MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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### Systolic Blood Pressure Measurements Analysis

Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Our goal is to find the regression equation, letting the right arm blood pressure be the predictor (\( x \)) variable. Additionally, we'll be identifying the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 80 mm Hg, using a significance level of 0.05.

#### Blood Pressure Measurements
- **Right Arm:** 100, 99, 93, 77, 77
- **Left Arm:** 174, 168, 148, 148, 146

Click the icon to view the critical values of the Pearson correlation coefficient \( r \).

---

#### Finding the Regression Equation

The regression equation is given by:

\[ \hat{y} = b_0 + b_1 x \]

(Round to one decimal place as needed.)

#### Prediction for Given Blood Pressure

Given that the systolic blood pressure in the right arm is 80 mm Hg, the best predicted systolic blood pressure in the left arm is \( \hat{y} \) mm Hg.

(Round to one decimal place as needed.)

---

### Data Table for Pearson Correlation Coefficient \( r \)

The table below provides critical values of the Pearson correlation coefficient \( r \) for significance levels \( \alpha = 0.05 \) and \( \alpha = 0.01 \):

#### Critical Values of the Pearson Correlation Coefficient \( r \)

| \( n \) | \( \alpha = 0.05 \) | \( \alpha = 0.01 \) |
|:------:|:-------------------:|:-------------------:|
|    4   |        0.950        |         0.990       |
|    5   |        0.878        |         0.959       |
|    6   |        0.811        |         0.917       |
|    7   |        0.754        |         0.875       |
|    8   |        0.707        |         0.834       |
|    9   |        0.666        |         0.798       |
|   10   |        0.632        |         0
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Transcribed Image Text:### Systolic Blood Pressure Measurements Analysis Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Our goal is to find the regression equation, letting the right arm blood pressure be the predictor (\( x \)) variable. Additionally, we'll be identifying the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 80 mm Hg, using a significance level of 0.05. #### Blood Pressure Measurements - **Right Arm:** 100, 99, 93, 77, 77 - **Left Arm:** 174, 168, 148, 148, 146 Click the icon to view the critical values of the Pearson correlation coefficient \( r \). --- #### Finding the Regression Equation The regression equation is given by: \[ \hat{y} = b_0 + b_1 x \] (Round to one decimal place as needed.) #### Prediction for Given Blood Pressure Given that the systolic blood pressure in the right arm is 80 mm Hg, the best predicted systolic blood pressure in the left arm is \( \hat{y} \) mm Hg. (Round to one decimal place as needed.) --- ### Data Table for Pearson Correlation Coefficient \( r \) The table below provides critical values of the Pearson correlation coefficient \( r \) for significance levels \( \alpha = 0.05 \) and \( \alpha = 0.01 \): #### Critical Values of the Pearson Correlation Coefficient \( r \) | \( n \) | \( \alpha = 0.05 \) | \( \alpha = 0.01 \) | |:------:|:-------------------:|:-------------------:| | 4 | 0.950 | 0.990 | | 5 | 0.878 | 0.959 | | 6 | 0.811 | 0.917 | | 7 | 0.754 | 0.875 | | 8 | 0.707 | 0.834 | | 9 | 0.666 | 0.798 | | 10 | 0.632 | 0
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