Difference between revisions of "Regression Lab In StatCrunch"
From Sean_Carver
| Line 3: | Line 3: | ||
* We are going to look at the three dimensions of diamonds and how they covary: length (x), width (y), and height (z). | * 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). | * Make a scatter plot for (x versus y) and separately for (x versus z). | ||
| − | * One of the conditions for | + | * One of the conditions for correlation and regression is the "No outliers condition." |
| + | * Do you see outliers in plots. | ||
| + | * Click on an outlier to turn it pink. | ||
| + | * Is the outlier an outlier for the other relationship. | ||
| + | * 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? Discuss. | ||
| + | * Do correlation and regression with the outliers and without the outliers. | ||
| + | * 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. | ||
Revision as of 15:35, 10 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 plots.
- Click on an outlier to turn it pink.
- Is the outlier an outlier for the other relationship.
- 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? Discuss.
- Do correlation and regression with the outliers and without the outliers.
- 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.
