Normal distributions in real life: Many variables are normally distributed, but

Question

Normal distributions in real life: Many variables are normally distributed, but not all are. (Fortunately, the central limit theorem saves us when we conduct research on samples from nonnormal populations if the samples are larger than 30!) Is the distribution of time spent commuting to work in the population of employed adults in San Antonio, Texas likely to be normal or nonnormal? Why?

Nonnormal; some people live close to work and others live far away, creating a bimodal distribution.

Nonnormal; there would be a wide range of commute times, but each one should be equally likely creating a uniform distribution.

Normal; there would be a wide range of commute times with a few far above and a few far below average.

Nonnormal; some people probably work at home, so those "zero" time commutes would result in a negative tail.

Explanation / Answer

Nonnormal;

there would be a wide range of commute times, but each one should be equally likely creating a uniform distribution.

option b

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