spss - Correlation between interval and ordinal data - Cross Validated
However, we do not know if the difference is between only two of the levels or not wish to assume that the difference between the two variables is interval and. Choosing the Correct Statistical Test in SAS, Stata, SPSS and R is the difference between categorical, ordinal and interval variables? for more information on this). 1 IV with 2 levels (independent groups), interval & normal, 2 independent. Correlation between ordinal data and metric data can be done using Spearman correlation. The 3-point scale can obviously not be normally.
We can do this as shown below. The mean of the variable write for this particular sample of students is We would conclude that this group of students has a significantly higher mean on the writing test than One sample median test A one sample median test allows us to test whether a sample median differs significantly from a hypothesized value.
We will use the same variable, write, as we did in the one sample t-test example above, but we do not need to assume that it is interval and normally distributed we only need to assume that write is an ordinal variable.
Spearman's Rank-Order Correlation using SPSS Statistics
Binomial test A one sample binomial test allows us to test whether the proportion of successes on a two-level categorical dependent variable significantly differs from a hypothesized value. Chi-square goodness of fit A chi-square goodness of fit test allows us to test whether the observed proportions for a categorical variable differ from hypothesized proportions. We want to test whether the observed proportions from our sample differ significantly from these hypothesized proportions.
Two independent samples t-test An independent samples t-test is used when you want to compare the means of a normally distributed interval dependent variable for two independent groups.
What statistical analysis should I use? Statistical analyses using SPSS
For example, using the hsb2 data filesay we wish to test whether the mean for write is the same for males and females. Because the standard deviations for the two groups are similar In other words, females have a statistically significantly higher mean score on writing An overview of statistical tests in SPSS Wilcoxon-Mann-Whitney test The Wilcoxon-Mann-Whitney test is a non-parametric analog to the independent samples t-test and can be used when you do not assume that the dependent variable is a normally distributed interval variable you only assume that the variable is at least ordinal.How To Use SPSS - Spearman Correlation Coefficient
We will use the same data file the hsb2 data file and the same variables in this example as we did in the independent t-test example above and will not assume that write, our dependent variable, is normally distributed.
Why is the Mann-Whitney significant when the medians are equal? Chi-square test A chi-square test is used when you want to see if there is a relationship between two categorical variables.
In SPSS, the chisq option is used on the statistics subcommand of the crosstabs command to obtain the test statistic and its associated p-value. Remember that the chi-square test assumes that the expected value for each cell is five or higher. This assumption is easily met in the examples below. The point of this example is that one or both variables may have more than two levels, and that the variables do not have to have the same number of levels.
Possible alternative tests to Spearman's correlation are Kendall's tau-b or Goodman and Kruskal's gamma. We show you the main procedure for doing this here. In practice, checking for these two assumptions just adds a little bit more time to your analysis, requiring you to click of few more buttons in SPSS Statistics when performing your analysis, as well as think a little bit more about your data, but it is not a difficult task.
These two assumptions are: Your two variables should be measured on an ordinal, interval or ratio scale. Examples of ordinal variables include Likert scales e. You can learn more about ordinal, interval and ratio variables in our article: There is a monotonic relationship between the two variables.
A monotonic relationship exists when either the variables increase in value together, or as one variable value increases, the other variable value decreases. Whilst there are a number of ways to check whether a monotonic relationship exists between your two variables, we suggest creating a scatterplot using SPSS Statistics, where you can plot one variable against the other, and then visually inspect the scatterplot to check for monotonicity.
Your scatterplot may look something like one of the following: The relationship displayed in your scatterplot should be monotonic. In our enhanced guides, we show you how to: