find the equation of the least-squares regression line you would use for predicting y = sale price. (Give answers to three decimal places.)
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Based on your choice in Part (c), find the equation of the least-squares regression line you would use for predicting y = sale price. (Give answers to three decimal places.)
I attached the picture, thanks in advance!
![**Industrial Property Analysis: Correlation and Prediction of Sale Prices**
The following data on sale price, size, and land-to-building ratio for 10 large industrial properties appeared in a paper.
**Table 1: Property Data**
| Property | Sale Price (millions of dollars) | Size (thousands of sq. ft.) | Land-to-Building Ratio |
|----------|---------------------------------|-----------------------------|------------------------|
| 1 | 10.5 | 2167 | 2.1 |
| 2 | 2.6 | 750 | 3.4 |
| 3 | 30.6 | 2421 | 3.7 |
| 4 | 1.9 | 223 | 4.7 |
| 5 | 20.1 | 3916 | 1.7 |
| 6 | 8.1 | 2865 | 2.3 |
| 7 | 10.2 | 1699 | 3.2 |
| 8 | 6.6 | 1047 | 4.9 |
| 9 | 5.7 | 1107 | 7.5 |
| 10 | 4.4 | 405 | 17.3 |
**Analysis:**
(a) **Calculate the value of the correlation coefficient between sale price and size.**
\[ r = 0.702 \]
(b) **Calculate the value of the correlation coefficient between sale price and land-to-building ratio.**
\[ r = -0.330 \]
(c) **If you wanted to predict sale price and you could use either size or land-to-building ratio as the basis for making predictions, which would you use?**
\[ \text{Size} \]
(d) **Based on your choice in Part (c), find the equation of the least-squares regression line you would use for predicting \(y = \text{sale price}\).**
Let the regression equation be:
\[ \hat{y} = b_0 + b_1 x \]
**Note:** Specific numerical values for \(b_0\) and \(b_1\) would need to be calculated using the provided data.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F865b4b82-948d-4c8a-bb2d-a501f67df990%2F82871848-4eaf-41ae-89e0-6c0d41c96749%2Fkq4ghgk.png&w=3840&q=75)
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