**Core Concept**
In this scenario, we're dealing with a comparison of proportions between two groups, which is a fundamental concept in epidemiology and statistics. The chi-square test is a statistical method used to determine the significance of differences between observed and expected frequencies in categorical data.

**Why the Correct Answer is Right**
The chi-square test is the best statistical test to use when comparing proportions between two independent groups, such as in this case, where we have a standard group and a treatment group. This test allows us to determine whether the observed differences in proportions are statistically significant, taking into account the sample size and the expected frequencies. The chi-square test is particularly useful when dealing with categorical data, such as proportions or frequencies, and is widely used in epidemiological studies to compare outcomes between groups.

**Why Each Wrong Option is Incorrect**
**Option A:** The Student T test is used to compare the means of two groups, which is not applicable in this scenario where we are comparing proportions.
**Option C:** The Paired T test is used to compare the means of two related groups, which is also not applicable here as the groups are independent.
**Option D:** The Test for variance is used to compare the variances of two groups, which is not relevant in this context where we are comparing proportions.

**Clinical Pearl / High-Yield Fact**
When comparing proportions between two groups, it's essential to use the correct statistical test to avoid Type I errors. The chi-square test is a robust method for comparing categorical data, but it's crucial to check the assumptions of the test, such as the expected frequencies and the sample size.

**✓ Correct Answer: B. Chi square test**