Note: Label the homework numbers and attach all python code under appendix in your word/pdf format homework. 1. For the data given below compute the linear regression parameters by hand: Problem statement: Company M&M has a current product XYZ which is targeted towards the luxury goods market. It has observed product sales as below: (10 pts) Months Sales (in K$, 1K=1000$) 3 100 5 250 7 330 9 590 12 660 15 780 18 890 *Note that the sales amount does not have to be expanded in K scale. Use the numbers directly.

1b. What is the expected product sales for the next year (next 12 months)? What are the inferences (, values) conveyed through this predictive linear regression model? (5 pts)

1c. Company M&M wants to invest in a new product ABC if the current product XYZ has not produced a 1.5 times increase in sales over the next year. As a Data Scientist, would you advise company M&M to invest in a new product ABC or make changes to the current product XYZ? Provide your reasoning based on facts and figures to substantiate your decision-making process. (10 pts)

1d. Write a python program to implement questions 1-3. Provide code documentation and compare results obtained using the linear regression function from sklearn with your own linear regression model as discussed in class). Compare and provide data visualization (scatter plot) and plot the regression line for all cases. (15 pts) *Note only provide data visualization here (1 scatter plot with regression line plot x 2 cases: your linear regression code vs. sklearn linear regression code, 10 pts = 5 pts per plot/case x 2, 5 pts for code = 15 pts )

I want solutions for every part. please help