Statistics Calculators
9 calculators
Inferential statistics: confidence intervals, correlation, linear regression, chi-square, margin of error and p-values. More than anywhere else on this site, the result depends on assumptions you must verify yourself — independence, sample size and distribution shape. A p-value computed on data that violates them is not evidence of anything.
- Chi-Square Calculator Calculate the chi-square statistic for observed and expected frequencies.
- Confidence Interval Calculator Calculate a two-sided Student t confidence interval for a population mean from sample statistics.
- Correlation Calculator Calculate the Pearson correlation coefficient between two data sets.
- Linear Regression Calculator Fit a least-squares regression line to two data sets and predict new values.
- Margin of Error Calculator Work out how far a survey result could be from the true value, given the sample size and confidence level.
- P-Value Calculator Test a sample mean against a null hypothesis and get the p-value, the z statistic and both one- and two-tailed results.
- Percentile Calculator Find the value at a given percentile, or the percentile rank of a given value.
- Sample Size Calculator Find how many responses a survey needs for a given margin of error and confidence level.
- Z-Score Calculator — Standard Score & Normal Percentile Convert a value to a z-score using the mean and a positive standard deviation.
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A statistical method is selected from the study question, data structure and assumptions, not from which result looks most favorable. A descriptive score summarizes observations, a confidence interval describes uncertainty under a model, and a hypothesis test asks a specified comparison question.
Summarize and relate observations
Use z-scores or percentiles to locate a value relative to a distribution. Correlation and linear regression describe different relationships; their outputs do not by themselves establish a causal explanation or validate a fitted model.
Plan or evaluate an inferential calculation
Confidence intervals, p-values and chi-square calculations require method-specific inputs and assumptions. Sample-size tools are planning scenarios whose inputs, such as uncertainty or effect assumptions, must be chosen for the actual study.
Report the method with the result
Keep the sample definition, units, model assumptions and rounding alongside the numerical output. A small p-value, a narrow interval or a large sample-size result is not a substitute for checking data quality and the research design.