BetaThis calculator is still under development (v2.20). Features and results may change, and errors are possible — please check anything that looks wrong and let me know.
Statistics Calculator · v2.20
A complete statistics calculator.
Choose Guided or Calculator Mode. Both use the same data lists, saved work, and statistical engines.
11 guided calculators12 calculator proceduresShared data lists L1–L6Saves in this browser
How do you want to work?Your data lists, saved work, and calculation engines are shared in both modes.
Your data lists and calculator settings save automatically in this browser. Download a backup to reopen this work later or move it to another device.
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1. Add data
Choose the easiest way to add a data set: enter one list of numbers, or paste or upload a table from a spreadsheet.
Commas, spaces, semicolons, and new lines all work. Brackets such as [12, 15, 18] are optional.
Copy cells from Excel, Google Sheets, or another spreadsheet and paste them here. CSV means comma-separated values; TSV means tab-separated values. You usually can leave automatic detection selected.
Drop a spreadsheet data file here
CSV and TSV files are supported, or choose a file from your computer.
Separate several entries with commas. Blank cells are already treated as missing.
Review your table
Check that the rows and columns look right. You can edit cells before adding a numeric column to a data list. Yellow cells are missing; red cells need attention.
Rows with nonnumeric entries:
2. Check your data lists (L1–L6)
These six lists are where the calculator keeps data sets. Open the table to review or edit values — type a number and press Enter to drop straight to the next row. When a calculator asks for a data list, choose the list that contains your numbers. Blank cells are ignored.
Data lists · all lists empty
3. Guided calculations
Choose what you want to calculate, then enter the requested information. If the calculation uses a data set, select the L1–L6 list that contains your numbers.
Guided Mode shows the modern result first. For TI-supported procedures, the equivalent calculator command appears with the result.
Summarizing data
Probability and distributions
Inference
Guided mode
Descriptive statistics
The calculator output remains TI-compatible. Detailed results add mode, variance, range, IQR, and outlier information.
Summarizes a shared data list with the verified one-variable statistics engine.
Guided mode
Binomial probability
Binomial conditions
Guided mode
Normal area and percentile
The guided form will generate the equivalent normalcdf or invNorm command.
Guided mode
Sampling distribution
The transformed sampling-distribution parameters will be used in the equivalent normal command.
Guided mode
Scatterplot
Plot one list against another and look at the pattern. No line is fitted — decide whether a straight line is appropriate before you fit one.
The correlation 𝑟 is reported with the plot. To fit and report a least-squares line, use the Regression calculator.
Guided mode
Least-squares regression
Leave blank to omit a prediction.
The fitted line, scatterplot, and prediction use the same paired rows. Regression significance tests and residual analysis are not built yet.
Guided mode
Confidence interval
Enter a decimal such as .90, .95, or .99.
Two independent samples uses 2-SampTInt.
Known uses ZInterval; unknown uses TInterval.
Welch’s method is the usual choice. Pooling assumes the two population standard deviations are equal, which is rarely safe.
Two-sample interval assumptions
Where both sample sizes are greater than 30 the size branch is satisfied on its own; the calculator reports 𝑛₁ and 𝑛₂ with the check.
Paired-interval assumptions
Where the number of pairs is greater than 30 the size branch is satisfied on its own; the calculator reports 𝑛 with the check.
Mean-interval assumptions
For n > 30, the sample-size branch is automatically satisfied. With raw data and a smaller sample, use the dotplot review below.
Dotplot normality review
For a small sample, inspect the dotplot and mark anything you see that would rule out approximate normality. The calculator does not make this visual judgment for you.
Two-proportion interval assumptions
Proportion-interval assumptions
Guided mode
Hypothesis tests
Example: the population mean wait time or the population proportion of customers who return.
Two independent samples uses 2-SampTTest.
Known uses Z-Test; unknown uses T-Test.
The usual practice is not to assume the two variances are equal.
Two-sample test assumptions
The same three conditions the confidence interval requires. Where both sample sizes exceed 30 the size branch is satisfied on its own.
Paired-test assumptions
Where the number of pairs is greater than 30 the size branch is satisfied on its own; the calculator reports 𝑛 with the check. With raw data and a smaller sample, use the dotplot review.
Mean-test assumptions
For n > 30, the sample-size branch is automatically satisfied. With raw data and a smaller sample, use the dotplot review below.
Dotplot normality review
For a small sample, inspect the dotplot and mark anything you see that would rule out approximate normality. The calculator does not make this visual judgment for you.
Two-proportion test assumptions
Proportion-test assumptions
This wording is used only to explain the classification.
Guided mode
Discrete random variable
Example: winnings per game or number of repairs.
Probability distribution
𝑥𝑃(𝑥)
Rows remain paired. A value without a probability, or a probability without a value, must be corrected.
Separate values with commas.
Guided mode
Frequency and histogram builder
Use one observation per line. Commas or semicolons also work when category names do not contain them.
Category frequencies
CategoryFirstSecond
Leave the entire second series blank for a single distribution. A side-by-side bar graph requires both series.
Guided mode
Probability basics
Used only to make the interpretation easier to read.
For a continuous random variable, including or excluding an endpoint does not change the probability.
Unusual events: an event is unusual only when its probability is less than 0.05. A probability of exactly 0.05 is not classified as unusual.
Calculator mode
Enter a command or expression
Math examples: (14.7-12.3)/2.1, sqrt(48), 2^7, A=25, Ans*100, mean(L1). Statistical commands use the same shared lists and engines as Guided Mode.
Keypad and functions
Calculation history
Recent calculator entries
Your result will appear here.
Run a calculation in the mode you selected. Your shared data and saved work stay available when you switch modes.
Calculator output
Calculator output format
1-Var Stats L1
Detailed results
The same engine, with standard notation, clearer labels, and descriptive extensions
4. Explore the distribution
The dotplot, histogram, and modified boxplot use the same data. The dotplot supports visual normality assessment; the boxplot and the summary statistics use the same quartiles.
Dotplot
Use the individual data values to inspect clusters, gaps, skewness, multiple modes, and unusual points.
Histogram
Equal-width classes; adjust the class count above.
Modified boxplot
Whiskers stop at the most extreme non-outliers.
4. View the binomial distribution
Highlighted bars are the outcomes included in the selected probability region.
4. View the regression
The scatterplot, fitted line, and optional prediction use the same paired lists and regression coefficients.
4. View the confidence interval
The interval, point estimate, and optional claim use the same calculated endpoints.
4. View the hypothesis test
The shaded tail or tails use the same alternate hypothesis, test statistic, and P-value as the numerical result.
4. View the probability distribution
The highlighted bars are the outcomes included in the selected event.
4. View the frequency graph
The graph and table use the same category counts or quantitative class intervals.
4. View the probability
The graph uses the same probability calculation shown above.
4. View the normal distribution
The shaded region and cutoff markers use the same parameters as the calculated result.
Runs locally in your browser. No data are uploaded to a server.
An independent educational tool for introductory statistics. Results are formatted to match what you will see on the TI-84 Plus CE used in class. Not affiliated with, endorsed by, or sponsored by Texas Instruments. TI-84 Plus CE is a trademark of Texas Instruments Incorporated.