Now say a simple linear regression model is fit to the data. Fitting the simple linear regression model, the estimated regression equation is: Y = 6.4285 +1.0534X i. The original units of measurement were Y=distance length in inches and X=height in inches. Now say the response variable is recorded in feet NOT inches (there are 12 inches in one feet). What will happen to the intercept estimate of 6.4285? Will it stay the same, increase, or decrease? Explain in a sentence or two. j. The original units of measurement were Y=distance length in inches and X=height in inches. Now say the explanatory variable is recorded in feet NOT inches (there are 12 inches in oe feet). What will happen to the intercept estimate of 6.4285? Will it stay the same, increase, or decrease? Explain in a sentence or two. k. Continue with the situation in part j. Let pi be the correlation coefficient between distance in inches and height in inches. Let p2 be the correlation coefficient between distance in inches and height in feet. Is pi equal to, less than, or greater than P2. Explain in a sentence.
Now say a simple linear regression model is fit to the data. Fitting the simple linear regression model, the estimated regression equation is: Y = 6.4285 +1.0534X i. The original units of measurement were Y=distance length in inches and X=height in inches. Now say the response variable is recorded in feet NOT inches (there are 12 inches in one feet). What will happen to the intercept estimate of 6.4285? Will it stay the same, increase, or decrease? Explain in a sentence or two. j. The original units of measurement were Y=distance length in inches and X=height in inches. Now say the explanatory variable is recorded in feet NOT inches (there are 12 inches in oe feet). What will happen to the intercept estimate of 6.4285? Will it stay the same, increase, or decrease? Explain in a sentence or two. k. Continue with the situation in part j. Let pi be the correlation coefficient between distance in inches and height in inches. Let p2 be the correlation coefficient between distance in inches and height in feet. Is pi equal to, less than, or greater than P2. Explain in a sentence.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Only need part i, j, k. Thank you for the help!
![Now say a simple linear regression model is fit to the data. Fitting the simple linear regression model, the estimated regression equation is:
\[ \hat{Y} = 6.4285 + 1.0534X \]
i. The original units of measurement were Y = distance length in inches and X = height in inches. Now say the *response* variable is recorded in *feet* NOT inches (there are 12 inches in one foot). What will happen to the intercept estimate of 6.4285? Will it stay the same, increase, or decrease? Explain in a sentence or two.
j. The original units of measurement were Y = distance length in inches and X = height in inches. Now say the *explanatory* variable is recorded in *feet* NOT inches (there are 12 inches in one foot). What will happen to the intercept estimate of 6.4285? Will it stay the same, increase, or decrease? Explain in a sentence or two.
k. Continue with the situation in part j. Let ρ₁ be the correlation coefficient between distance in inches and height in inches. Let ρ₂ be the correlation coefficient between distance in inches and height in feet. Is ρ₁ equal to, less than, or greater than ρ₂? Explain in a sentence.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fe5f558a7-14fc-4024-84d6-4debb1adc6f6%2F82c151ba-bb09-43ee-8f14-068c9a8b6a1c%2Fsl40zid_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Now say a simple linear regression model is fit to the data. Fitting the simple linear regression model, the estimated regression equation is:
\[ \hat{Y} = 6.4285 + 1.0534X \]
i. The original units of measurement were Y = distance length in inches and X = height in inches. Now say the *response* variable is recorded in *feet* NOT inches (there are 12 inches in one foot). What will happen to the intercept estimate of 6.4285? Will it stay the same, increase, or decrease? Explain in a sentence or two.
j. The original units of measurement were Y = distance length in inches and X = height in inches. Now say the *explanatory* variable is recorded in *feet* NOT inches (there are 12 inches in one foot). What will happen to the intercept estimate of 6.4285? Will it stay the same, increase, or decrease? Explain in a sentence or two.
k. Continue with the situation in part j. Let ρ₁ be the correlation coefficient between distance in inches and height in inches. Let ρ₂ be the correlation coefficient between distance in inches and height in feet. Is ρ₁ equal to, less than, or greater than ρ₂? Explain in a sentence.
Transcribed Image Text:**Educational Content: Analyzing Athlete Performance**
**Topic: Exploring the Relationship Between Athlete Height and Long Jump Distance**
A high school track and field coach conducted a study to evaluate the relationship between an athlete's height and their performance in the long jump event. Both the height and jump distance are measured in inches. The coach collected data on each athlete's height and the distance they jumped. In this study, the height of the athlete is the explanatory variable (X), while the length of the jump is the response variable (Y).
**Scatter Plot Analysis:**
The scatter plot below displays the collected data:
- **X-axis (Horizontal):** Represents the height of the athletes, ranging from 68 inches to 78 inches.
- **Y-axis (Vertical):** Represents the distance jumped, ranging from 78 inches to 88 inches.
- **Data Points:** Each point on the scatter plot corresponds to a measurement of an athlete's height against their jump distance.
**Observations:**
- There appears to be a positive correlation between height and jump distance, as taller athletes generally tend to have longer jump distances.
- The data points are scattered in a pattern that suggests an upward trend, indicating that as the explanatory variable (height) increases, the response variable (jump distance) also increases.
This study helps demonstrate how height can be a factor in athletic performance, particularly in long jump events, providing valuable insights for coaches in training athletes.
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