The assumption of equal intervals says that all distances between adjacent answer categories are equal in the repondents’ perception. This assumption is an attempt to justify treating ordinal variables as if they were metric variables. Doing so enables one to compute means, standard deviations and Pearson correlations on ordinal variables. This is simpler than using more appropriate techniques. Assumption of Equal […]
Many easy options have been proposed for combining the values of categorical variables in SPSS. However, the real information is usually in the value labels instead of the values. This tutorial proposes a simple trick for combining categorical variables and automatically applying correct value labels to the result. SPSS Combine Categorical Variables Example You may follow along by downloading and opening hospital.sav. Now say […]
Summary This tutorial shows how to create nice tables and charts for comparing multiple dichotomous or categorical variables. We recommend following along by downloading and opening freelancers.sav. The question we’ll answer is in which sectors our respondents have been working and to what extent this has been changing over the years 2010 through 2014. Variables sector_2010 through sector_2014 contain the necessary information. SPSS Frequency […]
This tutorial shows how to create nice tables and charts for comparing multiple dichotomous variables. If statistical assumptions are satisfied, these may be followed up by a McNemar test (2 variables) or a Cochran Q test (3+ variables). We’ll use the freelancers.sav data throughout. SPSS DESCRIPTIVES Table The simplest way to compare multiple dichotomous variables is simply running DESCRIPTIVES: as long as […]
When analyzing your data, you sometimes just want to gain some insight into variables separately. The first step in doing so is creating appropriate tables and charts. This tutorial shows how to do so for dichotomous or categorical variables. We recommend you follow along by downloading and opening smartphone_users.sav. SPSS Frequency Tables We’d like to know which smartphone brands were […]
Introduction When reporting on data, we usually summarize our variables. The most basic way for doing so is presenting their frequency distributions. Visualizing these as histograms tends to give immediate insight into what a variable ‘looks like’, especially when many distinct values are present. However, frequency distributions often provide more detail than we actually need. […]
Summary This tutorial will investigate the association between metric variables with nice tables and charts. As an example, we’ll use income_2010 and income_2011 from freelancers.sav. Quick Data Check Before jumping into analyses, let’s first just inspect whether both variables have plausible values. A fast way for doing so is generating a histogram by running FREQUENCIES. The syntax below does just that. […]
Summary This tutorial shows how to run nice tables and graphs for investigating the association between a metric and a categorical variable. If statistical assumptions are met, these may be followed up by an ANOVA. As an example, we’ll use freelancers.sav and see whether (and how) sector_2010 is related to income_2010. Data Inspection and FILTER We’ll first inspect FREQUENCIES for sector_2010 by running the syntax below […]
Summary This tutorial shows how to create nice tables and charts for studying the association between a dichotomous and a metric variable. If statistical assumptions are met, these may be followed up by an independent samples t test. As an example, we’ll investigate whether there’s an association between income_2010 and gender in freelancers.sav: is the average income over 2010 equal for […]
This tutorial walks through running nice tables and charts for investigating the association between categorical or dichotomous variables. If statistical assumptions are met, these may be followed up by a chi-square test. As an example, we’ll see whether sector_2010 and sector_2011 in freelancers.sav are associated in any way. SPSS Quick Data Check Before doing anything else, let’s first just take a quick […]
Summary Creating dummy variables for several categorical variables by basic syntax is usually not hard. However, applying proper variable labels to the newly created dummy variables requires quite a bit of effort. The tool presented in this tutorial will take care of this -and some other issues- more easily. SPSS Dummy Variables Tool SPSS Create Dummy Variables Tool Instructions […]
Dummy coding a variable means representing each of its values by a separate dichotomous variable. These so-called dummy variables contain only ones and zeroes (and sometimes missing values). The figure below shows how the variable “pet” from favorite_pets.sav has been dummy coded as pet_d1 through pet_d4. Dummy Variables in SPSS Note that, for example, pet_d2 represents the value 2 on […]
