Unequal Variances can be the result of differing types of distributions.

Question

Options

• ATrue
• BFalse

• A
  73% (16)
• B
  27% (6)

Explanation

Option A is correct because variance - the spread of data around the mean - is fundamentally tied to the shape of the underlying distribution. Different distribution types (e.g., normal, exponential, Poisson, uniform) have different mathematical properties that produce different variances, even when comparing groups with similar means.

Why B is wrong: Saying "False" would incorrectly imply that unequal variances only arise from measurement error or sample size differences. In reality, if two groups follow distributions of different types (e.g., one is normally distributed and the other is exponentially distributed), their variances will inherently differ due to the mathematical nature of those distributions - not just random chance.

Memory tip: Think of it this way - a normal distribution is "bell-shaped and symmetric," while an exponential distribution is "right-skewed." Just by their shapes alone, you can see they spread data differently. Different shapes = different spreads = different variances. If the distributions don't match, neither will their variances.

No community discussion yet for this question.