The following is an incomplete F-table summarizing the results of a study of the variance of life satisfaction scores among unemployed, retired, part-time, and full-time employees.
Source of Variation | SS | df | MS | F |
---|---|---|---|---|
Between groups | 21 | |||
Within groups (error) | 36 | |||
Total | 139 |
(a) Complete the F-table. (Round your values for mean squares and F to two decimal places.)
Source of Variation | SS | df | MS | F |
---|---|---|---|---|
Between groups | 3 | 21 | ||
Within groups (error) | 36 | |||
Total | 139 |
(b) Compute omega-squared
(ω2).
(Round your answer to two decimal places.)
ω2 =
Source of variation | SS | DF | MSE |
Between group | 7 | 3 | 21 |
Within group (error) | 132 | 36 | 3.67 |
Total | 139 | 39 |
Let
SSB = SS(between)
SSE= SS(error)
SST = SS(total)
SSB = MSB / df(between)
SSB = 21/3 =7
SST = SSB + SSE
139 = 7 + SSE
SSE = 139 - 7 = 132
MSE = SSE/ df(error) = 132/36 = 3.67
df(total) =df(between) + df(error)
df(total) = 3 +36 = 39
Omega squared : ω2
ω2 = 7 - (3*3.67) /(139 + 3.67)
ω2 =7-11.01 / 142.67
ω2 = -4.01 / 142.67
ω2 = - 0.03
Generally ω2 is lies in 0 to 1. So the negative size can be
appear & it can be considered as 0.
ω2 is a strength of association measure provides an estimate of the
amount of variance in the dependent measure that can be explained
by the independent measure.
Here omega is negative. Since a negative
variance has no meaning, negative values are always set to
zero.
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