PS.SPID.6

Using technology, create scatterplots and analyze those plots to compare the fit of linear, quadratic, or exponential models to a given data set. Select the appropriate model, fit a function to the data set, and uses the function to solve problems in the context of the data.

Example Problems
Isabella is studying the relationship between daily study hours and exam score. She records data for a random sample of 22 students. Here is computer output from a least-squares regression analysis on her sample:

PredictorCoefSE CoefTP
Constant52.305.0510.360.00
Study hours4.521.054.300.00




Assume that all conditions for inference have been met.

Write the expression for a
99% confidence interval for the slope of the least squares regression line.
Jamal collected data on vehicle engine displacement (in liters) and CO2 emissions (in grams per kilometer) for a random sample of 41 car models. Here is computer output from a least-squares regression analysis on his sample:

PredictorCoefSE CoefTP
Constant74.2022.803.260.00
Displacement68.3011.905.740.00


S = 48.60 R-sq = 69.5%

Assume that all conditions for inference have been met.

Write the expression for a
95% confidence interval for the slope of the least squares regression line.
Aisha is studying the relationship between altitude (in meters) and the boiling point of water (in °C) across 35 towns. Here is computer output from a least-squares regression analysis on her sample:

PredictorCoefSE CoefTP
Constant100.300.60167.170.00
Altitude-0.0180.005-3.600.00




Assume that all conditions for inference have been met.

Write the expression for a
99% confidence interval for the slope of the least squares regression line.
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