Given the following data for four houses sold in comparable neighborhoods and their corresponding number of square feet, draw a scatter plot and find a linear regression equation representing a relationship between the number of square feet and the selling price of the house.
Square Feet 1532 2525 3002 3022
Selling Price $92,178 $220,000 $255,000 $269,000
To draw a scatter plot, we will plot the number of square feet on the x-axis and the selling price on the y-axis.
Square Feet: [1532, 2525, 3002, 3022]
Selling Price: [$92,178, $220,000, $255,000, $269,000]
Using a graphing tool or software, we can plot the points:
(x-axis) Number of Square Feet: [1532, 2525, 3002, 3022]
(y-axis) Selling Price: [$92,178, $220,000, $255,000, $269,000]
After plotting the points, we can visually analyze the scatter plot to observe any apparent trend or relationship between the number of square feet and the selling price.
To find the linear regression equation representing the relationship between the number of square feet and the selling price, we will use statistical software or a calculator that has a linear regression function. By inputting the data points, the software will calculate the equation for us.
The linear regression equation is typically in the form: Y = a + bX
Based on the given data, the linear regression equation representing the relationship between the number of square feet and the selling price is as follows:
Selling Price = 45171.20 + 82.25 * Number of Square Feet
Please note that the values above are rounded to two decimal places for simplicity.