Individual ReportEnterprise Industries produces Fresh, a brand of liquid laundry detergent. In order to manageits inventory more effectively and make revenue projections, the company would like tobetter predict demand for Fresh. To develop a prediction model, the company has gathereddata concerning demand for Fresh over the last 30 sales periods (each sales period is definedto be one month). Here, for each sales period,• y = the demand for the large size bottle of Fresh (in hundreds of thousands of bottles)in the sales period• x1 = the price (in dollars) of Fresh as offered by Enterprise Industries in the sales period• x2 = the average industry price (in dollars) of competitors’ similar detergents in thesales period• x3 = Enterprise Industries’ advertising expenditure (in hundreds of thousands of dollars)to promote Fresh in the sales period1. Please generate the descriptive statistics monthly average and monthly standarddeviation for y, x1, x2 and x3 based on the data provided.2. Please analyze the correlation between y and x1, the correlation between y and x2,and the correlation between y and x3 based on the data provided. Draw threeappropriate graphs in excel to show the relationship between two.3. Assuming Fresh predicts the average future monthly demand for the large size bottleof Fresh is 9 (hundreds of thousands of bottles) based on the data provided, examinewhether his prediction is accurate. Please use the hypothesis testing I to conduct theexamination by following steps below.(a)State the null (Ho) and alternative (Ha) hypotheses. Explain briefly what they mean.(b)Does it involve a one-tailed test or a two-tailed test? Why do you say that?(c)What is your calculated t-score? What is the critical t-score?(d)Assess the calculated and critical t-scores (as sentences in a paragraph): based ontheir values, will you keep the Ho or reject it and go for Ha?(e)Interpret: what does your chosen hypothesis says (the findings)?4. To help Enterprise Industry predict a more accurate future monthly demand for itsFresh product, please construct six following linear regression models(please reportits 𝑅2, 𝑎𝑑𝑗𝑢𝑠𝑡𝑒𝑑 𝑅2, and coefficients of 𝑏0, 𝑏1, 𝑏2, 𝑏3)𝑀𝑜𝑑𝑒𝑙 1 ∶ 𝑦 = 𝑏0 + 𝑏1𝑋1𝑀𝑜𝑑𝑒𝑙 2 ∶ 𝑦 = 𝑏0 + 𝑏2𝑋2𝑀𝑜𝑑𝑒𝑙 3 ∶ 𝑦 = 𝑏0 + 𝑏3𝑋3𝑀𝑜𝑑𝑒𝑙 4 ∶ 𝑦 = 𝑏0 + 𝑏1𝑋1 + 𝑏2𝑋2𝑀𝑜𝑑𝑒𝑙 5 ∶ 𝑦 = 𝑏0 + 𝑏1𝑋1 + 𝑏3𝑋3𝑀𝑜𝑑𝑒𝑙 6 ∶ 𝑦 = 𝑏0 + 𝑏1𝑋1 + 𝑏2𝑋2 + 𝑏3𝑋3Compare those 6 models and comment which model gives a better prediction ofdemand for Fresh.

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