project based on the standardized Minnesota Satisfaction Questionnaire. Any dataset will undergo similar processes of data analysis, evaluation, and application in decision making recommendations. In other words, you are completing a mini-Chapter 4 Quantitative Survey Data Analysis here.
Part 1. Compare 2015-16 Satisfaction ratings using descriptive statistics (table summary) and create a bar chart (figure) comparing the mean values for each. Write a short paragraph explaining the data. Write the corresponding RQ and Ho/Ha related to satisfaction.
Part 2. Complete an inferential statistic using a paired-comparison t test statistical test comparing 2015-16 mean values for each participant. Report the findings in a standard table (t and P values are required). Based on the P value, which hypothesis from Part 1 is supported/rejected and why. Explain your findings and conclusions in a short paragraph.
Part 3. Complete an inferential statistic using a Pearson correlation statistical test for relationship between satisfaction ratings in 2015 and 2016 for all participants in each year. Complete a scatterplot (figure) and report the findings in a standard table (r and P values are required at a minimum). Write an RQ related to the relationship with corresponding Ho/Ha. Based on the r and P values, discuss which hypothesis is supported/rejected and why. Explain your findings and conclusions in a short paragraph.
Part 4. Complete a predictive statistic (linear regression) for satisfaction ratings 2015 and 2016. Report the statistics using the standard Y = mx + b formula. Write an RQ related to the ability to predict future satisfaction based on 2015 and 16 data with corresponding Ho/Ha. Based on the P value, discuss which hypothesis is supported/rejected and why. Explain your findings and conclusions in a short paragraph. Predict what the satisfaction rating would be for 2017. Explain how accurate the prediction for 2017 satisfaction is.
Part 5. Split the data into 3 groups for each year (2015 and 16). Group 1 = participants 1-10; Group 2 = participants 11-20; Group 3 = participants 21-30. Write an Research Question related to finding differences between all 3 groups and years 15-16 with corresponding Ho/Ha related to differences in group satisfaction by year. Create a bar chart (figure) comparing the mean values for each group and year. Complete an ANOVA statistical test comparing groups and years. Report the findings in a standard table (P values are required). Based on the P value, which hypothesis is supported/rejected and why. Explain your findings and conclusions in a short paragraph.
The final project should be between 5-10 pages double spaced. 4 tables and 3 figures (minimum) are required.
*Regression (predictive formula hint)!

Use 2015 data and 2016 data as the 2 columns to generate the predictive formula. Your resultant formula should then be statistically significant (P <.01) Prediction formula Y = .94x -.20881 .94(x = any satisfaction value 0-5) -.20881 = the predicted satisfaction for 2017 .94 is the x variable beta coefficient. -.20881 is the Y intercept (constant)

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