Below a scatter diagram for x and y. The sample correlation coefficient for the data r = -0.823. 100 90 80 70 60 <-50 40 30 20 10 0 5 10 15 20 25 30 35 Is there a linear correlation between x and y? Use the "Critical Values for Correlation Coefficient" table provided to justify your answer. If there is linear correlation, is it positive or negative?

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**Scatter Diagram and Correlation Analysis**

Below is a scatter diagram for variables \( x \) and \( y \). The sample correlation coefficient for the data is \( r = -0.823 \).

**Scatter Diagram Description:**

The scatter diagram consists of several plotted points that represent paired values of \( x \) and \( y \). The \( x \)-axis ranges from 0 to 35, while the \( y \)-axis ranges from 0 to 100. The points appear to follow a downward trend, suggesting a possible negative relationship between the two variables.

**Questions for Analysis:**

1. **Is there a linear correlation between \( x \) and \( y \)?** 
   - Use the "Critical Values for Correlation Coefficient" table provided to justify your answer.

2. **If there is linear correlation, is it positive or negative?**

Based on the given information, since \( r = -0.823 \), it indicates a strong negative linear correlation between \( x \) and \( y \).
Transcribed Image Text:**Scatter Diagram and Correlation Analysis** Below is a scatter diagram for variables \( x \) and \( y \). The sample correlation coefficient for the data is \( r = -0.823 \). **Scatter Diagram Description:** The scatter diagram consists of several plotted points that represent paired values of \( x \) and \( y \). The \( x \)-axis ranges from 0 to 35, while the \( y \)-axis ranges from 0 to 100. The points appear to follow a downward trend, suggesting a possible negative relationship between the two variables. **Questions for Analysis:** 1. **Is there a linear correlation between \( x \) and \( y \)?** - Use the "Critical Values for Correlation Coefficient" table provided to justify your answer. 2. **If there is linear correlation, is it positive or negative?** Based on the given information, since \( r = -0.823 \), it indicates a strong negative linear correlation between \( x \) and \( y \).
### Critical Values for Correlation Coefficient

The table below provides the critical values for the correlation coefficient. These values are essential for determining the statistical significance of a correlation in hypothesis testing. The column labeled "n" represents the sample size, while the adjacent numbers indicate the critical correlation coefficients for that particular sample size.

| n  | Coefficient | n  | Coefficient | n  | Coefficient | n  | Coefficient |
|----|-------------|----|-------------|----|-------------|----|-------------|
| 3  | 0.997       | 10 | 0.632       | 17 | 0.482       | 24 | 0.404       |
| 4  | 0.950       | 11 | 0.602       | 18 | 0.468       | 25 | 0.396       |
| 5  | 0.878       | 12 | 0.576       | 19 | 0.456       | 26 | 0.388       |
| 6  | 0.811       | 13 | 0.553       | 20 | 0.444       | 27 | 0.381       |
| 7  | 0.754       | 14 | 0.532       | 21 | 0.433       | 28 | 0.374       |
| 8  | 0.707       | 15 | 0.514       | 22 | 0.423       | 29 | 0.367       |
| 9  | 0.666       | 16 | 0.497       | 23 | 0.413       | 30 | 0.361       |

#### Explanation:

- **Sample Size (n):** This is the number of paired observations.
- **Critical Value of Correlation Coefficient:** The smallest value for the correlation coefficient that can be considered statistically significant at a given significance level, typically 0.05.

This table is utilized in statistical analysis to determine if the observed correlation in a sample is significantly different from zero at a certain significance level.
Transcribed Image Text:### Critical Values for Correlation Coefficient The table below provides the critical values for the correlation coefficient. These values are essential for determining the statistical significance of a correlation in hypothesis testing. The column labeled "n" represents the sample size, while the adjacent numbers indicate the critical correlation coefficients for that particular sample size. | n | Coefficient | n | Coefficient | n | Coefficient | n | Coefficient | |----|-------------|----|-------------|----|-------------|----|-------------| | 3 | 0.997 | 10 | 0.632 | 17 | 0.482 | 24 | 0.404 | | 4 | 0.950 | 11 | 0.602 | 18 | 0.468 | 25 | 0.396 | | 5 | 0.878 | 12 | 0.576 | 19 | 0.456 | 26 | 0.388 | | 6 | 0.811 | 13 | 0.553 | 20 | 0.444 | 27 | 0.381 | | 7 | 0.754 | 14 | 0.532 | 21 | 0.433 | 28 | 0.374 | | 8 | 0.707 | 15 | 0.514 | 22 | 0.423 | 29 | 0.367 | | 9 | 0.666 | 16 | 0.497 | 23 | 0.413 | 30 | 0.361 | #### Explanation: - **Sample Size (n):** This is the number of paired observations. - **Critical Value of Correlation Coefficient:** The smallest value for the correlation coefficient that can be considered statistically significant at a given significance level, typically 0.05. This table is utilized in statistical analysis to determine if the observed correlation in a sample is significantly different from zero at a certain significance level.
Expert Solution
Step 1

Given:

Sample size n = 7

The correlation coefficient r = -0.823

Formula Used:

If the amount of coefficient of correlation is greater than critical value, Then there is a linear relationship.

 

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