A study was conducted to determine if a person’s agreeability (whether they are
ID: 2910061 • Letter: A
Question
A study was conducted to determine if a person’s agreeability (whether they are generally an agreeable person or not) affects their income level. It also looked at the person’s gender to see if it was a factor as well. The variables are shown below:
Income: y = annual income in dollars
Agree: x1 = agreeability level with higher scores indicating a person is more aggregable and lower scores indicating less agreeable
Gender: x2 = 1 if male, 0 if female
Use the following information to answer the multiple regression questions.
Printout C: Least Squares Linear Regression of Income
Predictor
Variables Coefficient Std Error T P
Constant 40977.1 8788.81 4.66 0.0000
Agree -5479.36 2643.95 -1.07 0.2409
Gender 54225.1 12988.7 4.17 0.0001
x1x2 -8708.14 3934.83 -2.21 0.0293
R² 0.7626 Mean Square Error (MSE) 6.047E+07
Adjusted R² 0.7552 Standard Deviation 7700.00
Source DF SS MS F P
Regression 3 1.865E+10 6.217E+09 102.50 0.0000
Residual 96 5.805E+09 6.047E+07
Total 99 2.446E+10
Which of the following problems would cause us to transform the income variable and begin our model building again?
A plot of the residuals vs. y-hat values indicates a cone pattern.Explanation / Answer
Here' the answer to the question with full concept. Please don't hesitate to give a "thumbs up" in case you're satisfied with the answer
What causes us to transform income variable and begin our model again:
-- a residual vs. y^ ( y predicted) values indicate a spread out ( a cone) pattern
The same case is given in option A -- A plot of the residuals vs. y^ values indicates a conce pattern,
For your understanding when we see cone pattern, then its clear that we have heteroscedasticity in the data and we need to transform the independent variable to solve for this.
Option A is correct.
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