Which variable is most likely to follow a normal distribution?

The variable most likely to follow a normal distribution is family income. This is because family income tends to cluster around a central value due to the presence of various factors that influence it, such as education, geographic location, and job market conditions. While income data can be skewed by a small number of very high earners (resulting in a right skew), many large data sets of family income across a diverse population often approximate a normal distribution when analyzed in aggregate, particularly when considering income within specific groups or regions.

In contrast, the other variables have characteristics that lead them away from a normal distribution. The number of languages spoken is a discrete variable that usually has a limited range, making it less likely to follow a normal distribution due to the lack of continuous data points. Temperature readings can vary widely but are often influenced by seasonality and have a tendency to display patterns and extremes rather than a normal curve. Annual hours of TV watched can also be affected by cultural differences and trends, leading to a distribution that may be skewed rather than normal. Hence, family income stands out as the variable most aligned with the properties of a normal distribution in statistical studies.