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I’m interested in the effect of types of feedback on the number of hours basketball players spend doing exercises. I hypothesise that players who receive praise as feedback will spend significantly longer hours doing exercises than the no feedback group, and players who receive criticism will spend significantly fewer hours doing exercises than the no feedback group. After I’ve obtained a significant F-value from my one-way ANOVA omnibus test, what will be the most appropriate option to conduct my secondary analysis?Question 6Answera.Use the “pwmean” command to run post hoc comparisonsb.Use the “pwmean” command to run planned comparisons, specifically, set up contrasts to compare “praise vs. nothing” and “criticism vs. nothing”c.Use the “contrast” command to run post hoc comparisonsd.Use the “contrast” command to run planned comparisons, specifically, set up contrasts to compare “praise vs. nothing” and “criticism vs. nothing”e.Nothing, because we can get all the information from the omnibus F summary table

Question

I’m interested in the effect of types of feedback on the number of hours basketball players spend doing exercises. I hypothesise that players who receive praise as feedback will spend significantly longer hours doing exercises than the no feedback group, and players who receive criticism will spend significantly fewer hours doing exercises than the no feedback group. After I’ve obtained a significant F-value from my one-way ANOVA omnibus test, what will be the most appropriate option to conduct my secondary analysis?Question 6Answera.Use the “pwmean” command to run post hoc comparisonsb.Use the “pwmean” command to run planned comparisons, specifically, set up contrasts to compare “praise vs. nothing” and “criticism vs. nothing”c.Use the “contrast” command to run post hoc comparisonsd.Use the “contrast” command to run planned comparisons, specifically, set up contrasts to compare “praise vs. nothing” and “criticism vs. nothing”e.Nothing, because we can get all the information from the omnibus F summary table

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Solution

The most appropriate option for conducting your secondary analysis after obtaining a significant F-value from your one-way ANOVA omnibus test would be option d. Use the “contrast” command to run planned comparisons, specifically, set up contrasts to compare “praise vs. nothing” and “criticism vs. nothing”. This is because you have specific hypotheses about the direction of the differences between groups.

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Similar Questions

conducted planned contrasts using the “contrast {feedback 1 0 -1} {feedback 1 -1 0}, effects mcompare(bon)” command after I obtained a significant omnibus F-test result using “anova exercisehrs feedback”. Based on the outputs given by the first contrast command, choose the correct interpretation of the results.The praise group spent Answer 1 Question 1 Answer 2 Question 1 hours exercising than the nothing group.The praise group spent Answer 3 Question 1 Answer 4 Question 1 hours exercising than the criticism group.

I obtained a significant F-value from the one-way ANOVA model “anova exercisehrs feedback”. I then conducted pairwise comparisons on all groups to detect the differences between groups. Comparing the testing results using Tukey’s test and Scheffé’s test, we can see that:Question 3Answera.The results of Tukey’s test and Scheffé’s test agreed with each otherb.Tukey’s test results showed that the praise group differed significantly from the other two groups on the “exercisehrs”, while Scheffé’s test results only showed a significant difference between the nothing and praise groupsc.Scheffé’s test results showed that the praise group differs significantly from the other two groups on the “exercisehrs”, while Tukey’s test results only showed a significant difference between the nothing and praise groupsd.Both test results showed a significant difference between the nothing and criticism groups

Post-hoc analyses are important for:Question 2Answera.carrying out further analysis specifically on the means that showed the greatest difference when reporting the descriptive resultsb.calculating the effect size of each factorc.Double-checking that the ANOVA result was significant and not due to a type 1 errord.testing which pairs of conditions are significantly different after the ANOVA has been carried out

I’ve obtained a significant F-value from the one-way ANOVA model “anova exercisehrs feedback”. Next, I want to compare if the criticism group differs from the praise group in the number of hours exercising per day; what will be the best way to set up my contrast?Question 7Answera.Assign contrast coefficients as follows: praise (1), criticism (-1), nothing (0)b.Assign contrast coefficients as follows: praise (-1), criticism (-1), nothing (0)c.Assign contrast coefficients as follows: praise (2), criticism (2), nothing (0)d.Assign contrast coefficients as follows: praise (.5), criticism (.5), nothing (1)e.Assign contrast coefficients as follows: praise (-1), criticism (-1), nothing (2)Clear my choice

A study is being carried out on the effects of divided attention on driving performance. It involves testing participants on their reaction times to road hazards in a driving simulator. On two-thirds of the trials when a road hazard appears, the participant is already engaged in a secondary task of responding to questions. For a third of trials these are easy simple mental arithmetic questions and in the other third of trials, they are more demanding problem-solving questions . The researchers wish to compare participants' reaction times to spotting the hazard whilst varying the secondary task.What type of ANOVA design will their data analysis use?Question 11Answera.An independent sample mixed model ANOVAb.A repeated-measures one-way ANOVAc.A two-way repeated-measures one way ANOVAd.A 3-way factorial independent sample ANOVA

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