Question

The scatter plots shows the relationship between the number of levels and the total number of parking spaces in 10 different parking garages. Option 1: The scatter plot shows a positive correlation between the number of levels and the total number of parking spaces. Option 2: The scatter plot shows a negative correlation between the number of levels and the total number of parking spaces. Option 3: The scatter plot shows no correlation between the number of levels and the total number of parking spaces. Option 4: The scatter plot shows a perfect correlation between the number of levels and the total number of parking spaces.

Answer 1

The scatter plot shows the relationship between the number of levels and the total number of parking spaces in 10 different parking garages. The scatter plot can help determine the correlation between the variables.

Step-by-step explanation:

The scatter plot shows the relationship between the number of levels and the total number of parking spaces in 10 different parking garages. To determine the correlation, we can analyze the scatter plot. If the scatter plot roughly forms an increasing line from left to right, it indicates a positive correlation (Option 1). If the scatter plot roughly forms a decreasing line from left to right, it indicates a negative correlation (Option 2). If the scatter plot does not show any clear pattern, it indicates no correlation (Option 3). If the scatter plot forms a perfectly increasing or decreasing line, it indicates a perfect correlation (Option 4).

Answer 2

The question is about identifying the type of correlation in a scatter plot and determining if the variables are good candidates for linear regression. Positive, negative, and zero correlations depict different relationships between variables in scatter plots.

Step-by-step explanation:

The question refers to the relationship exhibited in a scatter plot and its importance in understanding correlation and the potential for linear regression. In scatter plots, correlation indicates the degree to which two variables are related. Specifically:

By examining the scatter plot provided for the parking garages' levels versus the total number of parking spaces, one can determine the correlation type and decide if these variables are suitable for linear regression. If the points lie close to a straight line, the data would be considered for linear regression. However, if the points follow a curved pattern, a different model might be more appropriate.