ANOVA calculator

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One-way ANOVA calculator

One-way Analysis of Variance (ANOVA) is a statistical test used to determine whether there are significant differences between the means of two or more independent groups. This calculator performs one-way ANOVA and provides detailed results including F-statistic, p-value, and group statistics. The results are visualized using box plots to help you understand the distribution of values across different groups.

Calculate F-statistic and p-value

Compute sum of squares and mean squares

Display group means and sample sizes

Visualize data with box plots

Support for multiple groups comparison

How to use the ANOVA calculator

  1. Upload data
    Upload your data file containing the groups and their corresponding values
  2. Select value column
    Select the column containing the numerical values you want to analyze
  3. Select group column
    Select the column containing the group labels
  4. View results
    The calculator will automatically compute and display: - F-statistic and p-value - Degrees of freedom - Sum of squares and mean squares - Group means and sample sizes - Box plot visualization

ANOVA calculator examples

Example 1: Plant growth study

Compare the heights of plants grown under different fertilizer treatments.

Input Data:

Treatment: [A, A, A, B, B, B, C, C, C]
Height: [10.2, 9.8, 10.0, 12.3, 11.8, 12.0, 8.9, 9.1, 8.7]

Group Statistics:

TreatmentNMean
A310.00
B312.03
C38.90
Overall910.31

ANOVA Results:

SourceSSdfMSFp-value
Between Groups15.162227.5811158.6744< 0.0001
Within Groups0.286760.0478--

Interpretation: There is a significant difference in plant heights between treatments (p < 0.05).

Example 2: Student performance

Compare test scores across different study methods.

Input Data:

Method: [Traditional, Traditional, Online, Online, Hybrid, Hybrid]
Score: [85, 82, 78, 75, 90, 88]

Group Statistics:

MethodNMean
Traditional283.50
Online276.50
Hybrid289.00
Overall683.00

ANOVA Results:

SourceSSdfMSFp-value
Between Groups157.0000278.500021.40910.0168
Within Groups11.000033.6667--

Interpretation: There is a significant difference in test scores between study methods (p < 0.05).

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