Business Data Analysis Computer Assignment -
PART 1 -
Economists believe that high rates of unemployment are linked to decreased life satisfaction ratings. To investigate this relationship, a researcher plans to survey a sample of families in Queensland. Answer the following questions:
1. What type of survey method the researcher could use and why?
2. What sampling method could be used to select the sample and why?
3. What are the variables the researcher should consider collecting data for the purpose of the analysis and why? Identify the data type(s) for the variables.
4. What kind of issues we may face in this data collection?
PART 2 -
To study the relationship between the preparation time spent by each student (in hours) for the exam and the reported mark, a sample of 100 students were selected randomly from a large statistics class. The data are stored in the file named "ASSIGNMENTDATA.XLS" in the course website. Using EXCEL, answer the following questions:
5. Using the appropriate BIN values, draw a histogram for each variable. Then, comment on the shape of the two distributions.
6. Use an appropriate plot to investigate the relationship between the two variables. Briefly explain the selection of each variable on the X and Y axes and why?
7. Prepare a numerical summary report about the data on the two variables by including the summary measures, mean, median, range, variance, standard deviation, smallest and largest values and the three quartiles, for each variable.
8. Compute a numerical summary measure to measure the strength of the linear relationship between the two variables. Interpret this value.
9. Construct a 90% confidence interval estimate for the population average time spent on preparation. Interpret the interval (use the spreadsheet on the course website).
10. Test the hypothesis that population average time spent on preparation is more than 65 hours using a 5% level of significance (use the spreadsheet on the course website).
11. Estimate a simple linear regression model and present the estimated linear equation. Then, interpret the coefficient estimates of the linear model.
12. Interpret the coefficient of determination, R-squared (R^{2}) value.
Attachment:- Assignment Files.rar