Comparing two proportions for paired samples (3)

Now that we've got our 2 parameters, we can actually check whether the difference is significant. To do so, we will use the McNemar test. The formula for the McNemar test is displayed below:

$$z = \frac{n_{01} - n_{10}}{\sqrt{n_{01} + n_{10}}}$$

Let's fill in some of the parameters using our own data (see below). To calculate this Z value, you would need to fill in the gaps. $n01$ in this case is the value in row zero and the first column. This would thus be the value of 50. $n10$ in this case is the value in the first row and column zero. This would thus be 35.

This exercise is part of the course

Inferential Statistics

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Exercise instructions

Calculate the z statistic using the McNemar test. Assign this to a variable z_value
Use the function pnorm() to check the p value that pertains to the z value and print it to the console. To use the pnorm() function, you can just fill in the the z_value as the first parameter. Also make sure to set the lower.tail argument to FALSE. Lastly, make sure to multiply the p value by 2 as we are doing a two-sided hypothesis test.
Is there a significant difference between the amount of surveyed people that approve of the European Union and the amount of their partners that approve of the European union? Assign either a yes or a no to the variable difference

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# calculate the z value and assign it to the variable z_value


# calculate the p value that pertains to the z value


# assign a yes or a no to the variable difference

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