Difference between revisions of "Regression Lab In StatCrunch"

Revision as of 02:21, 11 February 2019

Lab 3: Regression, Correlation and Outliers

• We are going to work with the small diamonds data set again: diamonds3K sampled from a larger data set with Codebook.
• We are going to look at the three dimensions of diamonds and how they covary: length (x), width (y), and height (z).
• Make a scatter plot for (x versus y) and separately for (x versus z).
• One of the conditions for correlation and regression is the "No outliers condition."
• Do you see outliers in the plots?
• Click on an outlier to turn it pink.
• Is the outlier an outlier for the other relationship? (x versus y) versus (x versus z).
• Look at the row in the data set for each outlier.
• Can you tell if the data were recorded wrong or if the diamond really had those dimensions? Consider what x, y, and z mean and remember you also have a measure of the diamond's weight (carat). Discuss.
• Repeat for the other outliers.
• Report the correlation coefficient and regression line with the outliers and without the outliers.
• Plot the Residuals versus X-Values, a histogram of the residuals, and a QQ-Plot of the residuals. Where does the outlier(s) show up?
• To do the analyses without the outliers, use Stat, Regression, Simple Linear to Save Residuals.
• Then use a where function to restrict the data to points with small enough residuals.