Statistical analysis of numeric data

Input Values


Note: This page now accepts data where either a comma (,) or point (.) is used as the decimal separator.

Undertake statistical analysis of numeric data, grouped by a category variable. Statistical tests include t-test, one-way analysis of variance (ANOVA), Wilcoxon rank sum test and Kruskal-Wallis test. Choice of test depends on user input (parametric or non-parametric) and the number of groups identified in the data.

Inputs are:

  • the type of analysis to be done (parametric or non-parametric);
  • whether the data is continuous or discrete;
  • desired level of confidence for confidence interval estimation;
  • the desired number of digits after the decimal point in summary results; and
  • two columns of data (including a header row with labels for each column). The first column is the category variable and the second is the numeric variable.

Note: missing values in the data will be omitted from calculations.

The program undertakes statistical tests depending on the options selected and also outputs a tabular summary and graphs of the data. Outputs include:

  • a summary of statistical test results for: t-test (2 groups) or ANOVA (>2 groups) if the parametric option is selected or Wilcoxon rank sum test (2 groups) or Kruskal-Wallis test (>2 groups) for the non-parametric option;
  • Shapiro-Wilk test for normality on all groups and Bartlett's test for homogeneity of variance if the parametric option is selected;
  • Note: for groups with < 4 or > 5000 observations it is not possible to calculate Shapiro-Wilks W statistic to test for normality of distribution
  • a numeric summary of the data for each group and overall, including histograms and normal plots;
  • Note: for groups with only one observation or with standard deviation = 0 histograms and quantile plots are not shown.
  • a table and bar chart of frequency counts for each cell if the data is identified as being discrete; and
  • a bar chart of the sample size per group, boxplots of the data by group and a plot of confidence intervals about the mean value for each group.
Type of statistical test to be done?
Parametric (t-test or ANOVA)
Non-parametric (Wilcoxon or Kruskal-Wallis)
Type of data?
Continuous (eg weights)
Discrete (eg scores or counts)
Confidence level:
Digits after decimal pt:
Paste the data to be summarised in the space below and click on submit (1st column is grouping variable, second column is data). Include a header row:
Download example data


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It provides a range of epidemiological tools for the use of researchers and epidemiologists, particularly in animal health.
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