Source of Variation Treatments Error Total ܓ =ܨ ܢܕ "ܨ ܐܐ Tܕ ܐܐ ܙ ܕܐ PPPPPs Ob The null hypothesis for this ANOVA problem is Select one O a Wi=p;=p;#we"wy=He Oc 60 135 P1 P2 P3 Pe Od P1 P2 Ps Consider the following partial ANOVA table: 3 lus 3.75
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- If difference scores begin to pile up away from a sample mean difference score of MD = 0, which of the following statements is true? The null hypothesis will likely fail to be rejected. The null hypothesis will likely be rejected. The sample size is large. The critical region is small.An experiment was conducted to compare the alcohol content of soy sauce on two different production lines. Production was monitored eight times a day. The data are shown here. Production line 1 0.38 0.37 0.39 0.41 0.38 0.39 0.40 0.39 Production line 2 0.48 0.39 0.42 0.52 0.40 0.48 0.52 0.52 Assume both populations are normal. It is suspected that production line 1 is not producing as consistently as production line 2 in terms of alcohol content. Perform a hypothesis test to compare the population standard deviation of these two types of production lines. What is the value of the test statistic?Below are pupil sizes from two samples: 8 men and 8 women (measured in millimeters). Test the hypothesis that thee is a difference in pupil sizes between males and females, using an alpha level of .01. Males Females 7.7 8.9 7.5 8.7 6.9 9.0 7.8 8.8 7.7 7.9 6.9 8.8 4.5 9.0 7.5 9.0 Explain what main effects and interaction effects are in a Two-Way ANOVA. How does the calculation of Fobt differ between an independent groups and repeated measures One-Way ANOVA? Which test is more powerful and why?
- Consider the following ANOVA summary table for this problem Source of variability SS df MS F Between 60 4 15 Within 1000 50 20 Total 1060 54 Based on the above ANOVA summary table and assuming α = .05, the researcher should.. . Select one: a. reject the H0 b. fail to reject the H0 c. be unable to make any decisions because there is insufficient information to reach a statistical decision. d. worry about a Type 1 errorOne of the advantages of a repeated-measures design is that it removes the individual differences from the error variance and increases the likelihood of rejecting the null hypothesis. The following data were obtained from a research study comparing three treatment conditions. Treatment 1 Treatment 2 Treatment 3 6 8 10 G=48∑?2 = 2945 5 5 1 2 3 0 1 2 T=12SS=26 T=16SS=30 T=20SS=38 1. Assume that the data are from an independent-measures study (like in Chapter 12 normal ANOVA) using three separate samples, each with n=4 participants, and use an independent-measures ANOVA with =.05 to test for significant differences among the three treatments. 2. Assume that the data are from a repeated-measures study using one sample of n=4 participants and use a repeated-measures ANOVA with =.05 to test for significant differences among the three treatments. 3. Compare your results from part A and part B.