Are all employees equally proven to having accidents? To investigate this hypothesis, Parry (1985) looked at a light manufacturing plant and classified the accidents by type and by age of the employee.
AgeAccident (sprain)Accident (burn)Accident (cut) Under 25917525 and over611312
Whole problem
It is needed to test, whether the all employees equally prone to having accidents.
The null and alternative hypotheses for the test are:
H0: Accident type seem to be independent of age.
H1: Accident type does not seem to be independent of age.
The expected frequency formula for a particular cell:
Expected frequency "= \\frac{Row \\; total \\times Column \\; total}{Overall \\; frequency}"
Consider Oi is the observed frequency for ith cell and Ei is the expected frequency for ith cell. There are total 2 rows (r) and 3 columns (c).
The chi-square test:
"\u03c7^2 = \\sum \\frac{(O_i -E_i)^2}{E_i}"
Degree of freedom (r-1)(c-1)
"\u03c7^2 = 20.78 \\\\\n\ndf = (2-1)(3-1)=2"
Consider that the level of significance is α = 0.05.
Using the Excel formula =CHISQ.DIST.RT(20.78,2) the P-value is approximately 0.
Decision rule:
If P-value is less than or equal to the level of significance, then reject the null hypothesis. Otherwise, fail to reject the null hypothesis.
Since the P-value of 0 is less than the level of significance of 0.05, reject H0.
Thus, there is enough evidence to conclude that accident type does not seem to be independent of age, at 5% level of significance.
Correct option is C.
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