You wish to determine if there is a linear correlation between the two variables at a significance level of a = 0.05. You have the following bivariate data set. y 77.4 61.2 29.4 72.3 36.7 71.8 22.8 71.2 19.5 55.6

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**Transcription for Educational Website:**

---

**What is the p-value for this correlation coefficient?**

p-value = _______ (Round to four decimal places.)

**Critical Values =** \( t_{(0.05/2,3)} = \) _______

---

**Instruction:**

Shade the sampling distribution curve with the correct critical value(s) and shade the critical regions. The arrows can only be dragged to t-scores that are accurate to one place after the decimal point (these values correspond to the tick marks on the horizontal axis). Select from the dropdown menu to shade to the left, to the right, between, or left and right of the t-score(s).

**Shade:** Left of a value ▼

*Click and drag the arrows to adjust the values.*

---

**Graph Explanation:**

The graph displayed is a normal distribution curve, representing the sampling distribution of the t-scores. It is marked along the horizontal axis with tick marks at integer and half-integer values ranging from -4 to 4. An arrow is currently positioned at -1.5 with a shaded region extending to the left, highlighting the critical area under the curve.

---

**Data Input:**

- **Decision:** Select an answer ▼
- **Conclusion:** Select an answer ▼ the claim that there is a linear correlation between the two variables.
Transcribed Image Text:**Transcription for Educational Website:** --- **What is the p-value for this correlation coefficient?** p-value = _______ (Round to four decimal places.) **Critical Values =** \( t_{(0.05/2,3)} = \) _______ --- **Instruction:** Shade the sampling distribution curve with the correct critical value(s) and shade the critical regions. The arrows can only be dragged to t-scores that are accurate to one place after the decimal point (these values correspond to the tick marks on the horizontal axis). Select from the dropdown menu to shade to the left, to the right, between, or left and right of the t-score(s). **Shade:** Left of a value ▼ *Click and drag the arrows to adjust the values.* --- **Graph Explanation:** The graph displayed is a normal distribution curve, representing the sampling distribution of the t-scores. It is marked along the horizontal axis with tick marks at integer and half-integer values ranging from -4 to 4. An arrow is currently positioned at -1.5 with a shaded region extending to the left, highlighting the critical area under the curve. --- **Data Input:** - **Decision:** Select an answer ▼ - **Conclusion:** Select an answer ▼ the claim that there is a linear correlation between the two variables.
# Analyzing Correlation in Bivariate Data

You wish to determine if there is a linear correlation between the two variables at a significance level of \( \alpha = 0.05 \). You have the following bivariate data set:

| X   | Y   |
|-----|-----|
| 61.2 | 77.4 |
| 29.4 | 72.3 |
| 36.7 | 71.8 |
| 22.8 | 71.2 |
| 19.5 | 55.6 |

### Hypothesis Testing
- \( H_0: \) \( \rho \) = 0 
- \( H_a: \) \( \rho \) ≠ 0

### Original Claim
- \( H_1 \)
- \( H_0 \)

**Note**: In your calculations, except for the p-value and the graph, round both \( r \) and \( t \) to 3 decimal places in ALL calculations.

#### Correlation Coefficient
What is the correlation coefficient for this data set?
- \( r = \) [Input Field]

#### Calculating the t-Score
To find the p-value for a correlation coefficient, you need to convert to a t-score:

\[ 
t = \frac{r \sqrt{n - 2}}{\sqrt{1 - r^2}} 
\]

This t-score is from a t-distribution with \( n-2 \) degrees of freedom.

- \( t = \) [Input Field]
Transcribed Image Text:# Analyzing Correlation in Bivariate Data You wish to determine if there is a linear correlation between the two variables at a significance level of \( \alpha = 0.05 \). You have the following bivariate data set: | X | Y | |-----|-----| | 61.2 | 77.4 | | 29.4 | 72.3 | | 36.7 | 71.8 | | 22.8 | 71.2 | | 19.5 | 55.6 | ### Hypothesis Testing - \( H_0: \) \( \rho \) = 0 - \( H_a: \) \( \rho \) ≠ 0 ### Original Claim - \( H_1 \) - \( H_0 \) **Note**: In your calculations, except for the p-value and the graph, round both \( r \) and \( t \) to 3 decimal places in ALL calculations. #### Correlation Coefficient What is the correlation coefficient for this data set? - \( r = \) [Input Field] #### Calculating the t-Score To find the p-value for a correlation coefficient, you need to convert to a t-score: \[ t = \frac{r \sqrt{n - 2}}{\sqrt{1 - r^2}} \] This t-score is from a t-distribution with \( n-2 \) degrees of freedom. - \( t = \) [Input Field]
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