A public health researcher is comparing the effectiveness of two malaria prevention strategies in a rural Indian district. Strategy A (bed nets) was implemented in 500 households, with 45 cases of malaria. Strategy B (indoor spraying) was implemented in 480 households, with 28 cases of malaria. Which statistical test is most appropriate to determine if the difference in malaria incidence between the two strategies is statistically significant?
A. Mann-Whitney U test
B. Chi-square test of independence
C. Pearson correlation coefficient
D. Paired t-test
Explanation
Test Selection for Categorical Data Comparison
Data Type Identification
Key Point
The outcome variable (malaria: yes/no) is categorical/dichotomous, and we are comparing two independent groups (Strategy A vs Strategy B).
Why Chi-Square Test?
High-YieldNEET PG
Chi-square test of independence is used when:
Both variables are categorical (exposure/intervention and outcome)
Comparing two or more independent groups
Sample sizes are adequate (expected frequency ≥ 5 in each cell)
Contingency Table Structure
Table
Strategy
Malaria Cases
No Malaria
Total
A (Bed nets)
45
455
500
B (Spraying)
28
452
480
Total
73
907
980
Clinical Pearl
The chi-square statistic tests whether the observed frequencies differ significantly from expected frequencies under the null hypothesis of independence (no difference between strategies).
Formula
χ2=∑E(O−E)2
where O = observed frequency, E = expected frequency.
Mnemonic
CATEGORICAL → CHI-SQUARE — When you have categories (yes/no, present/absent), use chi-square; when you have continuous measurements, use t-test.
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