Statistically significant results from ANOVA tell you which groups' means differ from each other.
a. true
b. false
option B: false
since Statistically significant results from ANOVA only tells us that at least one pair of mean group differ from each other but does not indicate which groups means differs
Statistically significant results from ANOVA tell you which groups' means differ from each other. a. true...
After observing statistically significant ANOVA results, Bonferroni-corrected inferences to determine which groups differ from each other require the following steps (select all that apply): o Select one or more: a. Compute the type I error rate allowable for each pairwise comparison in order to insure that the type I error rate across all comparisons does not exceed some pre-specified level b. Determine that the difference between a specific pair of groups is statistically significant if the t-test p-value is less...
If the ANOVA test is significant, what does that tell us? It indicates which means differ significantly from each other. It indicates that all means are the same. It indicates that there is a difference somewhere between at least two of the groups being compared. It indicates that the null hypothesis is true.
f the results of an “F-test” are statistically significant, that means for the variable being measured, the variation in one of the populations is greater than the variation in the other population. True False
I understand that one way ANOVA tells me that at least two groups are different from each other, however it doesn't tell me which groups are different. If the results of my ANOVA were to return a significant f-statistic, how do I determine which ad hoc test I need to run to tell me exactly which groups have a difference in means?
There is no statistically significant difference between the sample means of two groups Group of answer choices A. False Hypothesis B. Research Hypothesis C.Null Hypothesis D.True Hypothesis
Which of the following statements is true about the ANOVA? Group of answer choices An ANOVA indicates if any significant difference exists and specifies which two groups were statistically significant. An ANOVA indicates no significant difference between two groups that are statistically significant. An ANOVA indicates no significant difference between three groups that are not statistically significant. An ANOVA indicates if any significant difference exists but does not specify which two groups were statistically significant.
Which results are statistically significant? Explain how you arrived at this decision. Use the ANOVA Summary Table to answer the question that follow: 1 Source Factor A Factor B AXB Error Total Sum of Squares df 2.38 72.90 2 204.90 2 369.14 36 649.32 41 Mean Squar 2.38 36.45 102.45 10.25 What values form the numerator and denominator for the F-ratio (F-test) for each statistical effect?
The results of a study examining the effectiveness of two instructional strategies indicated a statistically significant difference between the means of the two treatment groups on an achievement test. Which of the following is a reasonable conclusion? a. We can be 95% confident one instructional strategy is better than the other. b. The difference between the two instructional strategies is meaningful. c. It is likely one instructional strategy is more effective. d. Both instructional strategies are equally effective.
a) A result is statistically significant if it is unlikely to occur by random chance alone. true or false b) If a result is NOT statistically significant, that means the chance model must be true. true or false c) there are always two possible explanations for the statistics obtained from a sample. Select the two possible explanations below. Generalizability Something is going on Random chance Sampling bias d) what does the researcher's question, or what the researcher thinks is true, determine?...
In ANOVA, variability between groups reflects _________, whereas variability within groups reflects __________ . total variance; error variance error variance ; total variance random error; a true effect (if one exists) both a true effect (if one exists) and random error; only random error just a true effect (if one exists); random error Rejecting the null hypothesis with the overall or omnibus One-way Analysis of Variance indicates that the: mean of one sample differs significantly from the mean of at...