Statistical Package of Social Science used for analysis of data it is the set of software programs that are combined together in a single package

1. SPSS
Statistical package for the social sciences

2. MEANING
• SPSS (Statistical package for the social sciences) is the set of
software programs that are combined together in a single
package
• The basic application of this program is to analyze scientific
data related with the social science.

3. • This data can be used for market research, surveys, data
mining, etc.
• The SPSS software package was created for the management
and statistical analysis of social science data.

4. USES OF SSPS
• SPSS provides an efficient and organized way to manage large
and complex data sets and perform advanced statistical
analysis.
• SPSS can be used for various purposes, including data
management, data analysis, and data visualization.

5. • SPSS is revolutionary software mainly used by research
scientists which help them process critical data in simple steps
• Working on data is a complex and time consuming process, but
this software can easily handle and operate information with
the help of some techniques.

6. FESTURES OF SPSS
• Trend analysis, assumptions, and predictive models are some
of the characteristics of SPSS.
• It is easy for you to learn, use and apply. It helps to get data
management systems and editing tools handy.

7. • • Modeler program that allows for predictive modeling. It
enables researchers to build and validate predictive models
using advanced statistical procedures.
• • Text analysis helps you derive insights from qualitative
inputs through open-ended questionnaires.

8. • • Visualization Designer allows researchers to use their data
for a variety of visual representations.
• • Using SPSS features, users can extract every piece of
information from files for the execution of descriptive,
inferential, and multiple variant

9. Types of data in SPSS
• Metric data is any reading which is at least have an interval
scale.
• As opposed to Non Metric data which can be nominal or
ordinal. Eg: weight, height, distance, revenue, cost etc., all of
them are interval scales or above.

10. Preparation of data in SPSS
• Click the Variable View tab. Type the name for your first
variable under the Name column.
• Click the Data View tab.
• Now you can enter values for each case.
• Repeat these steps for each variable that you will include in
your dataset.

11. Finding outliners
• The first way to identify outliers in SPSS is through graphical
representations such as boxplots and scatterplots. A box plot is
a graphical representation of the distribution of a dataset,
which displays the minimum, first quartile, median, third
quartile, and maximum.

12. Uploading in SPSS
• Import a CSV data file into SPSS, begin by clicking File > Open >
Data. In the Open Data window, change Files of type to “CSV
(*. Csv)”. Locate your file and click on it to select it, then click
OK.