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Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. 772 Height, x Stories, y 628 48 518 45 508 (a) x= 502 feet (c) x= 321 feet 496 483 (b) x= 647 feet (d) x= 732 feet 51 43 38 36 Find the regression equation. (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)

Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. 772 Height, x Stories, y 628 48 518 45 508 (a) x= 502 feet (c) x= 321 feet 496 483 (b) x= 647 feet (d) x= 732 feet 51 43 38 36 Find the regression equation. (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)

A First Course in Probability (10th Edition)
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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**Regression Analysis on Building Heights** This lesson involves analyzing a dataset to find the regression equation that predicts the number of stories in buildings given their heights. The data provided is as follows: | Height (x) | Stories (y) | |------------|-------------| | 772 | 51 | | 628 | 48 | | 518 | 45 | | 508 | 43 | | 496 | 38 | | 483 | 36 | **Task Instructions** 1. **Find the Regression Equation:** - Use the given dataset to calculate the regression line. - Calculate the slope and y-intercept. - Round the slope to three decimal places and y-intercept to two decimal places. 2. **Scatter Plot & Regression Line:** - Construct a scatter plot with the given data points. - Draw the regression line on the scatter plot. 3. **Predict Values:** - Use the regression equation to predict 'y' (the number of stories) for the given x-values: - (a) x = 502 feet - (b) x = 647 feet - (c) x = 321 feet - (d) x = 732 feet **Note:** This analysis assumes a significant correlation between the heights of buildings and the number of stories. **Further Steps:** - Use tools to help solve and visualize the data. - Check your answers for further understanding.
Transcribed Image Text:**Regression Analysis on Building Heights** This lesson involves analyzing a dataset to find the regression equation that predicts the number of stories in buildings given their heights. The data provided is as follows: | Height (x) | Stories (y) | |------------|-------------| | 772 | 51 | | 628 | 48 | | 518 | 45 | | 508 | 43 | | 496 | 38 | | 483 | 36 | **Task Instructions** 1. **Find the Regression Equation:** - Use the given dataset to calculate the regression line. - Calculate the slope and y-intercept. - Round the slope to three decimal places and y-intercept to two decimal places. 2. **Scatter Plot & Regression Line:** - Construct a scatter plot with the given data points. - Draw the regression line on the scatter plot. 3. **Predict Values:** - Use the regression equation to predict 'y' (the number of stories) for the given x-values: - (a) x = 502 feet - (b) x = 647 feet - (c) x = 321 feet - (d) x = 732 feet **Note:** This analysis assumes a significant correlation between the heights of buildings and the number of stories. **Further Steps:** - Use tools to help solve and visualize the data. - Check your answers for further understanding.
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