Question 1

When should I use mean vs median?

Accepted Answer

Use the mean when your data is roughly symmetric without outliers. Use the median when data is skewed or contains outliers, as it's not affected by extreme values. For example, median income is often more representative than mean income due to high earners skewing the average.

Question 2

What does standard deviation tell me?

Accepted Answer

Standard deviation measures how spread out your data is from the mean. A low standard deviation means data points cluster close to the mean, while a high standard deviation indicates wider spread. In a normal distribution, about 68% of data falls within 1 SD, 95% within 2 SDs, and 99.7% within 3 SDs of the mean.

Question 3

Why is my variance so much larger than my standard deviation?

Accepted Answer

Variance is the square of standard deviation, so it's always in squared units. For example, if your data is in meters and SD is 5m, variance would be 25m². Standard deviation is often preferred for interpretation because it's in the same units as your data.

Question 4

What if my data has no mode?

Accepted Answer

A data set has no mode when all values occur with equal frequency. This is common in continuous data or small sample sizes. In such cases, the mode isn't useful for describing central tendency - rely on mean or median instead.

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