One way MANOVA - overview
This page offers structured overviews of one or more selected methods. Add additional methods for comparisons (max. of 3) by clicking on the dropdown button in the right-hand column. To practice with a specific method click the button at the bottom row of the table
One way MANOVA | $z$ test for the difference between two proportions |
|
---|---|---|
Independent/grouping variable | Independent/grouping variable | |
One categorical with $I$ independent groups ($I \geqslant 2$) | One categorical with 2 independent groups | |
Dependent variables | Dependent variable | |
Two or more quantitative of interval or ratio level | One categorical with 2 independent groups | |
THIS TABLE IS YET TO BE COMPLETED | Null hypothesis | |
- | H0: $\pi_1 = \pi_2$
Here $\pi_1$ is the population proportion of 'successes' for group 1, and $\pi_2$ is the population proportion of 'successes' for group 2. | |
n.a. | Alternative hypothesis | |
- | H1 two sided: $\pi_1 \neq \pi_2$ H1 right sided: $\pi_1 > \pi_2$ H1 left sided: $\pi_1 < \pi_2$ | |
n.a. | Assumptions | |
- |
| |
n.a. | Test statistic | |
- | $z = \dfrac{p_1 - p_2}{\sqrt{p(1 - p)\Bigg(\dfrac{1}{n_1} + \dfrac{1}{n_2}\Bigg)}}$
Here $p_1$ is the sample proportion of successes in group 1: $\dfrac{X_1}{n_1}$, $p_2$ is the sample proportion of successes in group 2: $\dfrac{X_2}{n_2}$, $p$ is the total proportion of successes in the sample: $\dfrac{X_1 + X_2}{n_1 + n_2}$, $n_1$ is the sample size of group 1, and $n_2$ is the sample size of group 2. Note: we could just as well compute $p_2 - p_1$ in the numerator, but then the left sided alternative becomes $\pi_2 < \pi_1$, and the right sided alternative becomes $\pi_2 > \pi_1.$ | |
n.a. | Sampling distribution of $z$ if H0 were true | |
- | Approximately the standard normal distribution | |
n.a. | Significant? | |
- | Two sided:
| |
n.a. | Approximate $C\%$ confidence interval for $\pi_1 - \pi_2$ | |
- | Regular (large sample):
| |
n.a. | Equivalent to | |
- | When testing two sided: chi-squared test for the relationship between two categorical variables, where both categorical variables have 2 levels. | |
n.a. | Example context | |
- | Is the proportion of smokers different between men and women? Use the normal approximation for the sampling distribution of the test statistic. | |
n.a. | SPSS | |
- | SPSS does not have a specific option for the $z$ test for the difference between two proportions. However, you can do the chi-squared test instead. The $p$ value resulting from this chi-squared test is equivalent to the two sided $p$ value that would have resulted from the $z$ test. Go to:
Analyze > Descriptive Statistics > Crosstabs...
| |
n.a. | Jamovi | |
- | Jamovi does not have a specific option for the $z$ test for the difference between two proportions. However, you can do the chi-squared test instead. The $p$ value resulting from this chi-squared test is equivalent to the two sided $p$ value that would have resulted from the $z$ test. Go to:
Frequencies > Independent Samples - $\chi^2$ test of association
| |
Practice questions | Practice questions | |