You have noticed that there seems to be a relationship between the outdoor temperature (measured in degrees Fahrenheit) and the number of minutes it takes for your car to cool to a comfortable seventy-one degrees. You conduct an experiment, gathering data on randomly chosen days. Your data is displayed in the graph and computer printout below.
Coefficients:
Residual standard error: 1.2124 on 29 degrees of freedom R-squared: 0.51, Adjusted R-squared: 0.4931 F-statistic: 30.1878 on 1 and 29 DF, p-value: 6.43E-6 |
Is there evidence, at a 5% level of significance, of a linear relationship between the outdoor temperature and the number of minutes it takes for your car to cool? Assume that the conditions for inference have been satisfied.
a) Write the equation of the best-fit line. Use x and y for your variables.
b) State the parameter of interest. Write out the null and alternate hypothesis.
c) Carry out the procedure ("crunch the numbers"):
Sample statistic:
Standard error of statistic:
Standardized test statistic:
P-value:
d) Should the null hypothesis be rejected? (Enter "yes" or "no".)
Write a conclusion in context.