# Measure relationship between two variables spss student

### What statistical analysis should I use? Statistical analyses using SPSS

The mean of the variable write for this particular sample of students is , which you want to see if there is a relationship between two categorical variables. . You would perform a one-way repeated measures analysis of variance if you. Research question type: Relationship between 2 variables The relationship is measured by a quantity A dietetics student wanted to look at the relationship between calcium intake and knowledge or in SPSS, as right, using the. Graphs >. A simple correlation measures the relationship between two variables. Data for several hundred students would be fed into a regression statistics program I have created a sample SPSS regression printout with interpretation if you wish to .

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.

## Pearson's Product-Moment 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. 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.

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.

In this example, female has two levels male and female and ses has three levels low, medium and high. While other types of relationships with other types of variables exist, we will not cover them in this class. A canonical correlation measures the relationship between sets of multiple variables this is multivariate statistic and is beyond the scope of this discussion.

### Data Analysis - Pearson's Correlation Coefficient

Regression An extension of the simple correlation is regression. In regression, one or more variables predictors are used to predict an outcome criterion. Data for several hundred students would be fed into a regression statistics program and the statistics program would determine how well the predictor variables high school GPA, SAT scores, and college major were related to the criterion variable college GPA. Not all of the variables entered may be significant predictors.

R2 tells how much of the variation in the criterion e. The regression equation for such a study might look like the following: For example, someone with a high school GPA of 4. Universities often use regression when selecting students for enrollment. I have created a sample SPSS regression printout with interpretation if you wish to explore this topic further.

## What statistical analysis should I use? Statistical analyses using SPSS

You will not be responsible for reading or interpreting the SPSS printout. Non Parametric Data Analysis Chi-Square We might count the incidents of something and compare what our actual data showed with what we would expect. Suppose we surveyed 27 people regarding whether they preferred red, blue, or yellow as a color.

- ANOVA, Regression, and Chi-Square
- Spearman's Rank-Order Correlation using SPSS Statistics

If there were no preference, we would expect that 9 would select red, 9 would select blue, and 9 would select yellow. We use a chi-square to compare what we observe actual with what we expect. If our sample indicated that 2 liked red, 20 liked blue, and 5 liked yellow, we might be rather confident that more people prefer blue. If our sample indicated that 8 liked read, 10 liked blue, and 9 liked yellow, we might not be very confident that blue is generally favored.

**SPSS 24 Tutorial 9: Correlation between two variables**

Chi-square helps us make decisions about whether the observed outcome differs significantly from the expected outcome. Just as t-tests tell us how confident we can be about saying that there are differences between the means of two groups, the chi-square tells us how confident we can be about saying that our observed results differ from expected results.

In Summary Each of the stats produces a test statistic e.

Ultimately, we are interested in whether p is less than or greater than. It all boils down the the value of p. Model Building Thanks to improvements in computing power, data analysis has moved beyond simply comparing one or two variables into creating models with sets of variables. Structural Equation Modeling SEM analyzes paths between variables and tests the direct and indirect relationships between variables as well as the fit of the entire model of paths or relationships.

For example, a researcher could measure the relationship between IQ and school achievment, while also including other variables such as motivation, family education level, and previous achievement.