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Do blondes raise more funds? During fundraising, does the physical appearance of the solicitor impact the level of capital raised? An economist at the University of Nevada- Reno designed an experiment to answer this question and published the results in Economic Letters (Vol. 100, 2008). Each in a sample of 955 households was contacted by a female solicitor and asked to contribute to the Center for Natural Hazards Mitigation Research. The level of contribution (in dollars) was recorded as well as the hair color of the solicitor (blond Caucasian, brunette Caucasian, or minority female).

a) Consider a model for the mean level of contribution, E(y), that allows for different means depending on the hair color of the solicitor. Create the appropriate number of dummy variables for hair color. (Use minority female as the base level.)

b) Write the equation of the model, part a, incorporating the dummy variables.

c) In terms of the b’s in the model, what is the mean level of contribution for households contacted by a blond Caucasian solicitor?

d) In terms of the b’s in the model, what is the difference between the mean level of contribution for households contacted by a blond solicitor and those contacted by a minority female?

e) One theory posits that blond solicitors will achieve the highest mean contribution level, but that there will be no difference between the mean contribution levels attained by brunette Caucasian and minority females. If this theory is true, give the expected signs of the’s in the model.

f) The researcher found the b estimate for the dummy variable for blond Caucasian to be positive and significantly different from 0 (p-value < 0.01). Theβestimate for the dummy variable for brunette Caucasian was also positive, but not significantly different from 0 (p-value < 0.10). Do these results support the theory, part e?

Short Answer

Expert verified

a) For k no of level, the dummy variable created in the model is (k-1). Since here, there are 3 levels, 2 dummy variable x1 and x2 will be created where x1 represents a female with blond Caucasian hair color and x2 represents a female with brunette Caucasian hair color.

b) A model with 2 dummy variables can be written as y=β0+β1x1+β2x2where x1represents female with blond Caucasian hair color and x2represents female with brunette Caucasian hair color.

c) The mean contribution level for households contacted by a blond Caucasian solicitor is represented when thus the value of contribution can be summarized.

d) The mean level of difference in contribution for households contacted by a blond solicitor and those contacted by a minority female is represented byβ1.

e) β0will be positive since it represents the level of contribution of a household at the base level (which here is when the solicitor is minority female). β1will also be positive since the theory posits that the blond solicitors will collect the highest mean contribution level.β2 will not be recorded in the model since the mean contribution levels of brunette Caucasian and minority female is the same.

f) To check whetherβ1 is different from 0, theH0:β1 while H0:β10. Since the value of the p-value is given to be less than 0.01 which indicates that the value of β1is not zero. However, forβ2 the value is coming to be positive but not significantly different from 0 since the p-value is greater than 0.10 thus the value of β2will be 0.

Step by step solution

01

Creating dummy variables

For k no of level, the dummy variable created in the model is (k-1). Since here, there are 3 levels, 2 dummy variable x1 and x2 will be created where x1 represents female with blond Caucasian hair color and x2 represents female with brunette Caucasian hair color.

02

Dummy variable model

A model with 2 dummy variables can be written as representing a female with blond Caucasian hair color and a female with brunette Caucasian hair color.

03

Interpretation of β

The mean contribution level for households contacted by a blond Caucasian solicitor is represented when thus the value of contribution can be summarized.

04

Analysis of β

The mean level of difference in contribution for households contacted by a blond solicitor and those contacted by a minority female is represented by.β1

05

Signs of β’s

β0will be positive since it represents the level of contribution of a household at the base level (which here is when the solicitor is a minority female)

β1will also be positive since the theory posits that the blond solicitors will collect the highest mean contribution level.

β2will not be recorded in the model since the mean contribution levels of brunette Caucasian and minority female is the same.

06

Hypothesis testing for β’s

To check whetherβ1 is different from 0, theH0:β1whileH0:β10. Since the value of the p-value is given to be less than 0.01 which indicates that the value ofβ1is not zero. However, forβ2the value is coming to be positive but not significantly different from 0 since the p-value is greater than 0.10 thus the value ofβ2will be 0.

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Most popular questions from this chapter

Question: The Excel printout below resulted from fitting the following model to n = 15 data points: y=β0+β1x1+β2x2+ε

Where,

x1=(1iflevel20ifnot)x2=(1iflevel30ifnot)

It is desired to relate E(y) to a quantitative variable x1and a qualitative variable at three levels.

  1. Write a first-order model.

  2. Write a model that will graph as three different second- order curves—one for each level of the qualitative variable.

Question: Write a regression model relating the mean value of y to a qualitative independent variable that can assume two levels. Interpret all the terms in the model.

Consider fitting the multiple regression model

Ey=β0+β1x1+β2x2+β3x3+β4x4+β5x5

A matrix of correlations for all pairs of independent variables is given below. Do you detect a multicollinearity problem? Explain.


Going for it on fourth down in the NFL. Refer to the Chance (Winter 2009) study of fourth-down decisions by coaches in the National Football League (NFL), Exercise 11.69 (p. 679). Recall that statisticians at California State University, Northridge, fit a straight-line model for predicting the number of points scored (y) by a team that has a first-down with a given number of yards (x) from the opposing goal line. A second model fit to data collected on five NFL teams from a recent season was the quadratic regression model, E(y)=β0+β1x+β2x2.The regression yielded the following results: y=6.13+0.141x-0.0009x2,R2=0.226.

a) If possible, give a practical interpretation of each of the b estimates in the model.

b) Give a practical interpretation of the coefficient of determination,R2.

c) In Exercise 11.63, the coefficient of correlation for the straight-line model was reported asR2=0.18. Does this statistic alone indicate that the quadratic model is a better fit than the straight-line model? Explain.

d) What test of hypothesis would you conduct to determine if the quadratic model is a better fit than the straight-line model?

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