When any two treatments are involved, ANOVA and the Students t test (Chapter 11)
ID: 3261903 • Letter: W
Question
When any two treatments are involved, ANOVA and the Students t test (Chapter 11) result in the same conclusions. Also, for computed test statistics, t^2 - F. To demonstrate this relationship, use the following example. Fourteen randomly selected students enrolled in a history course were divided into two groups. The following is a list of the number correct for each or the two groups. Complete the ANOVA table. (Round your ss, MS, and F values to 2 decimal places and p value to 4 decimal places.) Use a alpha - 0.05 level of significance. (Round your answer to 2 decimal places.) The critical value of F b. Using the t test from Chapter 11, compute t. (Negative amount should be Indicated by a minus sign. Round your answer to 3 decimal places.) t c. There is any difference in the mean test scores. H0. There is in the mean scores between lecture and internet based formats.Explanation / Answer
One-way ANOVA: responce versus factors
Method
Null hypothesis All means are equal
Alternative hypothesis At least one mean is different
Significance level = 0.05
Equal variances were assumed for the analysis.
Factor Information
Factor Levels Values
factors 2 1, 2
Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
factors 1 64.38 64.38 2.16 0.167
Error 12 357.33 29.78
Total 13 421.71
factors N Mean StDev 95% CI
1 6 36.67 4.80 (31.81, 41.52)
2 8 41.00 5.88 (36.80, 45.20)
Pooled StDev = 5.45690
t test = (36.67-41) / 5.4569*sqrt((1/6)+(1/8))
t test = -4.33 / 2.9471
t test = -1.4693
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