The t-distribution is characterized by a single parameter, known as degrees of freedom. The t-distribution resembles the normal distribution as the former has a mean value of 0. However, the standard deviation of the t-distribution is higher than 1. As the sample size increases, the degrees of freedom increases, and the t-distribution approaches normality. Now, coming to the t-test, if the sample size is large, the sample mean of the sampling distribution is normally distributed, irrespective of the shape of the population distribution. For a t-test, a sample size of 30 or more is considered large. To conclude, the t-test can be conducted if the sample size is large or the population is normally distributed. Therefore, we conclude that the t-test is robust to moderate departures from normality. Thus while conducting the t-test it is not necessary that the population should be approximately normally distributed if the sample size is large.

The statement is false.