The formula for the sum of squares due to treatments, SSTR, follows where n, is the number of observations for treatment j, x, is the sample mean for treatment j, and is the mean of all the observations in the data. SSTR = n(x₁ - x)² j=1 The given data are below. Treatment Treatment A B 33 29 29 45 44 44 Treatment с 32 37 36

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**Step 2**

Now that the hypotheses have been determined, a test statistic needs to be found. A partial ANOVA table will be used to organize values in calculating the test statistic. Recall the format of the ANOVA table, given below. The final Total row will not be used.

| Source of Variation | Sum of Squares | Degrees of Freedom | Mean Square | \( F \) | p-value |
|---------------------|----------------|--------------------|-------------|-------|---------|
| Treatments          | SSTR           | \( k - 1 \)        | \( \frac{\text{SSTR}}{k - 1} = \text{MSTR} \) | \( F = \frac{\text{MSTR}}{\text{MSE}} \) |        |
| Error               | SSE            | \( n_T - k \)      | \( \frac{\text{SSE}}{n_T - k} = \text{MSE} \) |       |         |
| Total               | SSTR + SSE = SST | \( (k - 1) + (n_T - k) = n_T - 1 \) |             |       |         |

The formula for the sum of squares due to treatments, SSTR, follows where \( n_j \) is the number of observations for treatment \( j \), \( \bar{x}_j \) is the sample mean for treatment \( j \), and \( \bar{x} \) is the mean of all the observations in the data.

\[
\text{SSTR} = \sum_{j=1}^{k} n_j (\bar{x}_j - \bar{x})^2
\]

The given data are below:

|              | Treatment A | Treatment B | Treatment C |
|--------------|-------------|-------------|-------------|
| Observations | 33          | 45          | 32          |
|              | 29          | 44          | 37          |
|              | 29          | 44          | 36          |
|              | 27          | 47          | 37          |
|              | 32          | 50          | 33          |
| Sample Mean  | 30.00       | 46.00       | 35.00       |
| Sample Variance | 6.00       | 6.50       | 5.50       |
Transcribed Image Text:**Step 2** Now that the hypotheses have been determined, a test statistic needs to be found. A partial ANOVA table will be used to organize values in calculating the test statistic. Recall the format of the ANOVA table, given below. The final Total row will not be used. | Source of Variation | Sum of Squares | Degrees of Freedom | Mean Square | \( F \) | p-value | |---------------------|----------------|--------------------|-------------|-------|---------| | Treatments | SSTR | \( k - 1 \) | \( \frac{\text{SSTR}}{k - 1} = \text{MSTR} \) | \( F = \frac{\text{MSTR}}{\text{MSE}} \) | | | Error | SSE | \( n_T - k \) | \( \frac{\text{SSE}}{n_T - k} = \text{MSE} \) | | | | Total | SSTR + SSE = SST | \( (k - 1) + (n_T - k) = n_T - 1 \) | | | | The formula for the sum of squares due to treatments, SSTR, follows where \( n_j \) is the number of observations for treatment \( j \), \( \bar{x}_j \) is the sample mean for treatment \( j \), and \( \bar{x} \) is the mean of all the observations in the data. \[ \text{SSTR} = \sum_{j=1}^{k} n_j (\bar{x}_j - \bar{x})^2 \] The given data are below: | | Treatment A | Treatment B | Treatment C | |--------------|-------------|-------------|-------------| | Observations | 33 | 45 | 32 | | | 29 | 44 | 37 | | | 29 | 44 | 36 | | | 27 | 47 | 37 | | | 32 | 50 | 33 | | Sample Mean | 30.00 | 46.00 | 35.00 | | Sample Variance | 6.00 | 6.50 | 5.50 |
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