# Minitab Help 4: SLR Assumptions, Estimation & Prediction

### 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.
- 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.

### 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.

### Chemical solution concentration

- Perform a basic regression analysis with y = y (concentration) and x = x (time).

### Real estate sales

- Perform a basic regression analysis with y = SalePrice and x = Sqrfeet.

### 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.
- 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.
- 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