SPSS Main Features – A Quick Overview

SPSS is used to edit and analyze many qualitative data for different sources. SPSS is also used to run different inferential statistics such as t-test ANOVA, reliability analysis, predicting models (regression) and factor analysis.

Opening Data Files in SPSS:

SPSS uses its own data file format(.sav). Besides its own data file, SPSS can open different file formats which include MS Excel files(.xls), plain text files(.txt), Relational database files (SQL), Stata and SAS.

Editing Data in SPSS:

editing and cleaning before they can be analyzed. SPSS performs different complex tasks with amazing efficiency by restricting data. Examples of these tasks are creating means and sums as new variables and performing operations on missing values. SPSS also contains different numeric functions, string functions, and date functions.

We are done with SPSS introduction and now Let’s move to see how SPSS looks and feels like.

There are two views in SPSS as shown in below figure.

Data View

Variable View

SPSS Data View:

SPSS data similar to likes spreadsheet, which has columns and rows. We enter the data in data view and we declare variables in the variable view.

I have opened the accidents.sav file from SPSS sample files. The above screen shoot shows the data displays data values. For instance, the top to down numbers are representing the individual samples of data and right to left columns shown the different variables. The columns agecat, gender, accid and pop are variables. SPSS reads data files are in numeric forms than string. Therefore, it is always better to convert strings data into the numeric. For example, if a surrey question contains answers like the male, female or uses any Likert scale then convert it to numeric values like Yes = 1, No = 2. In case of Likert scale use 1 to 5 or suitable numbers according to defined scales

SPSS Variable View:

SPSS Variable View is used to see and edit variable in your data set. In variable view each column of the Data View is described by a row of the Variable View. The rows in variable view defines different variables and columns in variable view are different attributes of variables.

Name: Enter the Unique Identifiable and Sorting Variable Name, Eg: In the Data of Post Graduate Students, The Variables can be Student_ID, Gender, Age, Degree,Hobbies Etc, There are certains restriction while naming variables. Which does not allow any special character, Space between words while describing the variables. SPSS automatically generates the other information of variable after defining its name.

Type: There are different types of variables. Which can be changed at a time. These includes Numeric, String, Date, Custom Currency, Comma, Dot, Scientific notation, Dolor and restricted numbers

Width: Allows us to define the character width of Variable, if we want to get mobile numbers, we must limit variable width to 10.

Decimal: It is used in case of percentages, where we need to define the decimal point to display.

Label: Because there is certain restriction in name attribute, in label you can use special characters or space.

Value: The value attribute is used to give label option of a questionnaire. In case of a five-point Likert scale, we can label 1 = Strongly Agree, 2 = Agree, 3 = Uncertain, 4 = Disagree and 5 = to Strongly Disagree.

Missing: We can declare any number as a missing value and SPSS won’t consider it in calculations.

Align: The Alignment of data can be Left, Right and Middle.

Measure: There are three types of the variable, Ordinal, Nominal and Scale. Measure attribute is used to define type of variable.

TIP: All the attributes of variable can be copied, and you can paste on other similar variable to save the time.

SPSS Data Analysis:

SPSS opens different types of data and displays in the data view. So, the basic question every student asks is how to analyze your data in SPSS?

The simplest and easiest option is to use SPSS menu options.

Let’s dive deeper into SPSS data analysis, click on the analyze menu than descriptive statistics. Which will show you different options, then click on descriptive?

The first variable is age and we can calculate the average age. When use clicks on descriptive it will show you descriptive options. Check the mean and standard deviation option then press continue and then press ok.

SPSS Output Window:

When you click Ok, a new window will open, which is SPSS’ output window. The SPSS output window shows a nice table that has a ages variable and its calculated values for Mean (35.39) and Standard Deviation (7.948).

Is SPSS easy to use?

Yes, It is, follow our tutorial to learn more.

Interpreting SPSS output Tables:

Our tutorials and videos will help you understand the tables and graphs that SPSS Statistics generates while analyzing your data. SPSS Statistics produces different tables of output for the typical statistical tests you run, we tell show you by examples which tables are relevant, and which can be used in the writeup, while ignoring the others.

Presenting SPSS data in graphs and charts:

Witting results is not the only a way for academic researchers, they often need to illustrate the results by using different charts and graphs. Producing properly labeled and formatted graphs and charts take time, so we will show you how to use SPSS for building different graphs and charts.

Writing up SPSS results:

The final stage up the results in the appropriate format. When it comes to writing up your SPSS results for the research paper and thesis, we use the APA style and a general reporting style is used for other purposes.


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