Business Analytics
Business Analytics
3rd Edition
ISBN: 9780135231715
Author: Evans
Publisher: PEARSON
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Chapter A1, Problem 1PE

Develop a spreadsheet for computing the demand for any values of the input variables in the linear demand and nonlinear demand prediction models in Examples 1 .7 and 1 .8 in the chapter.

Expert Solution & Answer
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To determine

To develop a spreadsheet for computing the demand for any values if the input variables in the linear demand and nonlinear demand prediction models.

Explanation of Solution

Given:

Linear model is,

  D=a-bP,WhereD-Demanda-Constantb-SlopeP-Price

And Nonlinear model,

  D=cP-dWhereD-Demandc-Demandwhenpriceis0P-Price

Following is the formulae used in spreadsheet for linear model:

  Business Analytics, Chapter A1, Problem 1PE , additional homework tip  1

Following is the formulae used in spreadsheet for Nonlinear model:

  Business Analytics, Chapter A1, Problem 1PE , additional homework tip  2

Following is the output for linear model:

  Business Analytics, Chapter A1, Problem 1PE , additional homework tip  3

As per calculation, if the price increases then demand decreases.

Following is the output for Nonlinear model:

  Business Analytics, Chapter A1, Problem 1PE , additional homework tip  4

As per calculation, if the price increases then demand decreases.

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QUESTION 2 (CLO3) Consider a linear demand model to explain the quantity demanded for a product: Q = a+ B, Price+ B, Income+ B, Advert+ s where Q = quantity sold, Price = price of the product, Income = purchaser's income, Advert = advertising. The following data was collected in year 2018. The company spends millions of money in advertisements. The company wants to know how advertisement as well how other factors affect the quantity of units sold. The results are as follows: 中 Model Summary R 0.986 R? 0.973 Standard error of estimate 6.9872 Variables Coefficient Std error Sig Constant 205.862 19.354 0.000 Price -12.242 1.407 0.000 Income 1.414 0.422 0.015 Advert -3.344 1.798 0.112 Interpret and write a report based on the results obtained above.
The Capital Asset Price Model (CAPM) is a financial model that attempts to predict the rate of return on a financial instrument, such as a common stock, in such a way that it is linearly related to the rate of return on the overal market. Specifically, RStockAiBo + BR Markets + e You are to study the relationship between the two variables and estimate the above model: R StockAi-rate of return on Stock A for month i, i = 1,2,---, 59. RMarket-market rate of return for month i, i=1,2,..., 59. B₁ represent's the stocks 'beta' value, or its systematic risk. It measure's the stocks volatility related to the market volatility. Bo represents the risk-free interest rate. The data in the .csv file contains the data on the rate of return of a large energy company which will be referred to as Acme Oil and Gas and the corresponding rate of return on the Toronto Composite Index (TSE) for 59 randomly selected months. Therefore Re, represents the monthly rate of return for a common share of Acme Oil…
Consider a linear demand model to explain the quantity demanded for a product:               where Q = quantity sold, Price = price of the product, Income = purchaser’s income, Advert = advertising. The following data was collected in year 2018. The company spends millions of money in advertisements. The company wants to know how advertisementas well how other factors affect the quantity of units sold.   The results are as follows:                                                      Model Summary R 0.986 R2 0.973 Standard error of estimate 6.9872 Variables Coefficient Std error Sig Constant 205.862 19.354 0.000 Price -12.242 1.407 0.000 Income 1.414 0.422 0.015 Advert -3.344 1.798 0.112           Interpret and write a report based on the results obtained above.
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