# Economics Math: Correlations / Linear & Multiple Regression (Math Problem Sample)

Complete Problem 50 in Chapter 10 on page 477.

0-55) A golf club manufacturer is trying to determine how the price of a set of clubs affects the demand for clubs. The file P10_50.xlsx contains the price of a set of clubs and the monthly sales.

Assume the only factor influencing monthly sales is price. Fit the following three curves to these data: linear (Y = a + bX), exponential (Y = abX), and multiplicative (Y = aXb). Which equation fits the data best?

Interpret your best-fitting equation.

Using the best-fitting equation, predict sales during a month in which the price is $470.

In the discussion area, attach the Excel document showing work.

Please provide step by step instructions

Correlations/Linear & Multiple Regression

Name

Institution

Date

A golf club manufacturer is trying to determine how the price of a set of clubs affects the demand for clubs. The file P10_50.xlsx contains the price of a set of clubs and the monthly sales. Assume the only factor influencing monthly sales is price. Fit the following three curves to these data: linear (Y = a + bX), exponential (Y = abX), and multiplicative (Y = aXb). Which equation fits the data best?Interpret your best-fitting equation.

Assume the only factor influencing monthly sales is price. Fit the following three curves to these data: linear (Y = a + bX), exponential (Y = abX), and multiplicative (Y = aXb). Which equation fits the data best? 470.

Linear (Y = a + bX)

Regression line equation: y=50579.32-70.79x

Where Y is demand and x is price

When price is $ 470 the sales is 50579.32-70.79x=17,308

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.948677

R Square

0.899989

Adjusted R Square

0.887488

Standard Error

3251.334

Observations

10

ANOVA

df

SS

MS

F

Significance F

Regression

1

7.61E+08

7.61E+08

71.99113

2.85239E-05

Residual

8

84569378

10571172

Total

9

8.46E+08

Coefficients

Standard Error

t Stat

P-value

Intercept

50579.32

3612.023

14.00304

6.56E-07

X Variable 1

-70.7935

8.343613

-8.48476

2.85E-05

Exponential (Y = abX)

To get the equation We take the natural logarithms of the Y values ro give the model

Ln(Y)= 11.51-0.00399X

Y=e

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