The following data represent the results from an independent-measures study comparing two treatmentconditions. Both tables contain the same data, but are formatted differently.TreatmentOneOneOneOneOneOneTwoTwoTwoTwoTwoTwoTreatment TreatmentOneTwo6.58.27.165.64.6Response6.58.27.165.64.63.322.52.14.54.6F* test statistic:p-value:Conduct ANOVA with a = 0.05 for this data and calculate the F. test statistic and p-value. Round youranswer to three decimal places. Assume all population and ANOVA requirements are met.3.322.52.14.54.6t* test statistic:p-value:Now, conduct a t-test with a = 0.05 on the same data and calculate the t* test statistic and p-value.Round your answer to three decimal places.Observing the p-values, was there a difference in the result of the hypothesis test?O Yes, the p-values are different enough to change the outcome of the test.No, the p-values aren't that far off where it would change the outcome of the test.

Given level of significance is 0.05. We have to construct an ANOVA and t test with the level of…

Answered: The following data represent the…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The following data represent the results from an independent-measures study comparing two treatment conditions. Treatment Treatment One Two 5.5 4.4 6.7 4.2 6.1 5.3 6.7 5.8 6.5 Using SPSS, run the independent-measures single-factor ANOVA for this data: F-ratio: p-value: Now, run the independent-measures t test on the same data: t-statistic: p-value: What do you observe about the p-values? What is the relationship between the F-ratio and the t-statistic? > Next Question hp
Given the data below, what is the calculated test statistic? Placebo Medication 1 Medication 2 3 4 9 1 3 7 3 5 8 2 5 11 4 4 9 3 SS1 = 5.33 SS2 = 2.8 SS3 = 8.8 T1 = 16 T2 = 21 T3 = 44 n1 = 6 n2 = 5 n3 = 5 ∑X2 = 53 Do you reject the null? Yes No Was there a treatment effect for type of medication on number of anti-anxiety symptoms? Yes No
The following data represent the results from an independent-measures study comparing two treatment conditions. Treatment Treatment One Two 5.5 4.4 6.7 4.2 6.1 5.3 6.7 5.8 6.5 Using SPSS, run the independent-measures single-factor ANOVA for this data: F-ratio: p-value: Now, run the independent-measures t test on the same data: t-statistic: p-value: What do you observe about the p-values? What is the relationship between the F-ratio and the t-statistic? > Next Question M
Investigation of anti-body levels in a group of 22 patients before and after injection of an immunoglobulin produced the datasets provided: patient pre post 1 3.7 3.7 2 4.6 4.4 3 4.9 3.8 4 4.8 4.1 5 4.1 4.8 6 3.9 3.8 7 4.1 5.8 8 4.5 4.8 9 5.2 4.3 10 3.6 4.5 11 4.1 4.5 12 3.6 5.8 13 3 5.1 14 4.8 6.1 15 4.6 3.3 16 3.6 5.5 17 3.6 4.9 18 3.2 5.7 19 4.7 3.3 20 3.3 6.1 (a) Write a null and alternate hypothesis set to test if there is evidence for post-injection anti-bodylevels to be greater than pre-injection levels.(b) Test your hypothesis using the appropriate hypothesis test and significance level.(c) Compute a 99% confidence interval for the difference between pre and post-injection antibody levels.
treatment conditions. a. Treatment 1 0 0 0 3 0 0 T=3 SS = 7.5 Treatment 2 2 3 1 3 2 1 T = 12 SS=4 Treatment 3 4 2 4 3 4 4 G=36 SStotal = 42 T = 21 SS = 3.5 Use an analysis of variance with a = .05 to determine whether these data indicate any significant mean differences among the treatments. Please organize all of your work on a source table E C
The following data are from an independent-measures experiment comparing two treatment conditions: Treatment 1 Treatment 2 6 19 13 9 8 18 4 10 13 12 4 14 11 19 5 11 Which variables are described in this scenario and what are their scales of measurement? Which test should you use?
The following data represent the results from an independent-measures study comparing two treatment conditions. Treatment Response One 6.8 One 5.4 One 8.5 One 6.8 One 7.5 One 5.3 One 7.1 One 7.3 Two 3.6 Two 2.3 Two 3 Two 4.2 Two 1.9 Two 1.3 Two Two Treatment Treatment One Two 6.8 5.4 8.5 6.8 7.5 5.3 7.1 7.3 3.2 4.9 F-ratio: p-value: 0.000 Conduct ANOVA with a = 0.05 for this data and calculate the F-ratio and p-value. Round your answer to three decimal places. Assume all population and ANOVA requirements are met. 3.6 2.3 3 4.2 1.9 1.3 3.2 4.9 t-statistic: p-value: 0.000 0⁰ Now, conduct a t-test with a = 0.05 on the same data and calculate the t-statisitc and p-value. Round your answer to three decimal places. Observing the p-values, was there a difference in the result of the hypothesis test? No, the p-values aren't that far off where it would change the outcome of the test. O Yes, the p-values are different enough to change the outcome of the test.
The age of first marriage for women who responded to a survey by the CDC between 2006 and 2010 is used here. The women who first married in their twenties were randomly divided into three groups: A, B, and C. The ANOVA output is supplied below: Count NAS (Missings) 3773 group Count A 1288 B 1246 C 1239 Frequency Source DF 2 group Residual 3770 28 26 24 Response Variable (age) Summary Mean 22 20 T 0 Group Variable Summary NAS Mean (Missings) 23.73787 A 0 23.76941 0 23.77929 0 23.66344 ANOVA Table: age-group Sum of Squares 10.283 26969 Mean Square Std. Dev. Std. Dev. 2.674442 B F Value Pr>F MSG 0.71875 0.48743 MSE Age of First Marriage in 20's 2.728097 2.664101 2.628699 C
At the .05 significance level, does the data below show significant correlation? x y 3 12.87 4 13.66 5 17.95 6 23.44 7 15.93 8 13.62 9 27.91
5. Effect size for independent-measures t test - Cohen's d and r squared Tobacco companies have actively attempted to remake their public image by launching a youth smoking prevention advertisement campaign. Melanie Wakefield (a professor of applied psychology and researcher at the Center for Behavioral Research in Cancer in Victoria, Australia) and her colleagues conducted a study to assess the relation between exposure to tobacco companies' youth smoking prevention advertising and youth smoking-related beliefs, intentions, and behaviors. You use Professor Wakefield's research to design an experiment with two groups of middle school students from Morocco. You show the tobacco company's youth smoking prevention ads to one of the groups of students every day for a week at the beginning of their math class. After the week, you assess the groups on the degree to which the students approve/disapprove of adults smoking, using a 5-point Likert scale. You do not have a prediction about the…
Think about doing an Independent-Measures ANOVA, Step 3. If the data are as follows, find the SS-between. GROUP 1 GROUP 2 GROUP 3 1 3 5 3 2 7 2 4 6 Group of answer choices SS-between = 6.00 SS-between = 13.00 SS-between = 26.00 SS-between = 42.00
Identify the statistical procedures that are appropriate for the data. Childhood participation in sports, cultural groups, and youth groups appears to be related to improved self-esteem for adolescents (McGee, Williams, Howden-Chapman, Martin & Kawachi, 2006) in a representative study, a researcher compares scores on a standardized self-esteem questionnaire for a sample of n = 100 adolescents with a history of group participation and a separate sample of n = 100 who have no history of group participation.

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