Standard Edition

Descriptive statistics and distribution analysis Summary statistics, histograms, box plots, Q-Q plots, normality tests, one-sample hypothesis tests, and frequency analysis — the starting point of every analysis.

Understand your data before you model it

Every analysis starts here. What does the distribution look like? Is it symmetric or skewed? Are there outliers pulling the mean away from the median? Is it normal enough for a parametric test, or should you use a non-parametric alternative? The answers determine which test or model is appropriate — and skipping this step is how wrong conclusions happen.

Descriptive statistics, distribution plots, normality assessment, and one-sample tests belong in the same workflow — not scattered across separate tools. Characterise a continuous variable from summary statistics through to a formal normality test and a one-sample hypothesis test, or describe a discrete variable with frequency tables, bar plots, and proportion tests. Both continuous and discrete analysis in one place.

I use Excel to analyze, validate, and sumarize volumes of data every day. Since Analyse-It is always right there on my Excel ribbon, I go to it regularly. I am not a professional statistician, but Analyse-It gives me all of the tools in an easy to use package that lets me focus on understanding my data.

Shawn W.
Analyst

What’s included

Summarise location, spread, and shape in one output

Mean, median, SD, CV%, skewness, kurtosis, quantiles, geometric and harmonic mean — all the measures you need to characterise a variable, reported together. See immediately whether the distribution is symmetric, how spread out it is, and whether the tails are heavier or lighter than normal.

See the distribution, not just the numbers

A histogram shows the shape. A Q-Q plot shows departures from normality. A box plot shows the median, quartiles, and outliers. A CDF plot shows the cumulative distribution with Kolmogorov-Smirnov confidence bands. Dot plots show every observation. Each plot answers a different question — use whichever combination the data requires.

Assess normality before choosing a test

The Q-Q plot with Lilliefors confidence band shows visually whether the data depart from normality. Shapiro-Wilk, Anderson-Darling, and Kolmogorov-Smirnov provide formal tests. If the distribution isn’t normal, transform the variable directly and reassess — or switch to a non-parametric test.

Test a single sample against a hypothesised value

Does the mean differ from a target? One-sample t-test when normality holds, Wilcoxon or Sign test when it doesn’t. Mean and median estimates with confidence intervals. Hodges-Lehmann pseudo-median with Tukey CI for a robust location estimate. χ² test and CI for variance when dispersion is the question.

Describe and test categorical data

Frequency tables with cumulative and relative frequencies. Bar plots with cumulative frequency overlay. Binomial exact and Score Z tests for a single proportion. Pearson χ² and likelihood ratio G² tests for multinomial proportions — test whether the observed distribution matches a hypothesised one. Proportion with Clopper-Pearson exact or Wilson score CI.

Example analyses

See descriptive statistics and distribution analysis in detail — summary statistics, histograms, Q-Q plots, normality tests, and one-sample tests.

Continuous distribution
Newcomb’s speed of light, 64 observations. Descriptive statistics, histogram with normal overlay, box plot, CDF plot, Q-Q plot with Lilliefors band, Shapiro-Wilk normality test, and one-sample t-test.

Discrete distribution
Hair–eye colour frequencies, 592 observations. Frequency table, bar plot with cumulative frequency, pie chart, and Pearson χ² test of multinomial proportions.

Part of the Standard edition

Descriptive statistics are one part of a complete statistical analysis toolkit. The Standard edition also includes ANOVA and ANCOVA, simple and multiple regression, logistic regression, PCA and factor analysis, hypothesis testing, correlation, and categorical data analysis. See everything in the Standard edition →

Validated, reliable, trusted for over 30 years

Validated calculations Every statistic tested against NIST Standard Reference Datasets, published datasets and thousands of internal test-cases. No reliance on Excel'sbuilt-in functions. See how we develop and validate Analyse-it →

Data stays on your PC No cloud processing, no uploads, no third-party access. Your data never leaves your computer — essential when working with sensitive, confidential, or patient-identifiable data.

Standard Excel workbooks Analyses are ordinary Excel workbooks that you can share with colleagues, archive for audit, and open on any machine with Excel — no Analyse-it licence required.

No formulas to break Results contain no formulas, so they can't be accidentally edited or corrupted. The results you reported will be exactly what you find when you reopen the workbook.

Technical details

Continuous descriptive statistics

Sum, Mean, Variance, SD, CV%, Skewness, Kurtosis
Geometric Mean, Harmonic Mean new in v4.50
Median, Minimum, Maximum, Range, IQR
Quantiles
Mode
Transform variable new in v5.50

Normality tests

Shapiro-Wilk test
Anderson-Darling test
Kolmogorov-Smirnov test

Plots

Histogram with optional normal overlay
Frequency polygon
Dot plot — jittered, aligned, spread; vary symbol/colour
Skeletal box plot, Tukey outlier box plot, Quantile box plot
Mean error bar plot, Mean confidence diamond plot
CDF plot with optional Kolmogorov-Smirnov confidence band
Normal Q-Q plot with optional Lilliefors confidence band

One-sample location tests

Z test for mean with known population SD
Student’s one-sample t-test for mean
Wilcoxon test for mean/median
Sign test for median

Location estimators

Mean with t-based or Z-based CI
Median with Thompson-Savur CI
Hodges-Lehmann pseudo-median with Tukey CI

Dispersion tests & estimators

χ² test for variance
Variance with χ²-based CI

Discrete

Frequency table (frequency, cumulative, relative, cumulative relative)
Frequency bar plot with optional cumulative line
Frequency pie (whole-to-part) plot
Binomial exact test for proportions
Score Z test for binomial proportions
Pearson χ² and G² test for multinomial proportions
Proportion with Clopper-Pearson exact or Wilson score CI

Standard Edition Descriptive statistics and distribution analysis Summary statistics, histograms, box plots, Q-Q plots, normality tests, one-sample hypothesis tests, and frequency analysis — the starting point of every analysis.