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Given in the question that, the primary concern is deciding whether the mean of Population 2 is greater than the mean of Population 1.

We need to determine the null and alternative hypotheses.

A hypothesis is a testable hypothesis. The hypothesis is tested using a variety of statistical models.

A frequently accepted fact is referred to as a null hypothesis. The null hypotheses are rejected, disproved, or nullified by researchers. The researcher proposes an alternative hypothesis to disprove the null hypothesis.

The key concern in the scenario is determining whether Population 2's mean is bigger than Population 1's mean.

First, it is assumed that Population 2's mean is smaller than or equal to Population 1's mean. In other words, population 1's mean is bigger than or equal to population 2's mean. After that, the researcher seeks to disprove the null hypotheses.

Null hypotheses:$H_0:{\mathrm{μ}}_1â‰\yen {\mathrm{μ}}_2$

Alternate hypotheses:$H_a:{\mathrm{μ}}_1<{\mathrm{μ}}_2$

Given in the question that, we need to classify the hypothesis test as two tailed, left tailed, or right tailed.

The key concern in the scenario is determining whether Population 2's mean is bigger than Population 1's mean.

First, it is assumed that Population 2's mean is smaller than or equal to Population 1's mean. In other words, population 1's mean is bigger than or equal to population 2's mean. After that, the researcher seeks to disprove the null hypotheses.

Null hypotheses:$H_0:{\mathrm{μ}}_1â‰\yen {\mathrm{μ}}_2$

Alternate hypotheses: $H_a:{\mathrm{μ}}_1<{\mathrm{μ}}_2$

The influence of alternate hypotheses can be tested from the left side of the normal distribution curve. As a result, the hypotheses test is two-tailed.