Transpose Row Data into Columns

Use this tool to paste data that is organized in rows (e.g., from a textbook). Each row should start with a title, followed by the numbers separated by commas or tabs.

Process & Transpose Data

Statistics Display Options

Add Data Set Upload CSV Load Example

Data Visualization & Correlation

Toggle Points

X-Axis / Variable

Y-Axis

Chart Type

Show Regression Line

Residual Plot

Statistical Breakdowns

Analysis Summary

A summary of the selected analysis will appear here.

Prediction Calculator

Using the equation:

If x =

, then the predicted ŷ is:

...

Categorical Data Tools

Enter categorical data (e.g., Red, Blue, Blue, Green) separated by commas or new lines to generate visualizations.

Generate Bar Chart Generate Pie Chart

Visualization

Probability Calculator

Hypothetical 1000 Table Generator

Enter three known probabilities to generate a 2x2 contingency table and calculate related probabilities. For example, enter P(A), P(B), and P(A and B).

P(A)

P(B)

Third Probability

P(A and B) P(A or B) P(A | B) P(B | A)

Generate

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Generated Table

Your hypothetical 1000 table will appear here.

Show Tree Diagram

Calculated Probabilities

Calculated probabilities will appear here.

Tree Diagram

Raw Data Table Calculator

Load a categorical dataset from the Chapter 5 exercises to automatically generate a contingency table and calculate all related probabilities.

Contingency Table

Load a dataset to begin.

Calculated Probabilities

Calculated probabilities will appear here.

Z-Score Calculator

Calculate the z-score to see how many standard deviations a data point is from the mean.

Data Point (x)

Mean (μ or x̄)

Standard Deviation (σ or s)

Calculate Z-Score

Z-Score Result

Percentile Calculator

Enter a dataset to find key percentiles or the percentile rank of a specific value.

Data Set (comma-separated)

Find Percentile Rank for Value (optional)

Calculate Percentiles

Percentile Results

Empirical Rule (68-95-99.7) Calculator

For data that follows a bell-shaped, normal distribution, the Empirical Rule tells us how much data falls within a certain number of standard deviations from the mean.

Center (Mean)

Standard Deviation (SD)

Calculate

Correlation from Summary Data

Use this tool when you don't have the raw data, but you have pre-calculated summary statistics (like in exercise 4.20). Enter the values below to calculate the correlation coefficient (r).

n (Sample Size)

Σx (Sum of x)

Σy (Sum of y)

Σxy (Sum of x*y)

Σx² (Sum of x²)

Σy² (Sum of y²)

Calculate Correlation

Calculation Result

Normal Distribution Calculator

Mean (μ)

Std Dev (σ)

Calculation Type P(X < a) — Area to the Left P(X > a) — Area to the Right P(a < X < b) — Area Between P(X < a or X > b) — Area Outside

Probability:

0.0000

Sampling Distribution Simulator for Proportions (p̂)

Visualize how sample proportions (p̂) behave by drawing many random samples from a population.

Population Proportion (p)

Sample Size (n)

Number of Samples

Run Simulation

Distribution of Sample Proportions

For a Population Proportion (p)

Successes (x)

Sample Size (n)

Confidence90%95%98%99%

Calculate Interval for Proportion

For a Population Mean (μ)

Sample Mean (x̄)

Sample SD (s)

Sample Size (n)

Confidence Level 90% 95% 98% 99%

Calculate Interval for Mean

One-Sample Test for a Proportion (z-test)

1. State Hypotheses

H₀: p =

Hₐ:

p ≠ p₀

p < p₀

p > p₀

2. Enter Sample Data

Successes (x)

Sample Size (n)

3. Set Significance Level (α)

0.10 0.05 0.01

Run Test

One-Sample Test for a Mean (t-test)

1. State Hypotheses

H₀: μ =

Hₐ:

μ ≠ μ₀

μ < μ₀

μ > μ₀

2. Enter Sample Data

Mean (x̄)

SD (s)

Size (n)

3. Set Significance Level (α)

0.10 0.05 0.01

Run Test