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Read the following description of a data set. $\newline$ Todd works with a property developer building houses close to the coastline in Italy. His boss thinks that demand for the houses will be based primarily on their size. Todd wants to show his boss that proximity to the ocean is also a big factor to consider.So, he looks at several houses of the same size in the area. He records the distance of each house from the ocean (in kilometers), $x$ . He also notes the number of people who offered to buy each house, $y$ , when it was last put up for sale.The least squares regression line of this data set is: $y = -1.748x + 34.569$ $\newline$ Complete the following sentence: $\newline$ For each additional kilometer away from the ocean, the least squares regression line predicts there will be $\_\_$ fewer offers.

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Interpret regression lines

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Q. Read the following description of a data set.

\newline

Todd works with a property developer building houses close to the coastline in Italy. His boss thinks that demand for the houses will be based primarily on their size. Todd wants to show his boss that proximity to the ocean is also a big factor to consider.So, he looks at several houses of the same size in the area. He records the distance of each house from the ocean (in kilometers),

x

. He also notes the number of people who offered to buy each house,

y

, when it was last put up for sale.The least squares regression line of this data set is:

y = -1.748x + 34.569

\newline

Complete the following sentence:

\newline

For each additional kilometer away from the ocean, the least squares regression line predicts there will be

\_\_

fewer offers.

Calculate Change: Now, let's calculate the change in the number of offers for each additional kilometer away from the ocean using the slope of the regression line.
Check for Errors: We need to check if there is any math error in our calculation.

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