Answer:
Step-by-step explanation:
From the give information: A new vaccination is being used in a laboratory experiment to investigate whether it is effective. There are 275 subjects in the study. Is there sufficient evidence to determine if vaccination and disease status are related?
Vaccination Status Diseased Not Diseased Total
Vaccinated 53 17 70
Not Vaccinated 62 143 205
Total 115 160 275
In this study, we have two variables ( Vaccination and diseases status ) The null and the alternative hypothesis can be stated as follows:
Null hypothesis: The two variables ( Vaccination and diseases status ) are independent
Alternative hypothesis : The two variables ( Vaccination and diseases status ) are dependent
The Chi-square test statistics can be computed as:
The Expected Values for the table can be calculated by using the formula:
[tex]E_i=\dfrac{row \ total \times column \ total}{grand \ total}[/tex]
Vaccination Status Diseased Not Diseased Total
Vaccinated 29.273 40.727 70
Not Vaccinated 85.727 119.273 205
Total 115 160 275
[tex]Chi - Square \ X^2 = \dfrac{(O_i-E_i)^2}{E_i}[/tex]
Vaccination Status Diseased Not Diseased Total
Vaccinated 19.232 13.823 33.055
Not Vaccinated 6.564 45.573 52.137
Total 25.796 59.396 85.192
Therefore;
the Chi-Square Test Statistics = 85.192
For this study; we two rows and two columns
Therefore, the degree of freedom = (rows-1) × (columns-1)
the degree of freedom = (2 - 1) × (2 - 1)
the degree of freedom = 1 × 1
the degree of freedom = 1
Using the level of significance of ∝ = 0.05 and degree of freedom = 1 for the chi-square test
The p-value for the test statistics = 0.00001
Decision rule: Since the P-value is lesser than the level of significance , therefore we reject the null hypothesis at the level of significance of 0.05
Conclusion:
We accept the alternative hypothesis and conclude that the two variables
(Vaccination and diseases status ) are dependent i.e the vaccination and disease status are related
