In an independent measures ANOVA, when means greater than the differences betwee

Question

In an independent measures ANOVA, when means greater than the differences between treatment means are greater than the difference among the individuals within each treatment, the F-ratio will be low. Although the original data for a repeated-measures t-test consist of two scores for each participant, the calculation of the mean and variance are done with only-one score for each participant. If all of the participant in a repeated-measures study show roughly the same difference between treatments, then the data are likely to produce a significant value for the t- statistic. If an analysis of variance produces a value of F = 1.00, then all of the samples have exactly the same mean. A chisquare test should not be used if any expected frequency is less than five. In a chi square goodness of fit test, a large value for chi-square indicates a good between the sample data and the null hypothesis. When X and Y have a correlation coefficient of zero, your line of best fit will be horizontal line drawn at the mean of Y. A repeated-measures ANOVA will have higher power than an independent- ANOVA if the treatments have a consistent effect on participants. The value obtained for the sum of products, SP, determines the sign (+/-) for correlation The value for a correlation can never be greater than +1.00. If other factors are held constant, a larger numerical value for the correlation will result in a smaller standard error of estimate. For any non-zero correlation, the regression line will provide a better average, of Y values than will the mean of Y. FREE RESPONSE (For all problems involving computation, you must show partial credit) Describe (don't just name) one advantage and one disadvantage associated with design as opposed to an independent-measures design.

Explanation / Answer

1:

The F test is variance between groups divided by variance within group. So in the given case F ratio will be high.

Answer : fasle

2:

In repeated measure t-test we need both scores to calculate difference and standard deviation of difference.

Answer: false

3:

If the difference is roughly same , the SD of difference will be low. In that case test statistics will be high. That is chances of rejecting the null hypothesis will increase.

Answer: true

4:

If F ratio is 1, it means that variances between groups is approximately same as variance within groups.

Answer: false

5:

True

6:

False

7:

True

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