Mcnemar Test Calculator

Publish date: 2024-06-11
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Perform the Mcnemar exact test with a = , b = , c = , and d = , with level of significance

determine the null and alternative hypothesis, critical value, test statistic

The table setup below
  Column 1Column 2Row Total
Row 1aba + b
Row 2cdc + d
Column Totala + cb + dn = (a + b + c + d)
Plugging in our a, b, c, and d values, we get:
  Column 1Column 2Row Total
Row 1+
Row 2+
Column Total++n = ( + + + )
Evaluating, we get:
  Column 1Column 2Row Total
Row 10
Row 20
Column Total000
Display null and alternative hypothesis:

H0:   pb = pc

H1:   pb ≠ pc

Calculate the Mcnemar test statistic:
Χ2  =  (b - c)2
  b + c

Χ2  =  ( - )2
  +

Χ2  =  02
  0

Χ2  =  0
  0

Χ2 = NAN

Calculate the critical value:

χ2 = <--- Value can be found on Excel using =CHIINV(,1)

Draw our conclusion:

Since our test statistic of NAN > χ2 value of ,
it is in the rejection region, so we reject H0

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What is the Answer?

Since our test statistic of NAN > χ2 value of ,
it is in the rejection region, so we reject H0

How does the Mcnemar Test Calculator work?

Free Mcnemar Test Calculator - Given a 2 x 2 contingency table and a significance level, this will determine the test statistic, critical value, and hypothesis conclusion using a Mcnemar test.
This calculator has 5 inputs.

What 1 formula is used for the Mcnemar Test Calculator?

Χ2 = (b - c)2/(b + c)

For more math formulas, check out our Formula Dossier

What 5 concepts are covered in the Mcnemar Test Calculator?

alternative hypothesisopposite of null hypothesis. One of the proposed proposition in the hypothesis test.
H1hypothesisstatistical test using a statement of a possible explanation for some conclusionsmcnemar testused to determine if there are differences on a dichotomous dependent variable between two related groups.null hypothesisin a statistical test, the hypothesis that there is no significant difference between specified populations, any observed difference being due to sampling or experimental error.
H0test statistica number calculated by a statistical test

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