1305AFE: Business Data Analysis- Computer Assignment- Business Assignment Help

Internal Code: 1GICE

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Task: Many college instructors believe that students need to spend at least 2 hours studying outside of class for every hour of lecture. They believe that the number of hours students study to prepare for the exam affect students’ marks significantly. As opposed, some believe that the number of preparation hours do not essentially affect students’ marks while some other factors are to be considered. 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 below 11 questions: 1. What type of survey method is used and why? 2. What sampling method could be used to select the sample and why? 3. What are the variables we 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? 5. Using intervals such as 0–11, 12–23, 24–35, ... for the preparation time variable and class intervals 0–12, 13–25, 26–38, ... for marks and  explaining how to decide on the number of classes, use appropriate BIN values to 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. 10. Estimate a simple linear regression model and present the estimated linear equation. Then, interpret the coefficient estimates of the linear model. 11. Interpret the coefficient of determination, R-squared (R2) value.