Compare and Contrast

# Descriptive vs Inferential Statistics – All Key Differences

## Descriptive Statistics vs Inferential Statistics

Descriptive statistics help us to summarize and understand the data we have, inferential statistics help us to make predictions and inferences about larger populations based on that data.

### Descriptive Statistics:

Descriptive statistics primarily describe, summarize, and present data in a meaningful way. They provide a snapshot or summary of the data. This could include measures of central tendency like the mean, median, and mode, or measures of dispersion or variation like range, variance, and standard deviation. Graphical representations like pie charts, histograms, and box plots are also part of descriptive statistics. Descriptive statistics does not draw conclusions or make predictions beyond the data at hand.

Example: In a class of 30 students, the average score on a math exam might be 80% with a standard deviation of 5%.

### Inferential Statistics:

Inferential statistics go a step further. Using the data gathered from a small group (a sample), they infer and make predictions about the larger group (the population). Inferential statistics involve hypothesis testing, correlations, regressions, confidence intervals, chi-square tests, t-tests, ANOVA (Analysis of Variance), etc.

Inferential statistics allows us to take risks and make educated guesses. It helps us to decide whether an observed result is due to chance or whether there are other factors at play.

Example: From a sample of 100 voters, we might infer that a particular candidate will win the election in a city of 1 million voters.