Question

A researcher analyzes the factors that may influence amusement park attendance. She estimates the following model:...

A researcher analyzes the factors that may influence amusement park attendance. She estimates the following model: Attendance = β0 + β1Price + β2Temperature + β3Rides + ε, where Attendance is the daily attendance (in 1,000s), Price is the gate price (in $), Temperature is the average daily temperature (in oF), and Rides is the number of rides at the amusement park. A portion of the regression results is shown in the accompanying table.

df SS MS F Significance F
Regression 3 29,524.41 9,841.47 2.18E-14
Residual 26 2,564.37 98.63
Total 29 32,088.78
Coefficients Standard Error t-stat p-value Lower 95% Upper 95%
Intercept 27.328 40.254 0.5032 −55.415 110.071
Price −1.201 0.294 0.0004 −1.805 −0.598
Temperature 0.008 0.208 0.9693 -0.419 0.435
Rides 3.621 0.364 2.32E-10 2.874 4.369


When testing whether Temperature is significant at the 5% significance level, she ________.

Multiple Choice

  • rejects H0:β2 = 0, and concludes that Temperature is significant

  • does not reject H0:β2 = 0, and concludes that Temperature is significant

  • rejects H0:β2 = 0, and cannot conclude that Temperature is significant

  • does not reject H0:β2 = 0, and cannot conclude that Temperature is significant

Homework Answers

Answer #1

Answer: does not reject H0:β2 = 0, and cannot conclude that Temperature is significant

Explanation:

Null Hypothesis, Ho: β2 = 0 i.e Temperature is not significant

Alternative Hypothesis, Ha: β2   0 i.e. Temperature is significant

Decision Rule: Reject the Null Hypothesis Ho if p-value <

Conclusion: Since p-value = 0.9693 > so we fail to Reject the Null Hypothesis and conclude that   β2 = 0 i.e Temperature is not significant

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A researcher analyzes the factors that may influence amusement park attendance. She estimates the following model:...
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