Assignment Data

Demonstrate your ability to perform statistical analysis of a data set. You will locate your own data set; a great source of data is available at Kaggle (https://www.kaggle.com/)

Your data must contribute to addressing the research objective/questions and cover the following:

• At least two continuous variables for analysis.
• At least two grouping variables, each with two distinct categories.

Assignment Questions

Make sure the following questions are covered in the data analysis:

1. Create a graphical analysis for numerical and categorical variables. Also, Comment on the key findings. (10 marks)
2. For statistical analysis involving hypothesis test for two samples t-test: Formulate the null and alternative hypotheses. State your statistical decision using the significant value () of 5%. (10 marks)
3. Evaluate the performance of simple linear Regression analysis based on the two numerical variables. You describe and explain your process for variable selection. Your choices are justified by Regression data analysis. (10 marks)
4. Check the model assumptions for the simple linear regression model and common violations. (10 marks)
5. Evaluate the performance of Multiple linear Regression analysis based on the three numerical variables. You describe and explain your process for variable selection. Your choices are justified by Regression data analysis. (10 marks)
6. Check the model assumptions for the multiple linear regression model and common violations. (10 marks)
7. Evaluate the performance of the simple linear regression (Model 1) and the multiple linear regression (Model 2). Check which model (Model 1 or Model 2) seems to fit better. (10 marks)
8. At the 0.05 level of significance, determine whether the independent variable makes a significant contribution to the simple linear regression model 1. (10 marks)
9. At the 0.05 level of significance, determine whether the independent variables make a significant contribution to the multiple linear regression model 2. (10 marks)
10. State your conclusion in context. (10 marks)