Alcohol consumption and muscle strength

• Perform a basic regression analysis with y = strength and x = alcohol.
• Create a fitted line plot.
• Create residual plots and select "Residuals versus fits" to display a residual plot with fitted values on the horizontal axis.
• Display a residual plot with x = alcohol on the horizontal axis.

Blood pressure

• Perform a basic regression analysis with y = BP and x = Age. Repeat with x = Weight and x = Duration.
• Create a fitted line plot.
• Create residual plots for the model using x = Age and click in the "Residuals versus the variables" box to plot "Weight" on the horizontal axis.
• Perform a basic regression analysis with y = BP, x1 = Age, and x2 = Weight.
• Create residual plots for the model using x1 = Age and x2 = Weight and click in the "Residuals versus the variables" box to plot "Duration" on the horizontal axis.

Tread wear

• Perform a basic regression analysis with y = groove and x = mileage.
• Create a fitted line plot.
• Create residual plots and select "Residuals versus fits" to display a residual plot with fitted values on the horizontal axis.

Plutonium

• Perform a basic regression analysis with y = alpha and x = pluto.
• Create a fitted line plot.
• Create residual plots and select "Residuals versus fits" to display a residual plot with fitted values on the horizontal axis.

Alcohol and tobacco

• Perform a basic regression analysis with y = Alcohol and x = Tobacco.
• Create a fitted line plot.
• Create residual plots and select "Residuals versus fits" to display a residual plot with fitted values on the horizontal axis.
• Use Data > Subset Worksheet to exclude Northern Ireland from the worksheet.
• Perform a basic regression analysis with y = Alcohol and x = Tobacco (excluding Northern Ireland).
• Create a fitted line plot (excluding Northern Ireland).
• Return to the original worksheet that included Northern Ireland.
• Create residual plots and select "Standardized" and "Residuals versus fits" to display a standardized residual plot with fitted values on the horizontal axis.

Anscombe data

• Perform a basic regression analysis with y = y3 and x = x3.
• Create a fitted line plot.
• Create residual plots and select "Residuals versus fits" to display a residual plot with fitted values on the horizontal axis.

Skin cancer mortality

• Perform a basic regression analysis with y = Mort and x = Lat.
• Create a fitted line plot.

Alligators

• Perform a basic regression analysis with y = weight and x = length.
• Create a fitted line plot.

Alloy corrosion

• Perform a basic regression analysis with y = wgtloss and x = iron.
• Create a fitted line plot.

Handspan and height

• Perform a basic regression analysis with y = HandSpan and x = Height.
• Create residual plots and select "Residuals versus fits" to display a residual plot with fitted values on the horizontal axis.

Chemical solution concentration

• Perform a basic regression analysis with y = y (concentration) and x = x (time).
• Create residual plots and select "Residuals versus fits" to display a residual plot with fitted values on the horizontal axis.

Real estate sales

• Perform a basic regression analysis with y = SalePrice and x = Sqrfeet.
• Create residual plots and select "Residuals versus fits" to display a residual plot with fitted values on the horizontal axis.

Old Faithful geyser eruptions

• Perform a basic regression analysis with y = waiting and x = eruption.
• Create residual plots and select "Histogram of residuals" and "Normal probability plot of residuals."

Hospital infection risk

• Use Data > Subset Worksheet to select only hospitals in regions 1 or 2.
• Perform a basic regression analysis with y = InfctRsk and x = Stay.
• Create residual plots and select "Normal probability plot of residuals."

Car stopping distances

• Perform a basic regression analysis with y = StopDist and x = Speed.
• Create a fitted line plot.
• Create residual plots and select "Residuals versus fits" to display a residual plot with fitted values on the horizontal axis.
• Use Calc > Calculator to create a new response variable equal to √StopDist.
• Perform a basic regression analysis with y = √StopDist and x = Speed.
• Create a fitted line plot.
• Create residual plots and select "Residuals versus fits" to display a residual plot with fitted values on the horizontal axis.
• Find a confidence interval and a prediction interval for the response to predict StopDist for Speed = 10, 20, 30, and 40.

Student heights and weights

• Perform a basic regression analysis with y = wt and x = ht.
• Create a fitted line plot.
• Use Editor > Add > Reference Lines to add a horizontal line at the mean weight.
• Find a confidence interval and a prediction interval for the response to predict weight for height = 64.

Skin cancer mortality (revisited)

• Perform a basic regression analysis with y = Mort and x = Lat.
• Create a fitted line plot.
• Find a confidence interval and a prediction interval for the response to calculate 95% confidence intervals for E(Mort) at Lat = 40 and 28.
• Calculate mean(Lat).
• Find a confidence interval and a prediction interval for the response to calculate a 95% prediction interval for Mort at Lat = 40.
• Create a fitted line plot with confidence bands and prediction bands.

Hospital infection risk (revisited)

• Use Data > Subset Worksheet to select only hospitals in regions 1 or 2.
• Create a basic scatterplot of Stay versus InfctRsk.
• Use Data > Subset Worksheet to select only hospitals with Stay < 16 (i.e., remove the two hospitals with extreme values of Stay).
• Perform a basic regression analysis with y = InfctRsk and x = Stay.
• Find a confidence interval and a prediction interval for the response to calculate 95% confidence intervals for E(InfctRsk) at Stay = 10 and 95% prediction intervals for InfctRsk at Stay = 10.
• Create a fitted line plot with confidence bands and prediction bands