Question 1

What are the main types of descriptive statistics?

Accepted Answer

Descriptive statistics fall into three categories: (1) Central tendency - mean, median, mode; (2) Dispersion - range, variance, standard deviation, IQR; (3) Position - quartiles, percentiles, z-scores. Together they summarize where data centers, how spread out it is, and where individual values fall.

Question 2

How do I interpret quartiles?

Accepted Answer

Q1 (25th percentile) means 25% of data is below this value. Q2 (median, 50th percentile) splits data in half. Q3 (75th percentile) means 75% of data is below this value. The IQR (Q3-Q1) contains the middle 50% of data and is useful for identifying outliers.

Question 3

What's the difference between descriptive and inferential statistics?

Accepted Answer

Descriptive statistics summarize the data you have (this sample). Inferential statistics use sample data to make predictions or generalizations about a larger population. Descriptive statistics are always the first step before any inferential analysis.

Question 4

How many data points do I need for reliable descriptive statistics?

Accepted Answer

Basic statistics (mean, median) are meaningful with any sample size, but interpretation improves with more data. For quartiles and percentiles, at least 20-30 observations are recommended. For shape statistics (skewness, kurtosis), 50+ observations provide more reliable estimates.

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