G.12.b

Use technology to find the least-squares line of best fit for two quantitative variables.

Example Problems
Zara studied the age (in years) and resale value (in thousand dollars) of a random sample of 40 used cars. Here is computer output on the sample data:

Regression: resale value vs. age
PredictorCoefSE Coef
Constant18.70.9
Age-1.850.31



Assume that all conditions for inference have been met.

Write the expression for the
test statistic for testing the null hypothesis that the population slope in this setting is .
Leona collected data on the battery life (in hours) and price (in dollars) of a random sample of mobile phones. Here is computer output from a least-squares regression analysis on her sample:

PredictorCoefSE Coef
Constant191.31294.318
Battery life6.5563.788




Assume that all conditions for inference have been met.

Write the expression for the
test statistic for testing the null hypothesis that the population slope in this setting is 0.
Mateo collected data on students' heights (in ) and their vertical jump heights (in ) for a random sample of 35 athletes. Here is computer output on the sample data:

Regression: vertical jump vs. height
PredictorCoefSE Coef
Constant-14.322.8
Height0.120.07



Assume that all conditions for inference have been met.

Write the expression for the
test statistic for testing the null hypothesis that the population slope in this setting is ?
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