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since we are comparing more than 2 groups, we will use anova to test whether the data provide evidence that sat score is related to study strategy. one of the conditions that allows us to use anova safely is that of equal (population) standard deviations. can we assume that this condition is met in this case?

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Final answer:

In conducting a one-way ANOVA to compare SAT scores across study strategies, equal standard deviations among groups are required. The information suggests there are different standard deviations for the samples, hence, before proceeding, further testing for equal variance must be carried out to ensure the validity of the ANOVA.

Step-by-step explanation:

In the context of conducting an ANOVA test to compare SAT scores amongst different study strategies, it's crucial that the assumption of equal population standard deviations is met. When we say that there are equal standard deviations, we mean that the variability in SAT scores should be roughly the same across all groups being compared. This requirement is necessary because the one-way ANOVA relies on the assumption that the variances within each group are a fair representation of the variances across all groups (homoscedasticity).

From the information provided, it seems that there is an indication of different standard deviations for the samples, which implies that the populations may have differing variances. This would indeed violate the assumption necessary for a one-way ANOVA, which seeks to assess whether any observed differences among group means are greater than would be expected by chance if all group means were actually the same. Therefore, before proceeding with the ANOVA, it is advisable to perform an equal variance test (such as Levene's test or Bartlett's test) to verify whether the variances are statistically similar. If this assumption is not met, the results of the ANOVA might not be valid, and other statistical methods could be considered.

User Matansh
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Answer: To determine whether the condition of equal standard deviations is met in this case, we can perform a quick check by comparing the sample standard deviations of each group. If the sample standard deviations are roughly equal, then we can assume that the condition of equal standard deviations is met.

Alternatively, we can use Levene's test for equality of variances, which tests the null hypothesis that the population variances are equal across all groups. If the p-value of the test is greater than the significance level (usually 0.05), then we can assume that the condition of equal standard deviations is met.

Without the data or the sample standard deviations, it is not possible to determine whether the condition of equal standard deviations is met in this case.

Step-by-step explanation:

User Borbulon
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