Before performing a t-test to determine if the two groups are different, researchers must first ascertain if the variance in the two groups is the same using an F test.
Indicate whether the hypothesis below is the null or alternate hypothesis for the F test.
The variance in group A is not equal to the variance in group B
Calculate the F statistic for this data set and report it in the box below, rounded to two decimal places.
Use the formula =(1-(f.dist(F, df1,df2,true) in Excel to calculate the P value for the F statistic. Report the P value, rounded to 3 decimal places, in the box below. Do not use the rounded value for F when calculating the P value. Use the F value in the spreadsheet that has not been rounded.
Based on this p value, would you recommend using a Student's t test or a Welch's t test to determine if the two treatment groups have different means? Enter either Student's or Welch's in the box below.
Here is the data:
A | B |
42 | 48 |
8 | 131 |
27 | 24 |
40 | 79 |
9 | 91 |
67 | 143 |
53 | 27 |
35 | 86 |
73 | 54 |
80 | 12 |
35 | 72 |
38 | 115 |
38 | 31 |
53 | 53 |
46 | 125 |
61 | 109 |
47 | 99 |
6 | 25 |
28 | 130 |
43 | 104 |
THE HYPOTHESIS HERE IS ALETRNATE HYPOTHESIS : VARIANCE OF GROUP A IS NOT EQUAL TO VARIANCE OF GROUP B.
F-Test Two-Sample for Variances | ||
A | B | |
Mean | 41.45 | 77.9 |
Variance | 408.6815789 | 1718.726316 |
Observations | 20 | 20 |
df | 19 | 19 |
F | 0.23778165 | |
P(F<=f) one-tail | 0.001479554 | |
F Critical one-tail | 0.461201089 |
NULL HYPOTHESIS IS: TWO SAMPLKE VARIANCES ARE EQUAL
since calculated value of F(0.23778165) is is less than critical value of F(0.46120),so we accept the null hypothesis .i.e. their is no significant difference between the population variances.
2)= I suggest students t test if we are testing difference between two population means
t-Test: Two-Sample Assuming Equal Variances | ||
A | B | |
Mean | 41.45 | 77.9 |
Variance | 408.6815789 | 1718.726316 |
Observations | 20 | 20 |
Pooled Variance | 1063.703947 | |
Hypothesized Mean Difference | 0 | |
df | 38 | |
t Stat | -3.53416765 | |
P(T<=t) one-tail | 0.000546898 | |
t Critical one-tail | 1.68595446 | |
P(T<=t) two-tail | 0.001093796 | |
t Critical two-tail | 2.024394164 |
since calculated value of t is less than critical value of t for both one tail and two tail so we accept the null hypothesis i.e. their is no significant difference between means of two groups
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trained workers have higher earnings it would indicate that the
training is effective.[1]In terms of statistics, we will do a
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