X 10.2.17 Question Help ▼ Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 90 mm Hg. Use a significance level of 0.05. Right Arm 101 100 92 76 75 O Left Arm 174 167 181 146 148 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y=+x. (Round to one decimal place as needed.) Enter your answer in the edit fields
X 10.2.17 Question Help ▼ Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 90 mm Hg. Use a significance level of 0.05. Right Arm 101 100 92 76 75 O Left Arm 174 167 181 146 148 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y=+x. (Round to one decimal place as needed.) Enter your answer in the edit fields
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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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.
Question
![### Blood Pressure Measurements Analysis
**Objective:**
Determine the best predicted systolic blood pressure in the left arm using the systolic blood pressure readings from the right arm as the predictor (x) variable, utilizing the regression equation.
**Significance Level:**
0.05
**Data:**
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman:
| Right Arm (x) | 101 | 100 | 92 | 76 | 75 |
|---------------|-----|-----|-----|-----|-----|
| Left Arm (y) | 174 | 167 | 181 | 146 | 148 |
**Steps:**
1. **Find the regression equation:**
The regression equation is of the form:
\[
\hat{y} = \beta_0 + \beta_1 x
\]
Where \(\hat{y}\) is the predicted value of the left arm systolic blood pressure.
2. **Pearson Correlation Coefficient:**
- Click the icon to view the critical values of the Pearson correlation coefficient \(r\).
3. **Prediction:**
- Use the regression equation to predict the systolic blood pressure in the left arm (\(\hat{y}\)) given that the systolic blood pressure in the right arm is 90 mm Hg.
**Notes:**
- Round off the coefficients to one decimal place as needed.
**Interactive Elements:**
- The site provides an icon where users can click to view the critical values of the Pearson correlation coefficient \(r\), aiding in determining the relationship strength between the two variables.
Ultimately, the task requires calculating the regression coefficients (\(\beta_0\) and \(\beta_1\)) and using them to estimate left arm systolic blood pressure based on a right arm reading.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F2f4a9f05-fdd6-4e90-876c-ee547117be59%2F192f8c2f-23db-472d-9667-0248cb98d9e3%2F6xexsvw_processed.jpeg&w=3840&q=75)
Transcribed Image Text:### Blood Pressure Measurements Analysis
**Objective:**
Determine the best predicted systolic blood pressure in the left arm using the systolic blood pressure readings from the right arm as the predictor (x) variable, utilizing the regression equation.
**Significance Level:**
0.05
**Data:**
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman:
| Right Arm (x) | 101 | 100 | 92 | 76 | 75 |
|---------------|-----|-----|-----|-----|-----|
| Left Arm (y) | 174 | 167 | 181 | 146 | 148 |
**Steps:**
1. **Find the regression equation:**
The regression equation is of the form:
\[
\hat{y} = \beta_0 + \beta_1 x
\]
Where \(\hat{y}\) is the predicted value of the left arm systolic blood pressure.
2. **Pearson Correlation Coefficient:**
- Click the icon to view the critical values of the Pearson correlation coefficient \(r\).
3. **Prediction:**
- Use the regression equation to predict the systolic blood pressure in the left arm (\(\hat{y}\)) given that the systolic blood pressure in the right arm is 90 mm Hg.
**Notes:**
- Round off the coefficients to one decimal place as needed.
**Interactive Elements:**
- The site provides an icon where users can click to view the critical values of the Pearson correlation coefficient \(r\), aiding in determining the relationship strength between the two variables.
Ultimately, the task requires calculating the regression coefficients (\(\beta_0\) and \(\beta_1\)) and using them to estimate left arm systolic blood pressure based on a right arm reading.
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