GSU is trying to predict how price of books predict the quantity of books sold over the semesters. Perform a liner regression analysis, and and find the best model to predict quantity of books to stock in the book store. Make recommendation at setting the prices and quantity at their optimum values for maximizing quantity of books sold. Be prepared to discuss your analysis. Quantity Price 180 475 590 400 430 450 250 550 275 575 720 375 660 375 490 450 700 400 210 500

GSU is trying to predict how price of books predict the quantity of books sold over the semesters. Perform a liner regression analysis, and and find the best model to predict quantity of books to stock in the book store. Make recommendation at setting the prices and quantity at their optimum values for maximizing quantity of books sold. Be prepared to discuss your analysis. Quantity Price 180 475 590 400 430 450 250 550 275 575 720 375 660 375 490 450 700 400 210 500

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter4: Estimating Demand

Section: Chapter Questions

Problem 5E

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Sally Sells Sea Shells by the Sea Shore and collects all sales dataNow she is curious to find out what the elasticity of demand is for her shells Assume they are all the same type and quantity She scatter plots the data and finds there is a linear relationship that looks ripe for a regression estimation of the price response function for her shells The slope of her regression line is 61. Currently, her average daily price is 11.74 and she sells 95 quantity at that priceCalculate the point elasticity of demand for her sea shells
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Given the following data X (consumers of teff) or popn 3 6 8 1 13 13 14 Y ( teff consumption) 8 6 10 12 12 14 20 year 2013 2014 2015 2016 2017 2018 2019 Estimate the regression equation, Y= a+bX, Where Y denotes demand for teff while X is consumers of teff (population) By assuming demand for teff is only affected by its consumers, find the amount demand for teff in the year 2022 if the populations (consumers of teff) are about 18 people? (Hint: use the least square method, parameter a and b can be estimated by solving the two linear equations) SY= na+ bSX SXY=aSX +b Where n is number of years. For example, Estimate the sales for 2012, 2015 and fit a linear regression equation and draw a trend line.ar X Sales (Y) XY X2 year X Sales (Y) XY X2 2002 1 22734 22734 1 2003 2 24731 49462 4 2004 3 31489 94467 9 2005 4 44685 178740 16 2006 5 55319…
1. An analyst from your firm used a linear demand specification to estimate the demand for its product and sent you a hard copy of the results: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept Price of X Income 0.38 0.14 0.13 20.77 150 df 2 147 149 SS 58.87 -1.64 1.11 10398.87 63408.62 73807.49 Coefficients Standard Error 15.33 0.85 0.24 MS 5199.43 431.35 t Stat 3.84 -1.93 4.63 F 12.05 P-value 0.00 0.06 0.00 Significance F 0 Lower 95% 28.59 -3.31 0.63 Upper 95% b. Which regression coefficients are statistically significant at the 5 percent level? a. Based on these estimates, write an equation that summarizes the demand for the firm's product. 89.15 0.04 1.56 C. When price is $10, what is the income elasticity for this product for an income level of 35?
A company sets different prices for a particular DVD system in eight different regions of the country. The accompanying table shows the numbers of units sold and the corresponding prices (in dollars). Sales 420 380 350 400 440 380 450 420 Price 104 195 148 204 96 256 141 109a. Graph these data, and estimate the linear regression of sales on price. b. What effect would you expect a $50 increase in price to have on sales?
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5.2 42 The following regression shows the impact of the number of rooms (ROOM) on the monthly rent of an apartment (in thousand Rands) (RENT) from a sample of 42 randomly chosen apartments in Parow: Dependent Variable: RENT Variable C ROOM r-square: 0.7180 Parameter -0.7705 2.1331 SE of regression: 2.3397 Std. Error 0.8233 0.2114 sample size = 42 What will be values of the parameters, variance and standard errors of the parameters, estimated variance of error terms, coefficient of determination and correlation coefficient, if RENT is measured in Rands and there is no change to the unit of measurement of the ROOM variable?
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