### Analysis of Independent-Measures Experiment DataThe table below presents raw data from an independent-measures experiment comparing three different treatment conditions:#### Data Table| | **Treatment 1** | **Treatment 2** | **Treatment 3** ||----------------|-----------------|-----------------|-----------------|| **Observation 1** | 0 | 1 | 3 || **Observation 2** | 1 | 4 | 3 || **Observation 3** | 0 | 1 | 4 || **Observation 4** | 3 | 2 | 5 || **Mean (X̄)** | 1 | 2 | 3.75 |#### SummaryTo evaluate the effect of the independent variable, researchers conducted an independent-measures one-way Analysis of Variance (ANOVA). They computed the sum of squares between groups to be 15.5 and the sum of squares within groups to be 14.75.#### QuestionWhich of the following values is the critical value in the analysis (α = 0.05)?1. 3.982. 19.383. 2.904. 4.26By understanding the statistical analysis process, this educational resource aims to help students and researchers in interpreting experimental data accurately.---For those seeking further details on how to perform an ANOVA calculation and identify critical values, numerous statistical textbooks and online resources can provide step-by-step guidance. Remember, the critical value in ANOVA can be found using F-distribution tables or statistical software, considering the degrees of freedom between and within groups, and the level of significance (α).

The number of groups is k=3.The number of observations in each group is 4.The total number of…

Answered: Raw data in the table below come from…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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The following data represent the results from an independent-measures study comparing itwo treatment conditions. Test at 0.05 level of significance to determine whether there is a significant mean difference between the two treatments. Use 4 decimal places.Treatment I Treatment II 8 2 7 3 6 3 5 5 9 2STATISTICS = _____COMPUTED VALUE = _____TABULAR VALUE = _____CONCLUSION = _____
The data below are from a study comparing three different treatment conditions: Treatment 1 Treatment 2 Treatment 3 0 1 6 1 4 5 0 1 6 3 2 3 T = 4 T = 8 T = 20 SS = 6 SS = 6 SS = 6 N = 12 G = 32 ƩX2= 138 Conduct a single-factor independent-measures ANOVA to test the hypothesis that there are significant differences in the mean scores among the three treatment conditions. Use α = .01. a. The alternative hypothesis is
A taxi cab company takes a random sample of 50 of its taxis and notes their miles per gallon (mpg) on a test run. The computer output is shown below. Mean St Dev Min Q1 Q2 Q3 Max 19.78 3.09 13.30 17.80 20.00 21.83 26.00 50% of the taxis have MPG lower than what value? Group of answer choices A. 20 MPG B. (21.83 - 17.80) MPG C. 19.78 MPG D. (26-13.30)/2 MPG
The following data summarize the results from an independent-measures study comparing three treatment conditions. Treatment I II III N = 12 3 5 6 G = 60 5 5 10 ∑X2 = 392 3 1 10 1 5 6 x̅1 = 3 x̅2 = 4 x̅3 = 8 T1 = 12 T2 = 16 T3 =32…
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?
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Three brands of reducing pill were tried on a sample of 8 female adults. The data are given on the following table in terms of weight loss in pounds. Reducing Pll Used B Respondent A 4.5 3.2 3.0 2 4.1 3.0 2.8 3 3.6 38 3.2 4 53 3.9 3.6 4.8 4.2 3.5 27 3.1 3.5 43 4.0 29 3.8 3.3 36 Test the bypothesis that there is no signilicant difference in the average weight loss in pounds among the three groups of respondents using the three brands of reducing pills at 0.01 level
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The following data were obtained an independent-measures research study comparing three treatment conditions. Use an ANOVA with α = 0.05 to determine whether there are significant mean differences among the treatments. TREATMENT I II III 2 5 7 N = 14 5 2 3 G = 42 0 1 6 ∑X^2 = 182 1 2 4 2 2 T 12 10 20 SS 14 9 10
Suppose we want to compare scores (which can take on any value within a specified range) at baseline and at follow-up for a given sample. Using the data in the table below, compute a 95% CI for the mean difference in scores. Subject ID Baseline Follow-Up 1 13 6 2 10 8 3 9 11 4 12 11 5 8 5

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