What is SPSS?
SPSS stands for “Statistical Package for the Social Sciences”. It is an IBM tool. This tool first launched in 1968. This is one software package. This package is mainly used for statistical analysis of the data.
SPSS is mainly used in the following areas like healthcare, marketing, and educational research, market researchers, health researchers, survey companies, education researchers, government, marketing organizations, data miners, and many others.
It provides data analysis for descriptive statistics, numeral outcome predictions, and identifying groups. This software also gives data transformation, graphing and direct marketing features to manage data smoothly.
Why SPSS?
They came under IBM SPSS Statistics, and most of the users refer to it as SPSS only.
It is straight forward, and its English-like command language helps the user to go through the flow.
SPSS introduces the following four programs that help researchers with their complex data analysis needs.
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Statistics Program
SPSS’s statistics program gives a large amount of basic statistical functionality; some include frequencies, cross-tabulation, bivariate statistics, etc.
Modeler Program
Researchers are able to build and validate predictive models with the help of advanced statistical procedures.
Text Analytics for Surveys Program
It gives robust feedback analysis. which in turn get a vision for the actual plan.
Visualization Designer
Researchers found this visual designer data to create a wide variety of visuals like density charts and radial box plots.
Features of SPSS
- The data from any survey collected via Survey Gizmo gets easily exported to SPSS for detailed and good analysis.
- In SPSS, data gets stored in.SAV format. These data mostly comes from surveys. This makes the process of manipulating, analyzing and pulling data very simple.
- SPSS have easy access to data with different variable types. These variable data is easy to understand. SPSS helps researchers to set up model easily because most of the process is automated.
- After getting data in the magic of SPSS starts. There is no end to what we can do with this data.
- SPSS has a unique way to get data from critical data also. Trend analysis, assumptions, and predictive models are some of the characteristics of SPSS.
- SPSS is easy for you to learn, use and apply.
- It helps in to get data management system and editing tools handy.
- SPSS offers you in-depth statistical capabilities for analyzing the exact outcome.
- SPSS helps us to design, plotting, reporting and presentation features for more clarity.
Statistical Methods of SPSS
Many statistical methods can be used in SPSS, which are as follows:
- Prediction for a variety of data for identifying groups and including methodologies such as cluster analysis, factor analysis, etc.
- Descriptive statistics, including the methodologies of SPSS, are frequencies, cross-tabulation, and descriptive ratio statistics, which are very useful.
- Also, Bivariate statistics, including methodologies like analysis of variance (ANOVA), means, correlation, and nonparametric tests, etc.
- Numeral outcome prediction such as linear regression.
It is a kind of self-descriptive tool which automatically considers that you want to open an existing file, and with that opens a dialog box to ask which file you would like to open. This approach of SPSS makes it very easy to navigate the interface and windows in SPSS if we open a file.
Besides the statistical analysis of data, the SPSS software also provides data management features; this allows the user to do a selection, create derived data, perform file reshaping, etc. Another feature is data documentation. This feature stores a metadata dictionary along with the data file.
Types of SPSS
It has two types of views those are Variable View and Data View:
Variable View
- Name: This is a column field, which accepts the unique ID. This helps in sorting the data. For example, the different demographic parameters such as name, gender, age, educational qualification are the parameters for sorting data.
The only restriction is special characters which are not allowed in this type. - Label: The name itself suggests it gives the label. Which also gives the ability to add special characters.
- Type: This is very useful when different kind of data’s are getting inserted.
- Width: We can measure the length of characters.
- Decimal: While entering the percentage value, this type helps us to decide how much one needs to define the digits required after the decimal.
- Value: This helps the user to enter the value.
- Missing: This helps the user to skip unnecessary data which is not required during analysis.
- Align: Alignment, as the name suggests, helps to align left or right. But in this case, for ex. Left align.
- Measure: This helps to measure the data being entered in the tools like ordinal, cardinal, nominal.
The data has to enter in the sheet named “variable view”. It allows us to customize the data type as required for analyzing it.
To analyze the data, one needs to populate the different column headings like Name, Label, Type, Width, Decimals, Values, Missing, Columns, Align, and Measures.
These headings are the different attributes which, help to characterize the data accordingly.
Data View
The data view is structured as rows and columns. By importing a file or adding data manually, we can work with SPSS.
SPSS Installation Guide
First of all, we need to check the minimum system requirements at the SPSS Statistics System Requirements.
Then the option selects the Operating system loaded on your system and figure out the prerequisites.
Open browser for the SPSS website; this will lead to the downloading software application. Start with the SPSS free trial version.
Following are the Steps for importing Excel file into SPSS.
The first step is to click on File
=> Open
=> Select Data
=> Dialog Box
=> Files of type
=> .xls file.
After selecting the excel file that will be imported for performing the data analysis, we need to ensure that in the dialog box that we selected is “read variable names from the first row of data”.
And at the end, click OK. Your file has now imported in SPSS.
Conclusion
The bottom line is though Excel offers a good way of data organization, SPSS is more suitable for in-depth data analysis. This tool is very useful in the analysis and visualization of data.
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