Click the icon to view the table of results. a. State the multiple regression equation. ₁=+₁₁+x₂i (Round to two decimal places as needed.)

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### Table of Results

| Variable   | Coefficients | Standard Error | T Statistic | p-Value |
|------------|--------------|----------------|-------------|---------|
| Intercept  | 11.680464    | 7.132097       | 1.64        | 0.1048  |
| Revenue    | 0.6999226    | 0.321328       | 2.18        | 0.0319  |
| Efficiency | 0.8029396    | 0.077201       | 10.40       | <0.0001 |

#### Explanation:

This table presents a statistical analysis output. It includes:

- **Variable**: The name of the variable being analyzed.
- **Coefficients**: The estimated effect or contribution of each variable.
- **Standard Error**: Indicates the variability of the coefficient estimate.
- **T Statistic**: A measure used to evaluate the significance of the coefficient.
- **p-Value**: Shows the probability that the observed results could have occurred under the null hypothesis. Lower p-values suggest higher statistical significance.

#### Interpretation:

- **Intercept**: Has a coefficient of 11.680464, with a standard error of 7.132097. The t statistic is 1.64 with a p-value of 0.1048, indicating it is not statistically significant at common alpha levels (e.g., 0.05).

- **Revenue**: Shows a coefficient of 0.6999226, with a relatively larger standard error of 0.321328. It has a t statistic of 2.18 and a p-value of 0.0319, making it statistically significant at the 0.05 level.

- **Efficiency**: Displays a coefficient of 0.8029396, with a small standard error of 0.077201. It has a very high t statistic of 10.40 and a p-value of less than 0.0001, indicating a high level of statistical significance.
Transcribed Image Text:### Table of Results | Variable | Coefficients | Standard Error | T Statistic | p-Value | |------------|--------------|----------------|-------------|---------| | Intercept | 11.680464 | 7.132097 | 1.64 | 0.1048 | | Revenue | 0.6999226 | 0.321328 | 2.18 | 0.0319 | | Efficiency | 0.8029396 | 0.077201 | 10.40 | <0.0001 | #### Explanation: This table presents a statistical analysis output. It includes: - **Variable**: The name of the variable being analyzed. - **Coefficients**: The estimated effect or contribution of each variable. - **Standard Error**: Indicates the variability of the coefficient estimate. - **T Statistic**: A measure used to evaluate the significance of the coefficient. - **p-Value**: Shows the probability that the observed results could have occurred under the null hypothesis. Lower p-values suggest higher statistical significance. #### Interpretation: - **Intercept**: Has a coefficient of 11.680464, with a standard error of 7.132097. The t statistic is 1.64 with a p-value of 0.1048, indicating it is not statistically significant at common alpha levels (e.g., 0.05). - **Revenue**: Shows a coefficient of 0.6999226, with a relatively larger standard error of 0.321328. It has a t statistic of 2.18 and a p-value of 0.0319, making it statistically significant at the 0.05 level. - **Efficiency**: Displays a coefficient of 0.8029396, with a small standard error of 0.077201. It has a very high t statistic of 10.40 and a p-value of less than 0.0001, indicating a high level of statistical significance.
A nonprofit analyst is evaluating which variables to use for predicting nonprofit charitable commitment, representing how committed an organization is to its charitable purpose. The analysis involves two independent variables:

1. **Revenue (\(X_1\))**: Measured as total revenue in billions of dollars, this variable serves as an indicator of the size of the nonprofit.
2. **Efficiency (\(X_2\))**: This variable measures the percent of private donations remaining after fundraising expenses, serving as a measure of nonprofit fundraising efficiency.

The dependent variable is:

- **Commitment (Y)**: Measured as the percentage of total expenses allocated directly to charitable services.

Both variables \(X_2\) and \(Y\) are represented as percentages. Data were collected from a random sample of 97 nonprofit organizations. The results are available in a table.

**Task:**

a. State the multiple regression equation.

    \(\hat{Y}_i = \boxed{ } + (\boxed{ }) X_{1i} + (\boxed{ }) X_{2i}\)

    (Round to two decimal places as needed.)
Transcribed Image Text:A nonprofit analyst is evaluating which variables to use for predicting nonprofit charitable commitment, representing how committed an organization is to its charitable purpose. The analysis involves two independent variables: 1. **Revenue (\(X_1\))**: Measured as total revenue in billions of dollars, this variable serves as an indicator of the size of the nonprofit. 2. **Efficiency (\(X_2\))**: This variable measures the percent of private donations remaining after fundraising expenses, serving as a measure of nonprofit fundraising efficiency. The dependent variable is: - **Commitment (Y)**: Measured as the percentage of total expenses allocated directly to charitable services. Both variables \(X_2\) and \(Y\) are represented as percentages. Data were collected from a random sample of 97 nonprofit organizations. The results are available in a table. **Task:** a. State the multiple regression equation. \(\hat{Y}_i = \boxed{ } + (\boxed{ }) X_{1i} + (\boxed{ }) X_{2i}\) (Round to two decimal places as needed.)
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