Question

The following table summarizes the results of a study on SAT prep courses, comparing SAT scores of students in a private preparation class, a high school preparation class, and no preparation class. Use the information from the table to answer the remaining questions Number of Sum of Treatment Private prep class High school prep class No prep class Observations Sample Mean Squares (SS) 690 680 640 60 60 60 265,500.00 276,120.00 302,670.00 Using the data provided, complete the partial ANOVA summary table that follows. (Hint: T, the treatment total, can be calculated as the sample mean times the number of observations. G, the grand total, can be calculated from the values of T once you have calculated them.) Source Between treatments Within treatments Sum of Squares (Ss) df Mean Square (MS) In some ANOVA summary tables you will see, the labels in the first (source) column are Treatment, Error, and Total Which of the following reasons best explains why the within-treatments sum of squares is sometimes referred to as the "error sum of squares"? The within-treatments sum of squares measures treatment effects as well as random, unsystematic differences within each of the samples assigned to each of the treatments. These differences represent all of the variations that could occur in a study; therefore, they are sometimes referred to as "error." O Differences among members of the sample who received the same treatment occur because some treatments are more effective than others, so it would be an error to receive the less superior treatments The within-treatments sum of squares measures random, unsystematic differences within each of the samples assigned to each of the treatments. These differences are not due to treatment effects because everyone within each sample received the same treatment; therefore, the differences are sometimes referred to as error Differences among members of the sample who received the same treatment occur when the researchen makes an error, and thus these differences are sometimes referred to as "error." product,ratio,s um,or In ANOVA, the F test statistic is the diffrence variance. The value of the F test statistic is of the between-treatments variance and the within-treatments 8.11,0.11,0.14,or 2.20 close to 1, close When the null hypothesis is true, the F test statistic is too, or large When the null hypothesis is false, the F test statistic is most likely close to 1, close in general, you should reject the null hypothesis for values ot the test statistic close to u dose or large to 0, or large large values of the F test statistic values of the F test statistic close to 1

Answer 1

This problem is the ANOVA of one way classification. We have to derive the sum of squares with the help of basic summary values.

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