What does spss look like

The Values attribute allows you to create a list of value labels. Often several variables will share a common set of value labels, and in this window you can copy and paste value label sets. Variable labels are set by simply typing them in, value labels work through a dialog box. The Missing attribute is a place for you to designate certain data values that you want SPSS to ignore when it calculates statistics. For instance, in survey data it is common practice to record a data value of 8 when a respondent says "I don't know" in response to a question, and you can have SPSS treat the 8's in a variable as if they were missing data.

The other attributes, Width , Decimals , Columns , Align , Measure , and Role , are minor settings related to data display. Although Measure level of measurement is statistically a very important concept, it has little meaning within the SPSS software. The Output Viewer collects your statistical tables and graphs, and gives you the opportunity to edit them before you save or print them. The Output Viewer is divided into two main sections, an outline pane on the left, and a tables pane on the right.

When you print your output, it is the tables pane that is printed. When SPSS creates output tables, syntax, error messages, etc. Individual objects may be opened and edited, deleted, hidden, rearranged, or printed. To select an object to work with, you can either click on it in the tables pane, or click on the corresponding entry in the outline pane.

A red arrow appears next to the object in both panes. To edit objects , double-click on them in the tables pane. Depending on whether you are trying to edit a simple object like a title which is just a box with some text in it , or something more complicated like a table or a graph, you may be able to simply change the object in the Output Viewer, or another window may open.

Except for editing the look of graphs, it will often be easier to edit your output by exporting it to Microsoft Word first, but in principle you can change anything you can see in your output, down to deleting columns and changing numbers. But if your intent is to fake your results, you should attend our Simulations workshop for better methods of doing this.

To delete objects , select them in either pane and use the Delete key. To hide objects , double-click on the icon for each object in the outline pane. To make them visible, just double-click again. You can hide a whole section of the outline by clicking on the minus sign to the left of the group in the outline pane.

Hidden objects are not printed, but are saved with the output file. To rearrange objects , select the object or group of objects in either pane, and drag them until the red arrow points to the object below which you want them to appear.

To export your output , you go through a special procedure. There are three main settings to look at. Next, check that you are exporting as much of your output as you want, the Objects to Export at the top of the dialog. If you have a part of your output selected, this option will default to exporting just your selection, otherwise you typically will export all your visible output.

But you don't have to memorize a whole new language in order to paste and run SPSS syntax. The fundamental unit of work in the SPSS language is the command: think of commands as analogous to well-formed sentences. In this language, commands begin with a keyword and end with a period.

Commands should begin in the leftmost column in the editor. If they are wrapped onto more than one line, the continuing lines should begin with a blank space. Capitalization does not matter. Like the Output Editor, the Syntax Editor has two panes. The tables pane on the right is what is actually saved in the. Running syntax. To have SPSS actually carry out your command s , you must run them. Click Run , and then one of the menu options.

There is also an icon on the Toolbar to run your program, a right-facing triangle "play". You can run all the commands in the editor, or select a group of commands and run just that be careful that you highlight full commands, from the first keyword through the final period.

You can also run the current command, which is whatever command the cursor is located within. Pasting and running. From most dialog boxes you have the option of pasting commands instead of simply running them.

The syntax tends to be verbose, specifying many options that are the defaults - syntax you write yourself tends to be much shorter and simpler. After you have pasted a command, you still need to run it to get any output.

It covers common statistics, regression, and graphs. For instance, our first record seems to contain a male respondent from and so on. A more detailed explanation on the exact meaning of our variables and data values is found in a second sheet shown below. An SPSS data file always has a second sheet called variable view.

It shows the metadata associated with the data. Metadata is information about the meaning of variables and data values. Right, so SPSS can open all sorts of data and display them -and their metadata- in two sheets in its Data Editor window.

So how to analyze your data in SPSS? Doing so opens a dialog box in which we select one or many variables and one or several statistics we'd like to inspect. It holds a nice table with all statistics on all variables we chose. The screenshot below shows what it looks like. As we see, the Output Viewer window has a different layout and structure than the Data Editor window we saw earlier. SPSS Output items, typically tables and charts, are easily copy-pasted into other programs.

Tables are usually copied in rich text format, which means they'll retain their styling such as fonts and borders. The screenshot below illustrates the result.

Now, SPSS has a second option for running this or any other command: we can open a third window, known as the syntax editor window. This tutorial walks you through with some examples. We'll point out some tricks, pitfalls and alternatives as well. This tutorial presents a quick overview of what SPSS looks like and how it basically works.

Read more It shows our data so we can visually inspect it. Effect Size — A Quick Guide Effect size is an interpretable number that quantifies the difference between data and some hypothesis. This simple tutorial quickly explains the basics with outstanding illustrations and examples. SPSS Missing Values Tutorial In SPSS, missing values refer to system missing values: values that are absent from the data; user missing values: values that are present in the data but must be excluded from analyses.

SPSS Variable Types and Formats SPSS has 2 types of variables: numeric variables contain only numbers and can be used for calculations; string variables contain text and cannot be used for calculations. This tutorial walks you through the basics and some FAQ's such as how to remove cases based on 2 variables instead of one?

Three common ways to find outliers are inspecting histograms ; inspecting boxplots ; inspecting z-scores.