Please tell if I am doing things correctly. Question 1: What is the Pearson correlation r? (report to 2 decimal places) The Pearson correlation coefficient rr is given by the square root of R2R2. Since the provided R2R2 (coefficient of determination) is 89.89%, r=0.8989=0.9481r=0.8989 r =0.9481 The slope sign in the regression equation will determine the r sign. Since the slope is negative, rr will also be negative. r=−0.9481r=−0.9481 Answer: r=−0.95r=−0.95 (rounded to two decimal places) What is the strength of this relationship? Given that the absolute value of rr is 0.95, which is very close to 1, this indicates a very strong linear relationship. Answer: Strong Q;If you use the regression equation to make a prediction, what error or residual would you expect? (report to 3 decimal places) The residual standard error SS represents the typical amount by which the data points deviate from the regression line. It gives a measure of the spread of the residuals about the fitted regression line. The given value of SS is 0.345210.
Please tell if I am doing things correctly. Question 1: What is the Pearson correlation r? (report to 2 decimal places) The Pearson correlation coefficient rr is given by the square root of R2R2. Since the provided R2R2 (coefficient of determination) is 89.89%, r=0.8989=0.9481r=0.8989 r =0.9481 The slope sign in the regression equation will determine the r sign. Since the slope is negative, rr will also be negative. r=−0.9481r=−0.9481 Answer: r=−0.95r=−0.95 (rounded to two decimal places) What is the strength of this relationship? Given that the absolute value of rr is 0.95, which is very close to 1, this indicates a very strong linear relationship. Answer: Strong Q;If you use the regression equation to make a prediction, what error or residual would you expect? (report to 3 decimal places) The residual standard error SS represents the typical amount by which the data points deviate from the regression line. It gives a measure of the spread of the residuals about the fitted regression line. The given value of SS is 0.345210.
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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Please tell if I am doing things correctly.
Question 1: What is the Pearson
r =0.9481 The slope sign in the regression equation will determine the r sign. Since the slope is negative, rr will also be negative. r=−0.9481r=−0.9481
Answer: r=−0.95r=−0.95 (rounded to two decimal places)
- What is the strength of this relationship? Given that the absolute value of rr is 0.95, which is very close to 1, this indicates a very strong linear relationship.
Answer: Strong
Q;If you use the regression equation to make a prediction, what error or residual would you expect? (report to 3 decimal places) The residual standard error SS represents the typical amount by which the data points deviate from the regression line. It gives a measure of the spread of the residuals about the fitted regression line. The given value of SS is 0.345210.
Transcribed Image Text:Major concerns for many topics such as global climate change and social security
benefits include population growth rates and age of the population. The global
median age has increased from just over 20 years in 1970 to just over 30 years in
2022. A report from Age Structure (H. Ritchie and M. Roser) in Our World in Data
looked at the relationship between the median age of a country and the natural
growth rate of a country. Countries with lower median age tend to have higher
population growth rates. See the graph and analysis below:
Natural growth rate vs Median age
Natural growth rate
3
N
-1
-2
10
Regression Equation
20
S R-Sq
0.34521089.89%
30
40
Median age
Natural growth rate = 4.2464 -0.10808 Median age
Model Summary
50
60
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