State the null and alternative hypotheses. 2.Compute the test statistic. Document how SSTr and SSE were computed. Use 4 decimal places for the sample means, sample standard deviations and the grand mean and round your answers for SSTr and SSE to 2 decimal places. Use the values for SSTr and SSE to complete the following ANOVA table. Round each of your answers to 2 decimal places. (image of table) 3.Compute the p-value. Provide the name of the distribution and the parameters used to compute the p-value. Then enter your answer rounded to 4 decimal places. 4.Interpret the results of the significance test. Is this result statistically significant? Is this result important from a practical perspective?

MATLAB: An Introduction with Applications
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Chapter1: Starting With Matlab
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1. State the null and alternative hypotheses.

2.Compute the test statistic. Document how SSTr and SSE were computed. Use 4 decimal places for the sample means, sample standard deviations and the grand mean and round your answers for SSTr and SSE to 2 decimal places.

Use the values for SSTr and SSE to complete the following ANOVA table. Round each of your answers to 2 decimal places. (image of table)

3.Compute the p-value. Provide the name of the distribution and the parameters used to compute the p-value. Then enter your answer rounded to 4 decimal places.

4.Interpret the results of the significance test. Is this result statistically significant? Is this result important from a practical perspective?

The image displays an Analysis of Variance (ANOVA) table template used in statistical analysis. It consists of five main columns: Source, S.S. (Sum of Squares), df (degrees of freedom), M.S. (Mean Square), and F (F-ratio).

### Table Structure:

1. **Source**: 
   - Represents the different components in ANOVA.
   - Rows include:
     - Treatment
     - Error
     - Total

2. **S.S. (Sum of Squares)**: 
   - This column is reserved for the sum of squares for each source. It quantifies the variation for treatment and error.

3. **df (degrees of freedom)**:
   - This column indicates the degrees of freedom associated with each source.

4. **M.S. (Mean Square)**:
   - This column is for the mean square values, calculated by dividing the sum of squares by the corresponding degrees of freedom.

5. **F (F-ratio)**:
   - This column holds the F-ratio values, used to determine the statistical significance of the observed variance among the group means.

This table is commonly used in the context of hypothesis testing to analyze experimental data, particularly to compare the means among different groups and determine if any significant differences exist.
Transcribed Image Text:The image displays an Analysis of Variance (ANOVA) table template used in statistical analysis. It consists of five main columns: Source, S.S. (Sum of Squares), df (degrees of freedom), M.S. (Mean Square), and F (F-ratio). ### Table Structure: 1. **Source**: - Represents the different components in ANOVA. - Rows include: - Treatment - Error - Total 2. **S.S. (Sum of Squares)**: - This column is reserved for the sum of squares for each source. It quantifies the variation for treatment and error. 3. **df (degrees of freedom)**: - This column indicates the degrees of freedom associated with each source. 4. **M.S. (Mean Square)**: - This column is for the mean square values, calculated by dividing the sum of squares by the corresponding degrees of freedom. 5. **F (F-ratio)**: - This column holds the F-ratio values, used to determine the statistical significance of the observed variance among the group means. This table is commonly used in the context of hypothesis testing to analyze experimental data, particularly to compare the means among different groups and determine if any significant differences exist.
The table presents data across three categories: Control, CBT (Cognitive Behavioral Therapy), and Family. Each category contains a series of numerical values which likely represent outcomes or measurements from a study or experiment. Below is the transcribed data:

| Control | CBT  | Family |
|---------|------|--------|
| 1.1     | 0.5  | 12.1   |
| -1.2    | -7.3 | 11.4   |
| 0.4     | -3.5 | 3.5    |
| -1.4    | 14.3 | 10.8   |
| -4.4    | -1.2 | 12.9   |
| 12.9    | -11.7| -4.2   |
| 3.8     | -13.7| 0.9    |
| 17.4    | 10.2 | 8.9    |
| -7.3    | -6.2 | 2.3    |
| 2.4     | 6.3  | -4.3   |
| 13.1    | 1.4  | -2.9   |
| 7.9     | -7.4 | 12.9   |
| 0.4     | 7.7  | 14.5   |
| -5.2    | 2.4  | 7.6    |
| 20.7    | 11.1 | 3.8    |
| -8      | 1    | 6.6    |
| 1       | -1.9 | 10.7   |
| -3.2    | -10  |        |
| 2.3     | -4.3 |        |
| 0.7     | -7.5 |        |
| -2      | 1.8  |        |
| 0.9     | -0.6 |        |
| 1.2     | 2.6  |        |
| 10.7    | 5.2  |        |
| 2.1     | 16.7 |        |
| 2.1     |      |        |
| 5.1     | -11
Transcribed Image Text:The table presents data across three categories: Control, CBT (Cognitive Behavioral Therapy), and Family. Each category contains a series of numerical values which likely represent outcomes or measurements from a study or experiment. Below is the transcribed data: | Control | CBT | Family | |---------|------|--------| | 1.1 | 0.5 | 12.1 | | -1.2 | -7.3 | 11.4 | | 0.4 | -3.5 | 3.5 | | -1.4 | 14.3 | 10.8 | | -4.4 | -1.2 | 12.9 | | 12.9 | -11.7| -4.2 | | 3.8 | -13.7| 0.9 | | 17.4 | 10.2 | 8.9 | | -7.3 | -6.2 | 2.3 | | 2.4 | 6.3 | -4.3 | | 13.1 | 1.4 | -2.9 | | 7.9 | -7.4 | 12.9 | | 0.4 | 7.7 | 14.5 | | -5.2 | 2.4 | 7.6 | | 20.7 | 11.1 | 3.8 | | -8 | 1 | 6.6 | | 1 | -1.9 | 10.7 | | -3.2 | -10 | | | 2.3 | -4.3 | | | 0.7 | -7.5 | | | -2 | 1.8 | | | 0.9 | -0.6 | | | 1.2 | 2.6 | | | 10.7 | 5.2 | | | 2.1 | 16.7 | | | 2.1 | | | | 5.1 | -11
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