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 In SPSS, TEMPORARY indicates that the commands that follow are temporary. Temporary commands will be undone (reversed) when a command is run that reads the data. Such a command also indicates that the commands that follow are not temporary anymore. Temporary commands between TEMPORARY and a command that reads the data. SPSS Temporary Example “We’d like to dichotomize […]
SPSS doesn’t offer an easy way to set decimal places for output tables. This tutorial proposes a very simple tool for setting decimal places in basic output tables after they’ve been produced. It works best for simple tables such as DESCRIPTIVES, MEANS or CROSSTABS. Setting Decimal Places for Output Tables First, make sure that the SPSS Python Essentials are installed and […]
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 […]
SPSS CROSSTABS produces contingency tables: frequencies for one variable for each value of another variable separately. If assumptions are met, a chi-square test may follow to test whether an association between the variables is statistically significant. This tutorial, however, aims at quickly walking through the main options for CROSSTABS. We’ll use freelancers.sav throughout this tutorial as a test data […]
Introduction Having a basic understanding of SPSS numeric variables allows you to work fast and with a sense of confidence. This tutorial aims at accomplishing just that by pointing out some essential basics. You may follow along with this tutorial by downloading and opening hospital.sav. SPSS Numeric Variables – What Are They? Numeric variables are one of […]
Summary SPSS uses a handful of hidden variables for keeping track of things. These so called system variables have names starting with “$” and can be useful in some cases. The most important one is $casenum, the number shown next to each case in the data editor window. SPSS $casenum SPSS $casenum In the left outline of the […]
Most of this tutorial aims at getting you started fast and smoothly with SPSS syntax. But before doing so, let’s briefly point out some major reasons why working from syntax is the single best practice for SPSS.* SPSS Syntax – Some Advantages Your syntax file tells you exactly what you’ve done so far with your data. It holds all details of […]
9. Missing Values per Case (Overview and data file are are found here) Missing values complicate some analyses or may sometimes indicate that respondents didn’t fill out the questionnaire very seriously. In any case, it’s a good idea to at least check how missing values are distributed over respondents and we often do so for sections […]
6. Inconvenient Distributions (Overview and data file are are found here) Let’s first state this clearly: we don’t exclude variables simply because their distributions are not to our liking. What we mean by “inconvenient distributions” are variables that don’t really provide us with useful information. This point is perhaps best explained by an example. Let’s inspect q4. […]
5. Presence of User Missing Values (Overview and data file are are found here) User missing values are values that we want to exclude from analysis. We do so by specifying (ranges of) values as “missing” in SPSS. For ordinal variables, we typically exclude answers such as “Don’t know” or “Not applicable”. For metric variables, we exclude values that are not […]
Summary (Overview and data file are are found here) SPSS has two variable types: string variables and numeric variables. String variables have “String” under Type in Variable View. All other variables are numeric. The screenshot below illustrates this point for hotel_evaluation.sav. 3. Undesirable Variable Types A problem with some data files is that they contain string variables that should have been numeric. A […]
1. SPSS Case Count and Variable Count (Overview and data file are are found here) The very first thing we want to know about basically any data file, are its dimensions: how many cases and how many variables does it contain? For a quick case count, select any cell in data view and press the CTRL + shortkey. Alternatively, just […]
Before you start analyzing real-world data, make sure you have a basic idea what your data look like. How many cases and variables do you have? Do their frequency distributions look plausible? Do you have any string variables and do you need to set any missing values? A quick data inspection takes little time and effort and may save you […]
Do you think running a two-way ANOVA with an interaction effect is challenging? Then this is the tutorial for you. We’ll run the analysis by following a simple flowchart and we’ll explain each step in simple language. After reading it, you’ll know what to do and you’ll understand why. We’ll use depression.sav throughout. The screenshot below shows it in variable […]
One of the best known charts is a simple bar chart containing frequencies or percentages. The easiest way to run it in SPSS is the FREQUENCIES command. This tutorial walks you through some options. We’ll use freelancers.sav throughout, part of which is shown below. Option 1: FREQUENCIES In most cases, a simple FREQUENCIES command is our best option because it takes multiple […]
Independent Samples T-Test – What Is It? Null Hypothesis Test Statistic Assumptions Statistical Significance Effect Size Independent Samples T-Test – What Is It? An independent samples t-test evaluates if 2 populations have equal means on some variable.If the population means are really equal, then the sample means will probably differ a little bit but not […]
In SPSS, SELECT IF deletes cases (rows of data) that don’t satisfy some condition(s). Like so, SELECT IF basically means “don’t delete if …” A minimal example isSELECT IF(GENDER = 1). SPSS SELECT IF – Some Examples Say we collected data on our employees and the resulting data file is employees.sav. Our client is only interested in female […]
For testing moderation effects in multiple regression, we start off with mean centering our predictors:mean centering a variable is subtracting its mean from each individual score.After doing so, a variable will have a mean of exactly zero but is not affected otherwise: its standard deviation, skewness, distributional shape and everything else all stays the same. After mean […]
