Question

Match each term with its corresponding definition. 1. extrapolate a statistical measure to describe how two random variables are related 2. correlation estimate beyond data points 3. interpolate estimate between data points

Answer 1

The terms 'extrapolate', 'correlation', and 'interpolate' are matched with their definitions. In inferential statistics, estimates are made to infer population parameters from sample data using confidence intervals. To predict values like the cost of supplies, a regression equation is used and the significance of the correlation coefficient is checked.

Step-by-step explanation:

The terms provided relate to statistical analysis, specifically the areas of correlation and regression. Here's how they match with the corresponding definitions:

1. Extrapolate: Estimate beyond data points.
2. Correlation: A statistical measure to describe how two random variables are related.
3. Interpolate: Estimate between data points.

In the context of inferential statistics, we utilize sample data to make estimates about population parameters. We use point estimates to draw close to the value of a population parameter, and then we construct confidence intervals to provide a range of likely values for that parameter.

Regarding the scenarios provided:

1. The total cost of supplies for a person living eight or eighty miles from campus can be predicted using a regression equation (ý = a + bx), where 'a' is the intercept, 'b' is the slope, and 'x' is the distance from campus.
2. To determine significant correlation, we refer to the correlation coefficient and consider whether it is statistically significant based on a given confidence level, often through hypothesis testing like a t-test.

To graph a regression line, you would typically use statistical software or a graphing calculator to plot the data as a scatter plot, calculate the least-squares regression line, and then draw the line through the data points.