pleass answer the question correctly ot just copy and paste from somewhere else, its different

The Fresh Detergent Case Enterprise Industries produces Fresh, a brand of liquid detergent. In order to more effectively manage its inventory, the company would like to better predict demand for Fresh. To develop a prediction model, the company has gathered data concerning demand for Fresh over the last 33 sales periods. Each sales period is defined as one month. The variables are as follows: Period -Time period Demand - Y = demand for a large size bottle of Fresh (in 100,000) Price - the price of Fresh as offered by Ent. Industries AIP = the average industry price ADV = Ent. Industries Advertising Expenditure in $100,000) to Promote Fresh in the sales period. DIFF - AIP - Price = the "price difference" in the sales period 1- Find the monthly seasonal indices for the demand values using Simple Average (SA) method. Find the de-seasonalized demand values by dividing monthly demand by seasonal indices 2. Use regression to perform trend analysis on the de-seasonalized demand values. Is trend analysis suitable for this data? Find MAD and explain the Excel Regression output (trend equation, T, T-squared, goodness of model). 3. Find the seasonally adjusted trend forecasts for August through October 2021. 4- Perform simple linear regression analysis with ADV as the independent variable to predict demand. Write the complete equation, find MAD and explain the Excel Regression output. Make sure to use the de-seasonalized demand data for this model and all future models. 5- Repeat part (10) with DIFF as the independent variable. 6- Construct four variable regression model with Period, AIP, DIFF, and ADV as independent variables. Write the equation, find MSE, and explain the output. Rank variables based on their degree of contribution to the model. Observe significant F, R-squared, and p-values and explain 7- Perform multiple linear regression analysis with Period, DIFF, and ADV as independent variables. Write the equation and find MAD Which variable is the most significant predictor of demand? Rank the independent variables based on their degree of contribution to the model. Observe significant F, R-squared, and p-values and explain. 7- Perform multiple linear regression analysis with Period, DIFF, and ADV as independent variables. Write the equation and find MAD. Which variable is the most significant predictor of demand? Rank the independent variables based on their degree of contribution to the model. Observe significant F, R-squared, and p-values and explain. 8- Use the model obtained in parts 13 and make forecasts for the following months. Make sure to seasonalize final forecasts. Period Aug. Sep Oct. 2021 2021 2021 Price $7.30 $7.45 $7.50 AIP $7.65 $7.90 $7.95 ADV $11.7 $11.9 $12.3 8- Provide a paragraph of conclusion of your analysis. 9. Submission must include a Word File and Excel file of analysis. All team members must work on all parts of the project individually and compare results for accuracy and team leader will upload files. fx C E H Summer II - 2021 Month/Yr. Nov. 2018 ADV 5.3 6.7 Jan. 2019 DIFF -0.3 0.2 0.6 0 0.3 0.2 0.2 -0.4 -0.7 -0.2 0.2 0.1 0.4 0.5 Jan. 2020 PERIOD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 0.3 PRICE 6.1 5.8 5.7 5.7 5.6 5.6 5.6 6.3 6.4 6.2 5.9 5.9 5.7 5.7 5.8 5.8 5.7 5.8 5.7 5.8 5.8 5.9 5.7 5.7 5.6 5.7 5.7 5.9 5.8 5.3 5.4 5.7 5.9 AIP 5.8 6 6.3 5.7 5.9 5.8 5.8 5.9 5.7 6 6.1 6 6.1 6.2 6.1 6.1 6.2 6.3 6.1 5.7 5.8 5.6 5.9 5.6 6.1 6.4 5.6 5.8 5.8 6.2 6.3 6.4 6.5 DEMAND 9.4 10.3 115 11.1 11 10.5 10.2 8.9 8.3 8.2 8.8 9.8 10.1 11.3 12.5 12.4 12.1 11.8 11.5 11 10.2 10.3 10.9 11.2 7.2 7.3 7.2 6.5 6.7 6.8 5.8 5.5 6.5 6.2 7 6.9 6.8 6.8 7.1 7 6.8 6.5 8.1 7.7 7.3 7.5 8.1 8.3 8.7 9.2 9.4 9.8 10.1 10.3 10.8 0.3 0.5 0.5 0.4 -0.1 0 -0.3 0.2 -0.1 0.5 0.7 -0.1 -0.1 0 0.9 0.9 0.7 0.6 125 Jan. 2021 13.4 14.7 14.1 14 135 13.5 13.1 12.5 Jul-21 Aug-21 Sep. 21 Oct-21