Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the critical values of r using a = 0.01. Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals? Overhead Width 7.1 7.6 204 9.7 241 9.3 8.8 8.4 197 202 192 Weight 111 Click here to view a table of critical values for the correlation coefficient. (*** Construct a scatterplot. Choose the correct graph below. OA. OB. OD. Aweight (kg) Aweight (kg) Q Q Aweight (kg) Q 300 300- 300- -▬▬▬▬ Q ▬▬▬▬▬▬▬▬▬ ..... Q C Q TOO 100+ G 100- G 7 10 width (cm) width (cm) width (cm) width (cm) The linear correlation coefficient is r=- (Round to three decimal places as needed.) The critical values are r=. (Round to three decimal places as needed. Use a comma to separate answers as needed.) sufficient evidence to support the claim that there is a linear correlation between overhead widths of seals from photographs Because the absolute value of the linear correlation coefficient is and the weights of the seals for a significance level of α=0.01. Aweight (kg) F PRO than the positive critical value, there O C. 300 100+ 10 100+
Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the critical values of r using a = 0.01. Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals? Overhead Width 7.1 7.6 204 9.7 241 9.3 8.8 8.4 197 202 192 Weight 111 Click here to view a table of critical values for the correlation coefficient. (*** Construct a scatterplot. Choose the correct graph below. OA. OB. OD. Aweight (kg) Aweight (kg) Q Q Aweight (kg) Q 300 300- 300- -▬▬▬▬ Q ▬▬▬▬▬▬▬▬▬ ..... Q C Q TOO 100+ G 100- G 7 10 width (cm) width (cm) width (cm) width (cm) The linear correlation coefficient is r=- (Round to three decimal places as needed.) The critical values are r=. (Round to three decimal places as needed. Use a comma to separate answers as needed.) sufficient evidence to support the claim that there is a linear correlation between overhead widths of seals from photographs Because the absolute value of the linear correlation coefficient is and the weights of the seals for a significance level of α=0.01. Aweight (kg) F PRO than the positive critical value, there O C. 300 100+ 10 100+
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Need help with this, the third one is greater or less, is or is not.
------------------------------
**Scatterplot Construction:**
**Select the Correct Graph:**
**Option A**
| weight (kg) | | 300 | | | | | |
| ----------- | ---- | --- | ---- | ---- | ---- | ---- | ---- |
| | 300 | | | | | | | 300 |
| | 200 | | | | | | | 200 |
| | 100 | | | | | | | 100 |
| overhead width (cm) | | | 7 | | | | 10 |
\( \bigcirc \) **Option B**
**Option C**
| weight (kg) | | 300 | | | | | |
| ----------- | ---- | --- | ---- | ---- | ---- | ---- | ---- |
| | 300 | | | | | | | 300 |
| | 200 | | | | | | | 200 |
| | 100 | | | | | | | 100 |](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F4b33feb0-e62b-4e25-aad1-2d23e491b0f1%2F1d3ca89a-e716-4321-b731-a211ecd0dff3%2Fi34hqil_processed.png&w=3840&q=75)
Transcribed Image Text:### Correlation Analysis: Overhead Widths and Weights of Seals
**Problem Statement:**
Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient \( r \), and find the critical values of \( r \) using \( \alpha = 0.01 \). Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals?
------------------------------
**Data Provided:**
| Overhead Width (cm) | 7.1 | 7.6 | 9.7 | 9.3 | 8.8 | 8.4 |
| ------------------- | --- | --- | --- | --- | --- | --- |
| Weight (kg) | 111 | 204 | 241 | 197 | 202 | 192 |
[Click here to view a table of critical values for the correlation coefficient.](#)
------------------------------
**Scatterplot Construction:**
**Select the Correct Graph:**
**Option A**
| weight (kg) | | 300 | | | | | |
| ----------- | ---- | --- | ---- | ---- | ---- | ---- | ---- |
| | 300 | | | | | | | 300 |
| | 200 | | | | | | | 200 |
| | 100 | | | | | | | 100 |
| overhead width (cm) | | | 7 | | | | 10 |
\( \bigcirc \) **Option B**
**Option C**
| weight (kg) | | 300 | | | | | |
| ----------- | ---- | --- | ---- | ---- | ---- | ---- | ---- |
| | 300 | | | | | | | 300 |
| | 200 | | | | | | | 200 |
| | 100 | | | | | | | 100 |
Transcribed Image Text:**Table of Critical Values**
This table provides the critical values for the linear correlation coefficient \( r \), at significance levels \( \alpha = 0.05 \) and \( \alpha = 0.01 \), for different sample sizes \( n \).
| \( n \) | \( \alpha = .05 \) | \( \alpha = .01 \) |
|---------|--------------------|--------------------|
| 4 | .950 | .990 |
| 5 | .878 | .959 |
| 6 | .811 | .917 |
| 7 | .754 | .875 |
| 8 | .707 | .834 |
| 9 | .666 | .798 |
| 10 | .632 | .765 |
| 11 | .602 | .735 |
| 12 | .576 | .708 |
| 13 | .553 | .684 |
| 14 | .532 | .661 |
| 15 | .514 | .641 |
| 16 | .497 | .623 |
| 17 | .482 | .606 |
| 18 | .468 | .590 |
| 19 | .456 | .575 |
| 20 | .444 | .561 |
| 25 | .396 | .505 |
| 30 | .361 | .463 |
| 35 | .335 | .430 |
| 40 | .312 | .402 |
The two scatter plots on the left (marked as B and D) illustrate a graphical representation of weights (kg) versus widths (cm) for a dataset.
- **Scatter Plot B:** Points cluster around 200 kg for weights and span from about 7 cm to 10 cm for widths.
- **Scatter Plot D:** Similar to Scatter Plot B, with points clustering around 200 kg for weights and spanning from about 7 cm to 10 cm for widths.
The scatter plots can be used to visually estimate the presence and strength of a linear correlation between the two variables.
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