Suppose You Run a Regression of a Person's Height on His/her

question 33

Multiple Choice

Suppose you run a regression of a person's height on his/her right and left foot sizes,and you suspect that there may be multicollinearity between the foot sizes.What types of problems might you see if your suspicions are true?

• A)"Wrong" values for the coefficients for the left and right foot size
• B)Large p-values for the coefficients for the left and right foot size
• C)Small t-values for the coefficients for the left and right foot size
• D)Large t-values for the coefficients for the left and right foot size

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Definitions:

Extreme Values

Observations in data that are significantly higher or lower than the majority, often indicating outliers or anomalies in datasets.

Stem

In 'stem-and-leaf' displays, the 'stem' represents the leading digits of the numbers, providing a quick overview of data distribution while retaining the original data values.

Categorical Variables

Non-numeric variables that represent categories or groups.

Pie Charts

A type of graph in which a circle is divided into sectors that each represent a proportion of the whole, often used to visualize the relative proportions of different categories.