Regression Lab

DataOpen the inclusive-internet data set in the Stats at Cuyamaca College group on StatCrunch (directions).
PromptWe’ll use StatCrunch to produce the scatterplot with its least squares regression line, the regression equation, r-squared, and the standard error for two different regression models. Then we’ll determine which model is the best predictor of the response variable, percent-female-net.
Question 1
Using lit-level as the explanatory variable and percent-female-net as the response variable: graph the scatterplot with its regression line and produce the regression equation with r-squared and the standard error – all at the same time (directions). You should see page 1 of 2 of the StatCrunch output window. Copy all information above the Parameter estimates: table (do not copy the tables). Paste the information into your response.
Toggle to page page 2 of 2 of the StatCrunch output window. Download the scatterplot with the regression line and embed the .png file with your response.

Write the equation of the regression equation below as displayed in page 1 of 2 of the StatCrunch output window (or even better just copy and paste the equation). Round the values to two decimal places. Identify the slope and y-intercept and interpret each in context.
Identify r-squared (round to 4 decimal places). Then explain what r-squared means in context.
Identify the standard error, Se (round to 2 decimal places). Interpret the standard error in context.
Question 2
Using percent-schools-w-net as the explanatory variable and percent-female-net as the response variable: graph the scatterplot with the regression line and produce the regression equation with r-squared and the standard error – all at the same time (directions). You should see page 1 of 2 of the StatCrunch output window. Copy all information above the Parameter estimates: table (do not copy the tables). Paste the information into your response.
Toggle to page page 2 of 2 of the StatCrunch output window. Download the scatterplot with its regression line and embed the .png file with your response.

Write the equation of the regression equation below as displayed in page 1 of 2 of the StatCrunch output window (or even better just copy and paste the equation). Round the values to two decimal places. Identify the slope and y-intercept and interpret each in context.
Identify r-squared and round to 4 decimal places. Then explain what r-squared means in context.
Identify the standard error, Se (round to 2 decimal places). Interpret the standard error in context.
Question 3
Which regression equation is the best predictor? Use your work in Questions 1

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