Ho: there is no relationship between quality and shift
H1: there is a relationship between quality and shift
Chi-Square Test of independence | |||||||
Observed Frequencies | |||||||
Y | |||||||
0 | perfect | satisfactory | defective | Total | |||
shift 1 | 106 | 124 | 1 | 231 | |||
shift 2 | 67 | 85 | 2 | 154 | |||
Total | 173 | 209 | 3 | 385 | |||
Expected frequency of a cell = sum of row*sum of column / total sum | |||||||
Expected Frequencies | |||||||
perfect | satisfactory | defective | Total | ||||
shift 1 | 173*231/385=103.8 | 209*231/385=125.4 | 3*231/385=1.8 | 231 | |||
shift 2 | 173*154/385=69.2 | 209*154/385=83.6 | 3*154/385=1.2 | 154 | |||
Total | 173 | 209 | 3 | 385 | |||
(fo-fe)^2/fe | |||||||
shift 1 | 0.047 | 0.016 | 0.356 | ||||
shift 2 | 0.070 | 0.023 | 0.533 |
Chi-Square Test Statistic,χ² = Σ(fo-fe)^2/fe
= 1.0445
Level of Significance = 0.05
Number of Rows = 2
Number of Columns = 3
Degrees of Freedom=(#row - 1)(#column -1) = (2- 1 ) * ( 3-
1 ) = 2
Critical Value = 5.991
[ Excel function: =CHISQ.INV.RT(α,DF) ]
Decision: test statistic,X² < critical value , So, Do
not reject the null hypothesis
conclusion: there is no enough evidence to conclude that there is a relationship between quality and shift
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