Definition
A population is the entire group of units you want to make a claim about — all patients, every product from a line. A sample is the part you actually measure. Statistics lets you estimate population properties from the sample and tells you how precise that estimate is.
Foundations & hypothesis testing
Measuring a whole population is usually impossible or too expensive, so you work with a sample. For a sample to say something about the population it must be representative — ideally random, with every unit having the same chance of selection. Systematic bias (surveying only willing customers, say) cannot be repaired by any statistic afterwards.
From the sample you compute sample statistics (mean, proportion, variance) and use them to estimate population parameters. A confidence interval expresses the uncertainty of the estimate, and statistical tests tell you whether a difference seen in the sample can be generalized to the population or is just chance.
In Statistica
Statistica treats a sample as a data spreadsheet: each row is a unit, each column a variable. Statistics → Basic Statistics/Tables computes sample statistics and confidence intervals; a random subsample is created via Data → Subset / Random Sampling.
Related terms
- Confidence intervalA confidence interval is a range of values that, with a stated confidence (most often 95 %), covers the true value of a…
- p-valueThe p-value is the probability of obtaining a result at least as extreme as the one observed if the null hypothesis…
- Statistical power and sample sizeStatistical power is the probability that a test detects an effect that really exists (1 − β).
Knowledgebase guides
FAQ
- How large should a sample be?
- It depends on the smallest difference you want to detect reliably, on data variability and on the required power. Statistica includes a Power Analysis module that computes the needed sample size in advance — better than a guess.
- What if the sample is not random?
- Estimates may be systematically biased and no test will reveal it. Document how the sample was collected and generalize only to the population it really represents.
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Foundations & hypothesis testing
Updated: September 2026.