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Statistical significance testing

Chi-squared test for trend

Paste three columns of data (3 or more rows) to be analysed in the space below and click on submit. Include a header row with column identifiers. The first column must be numeric and represents the score or value for each category. Other columns are counts of individuals in each category combination. Do not include row or column totals.
Download example data


Undertake a chi-squared test for trend on a contingency table with 2 columns and 3 or more rows.

Inputs are:

  • - the desired level of confidence in the estimate;
  • - the desired precision of the results; and
  • - three columns of data. The first column represents group scores or values, while the remaining 2 columns are the respective counts for each combination of row and column categories. A header row of column names must be included but do not include row or column totals.

Outputs include:

  • - the table of observed counts, with row and column totals; and;
  • - chi-squared statistic, degrees of freedom and corresponding P-value for normal chi-square test, as well as for slope and linearity of the data:
    • - first row is a standard Pearson's Chi-squared test for association between predictor and outcome;
    • - second row is a Chi-squared test for linear trend. A significant result suggests that the slope of the trend line is non-zero; and;
    • - third row is a Chi-squarted test for linearity of the trend. A significant result suggests the trend is non-linear.


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