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SPSS or (Statistical Product and Service Solutions) is a statistical software used for various statistical analyses. Previously, this software's full form was Statistical Package for Social Science. In 2009, IBM acquired the software.
In social science, SPSS is often used by the government body, market researcher, health industry, survey companies, data miners, and sometimes education researchers also use SPSS to analyse their data.
SPSS's extension is .sav. SPSS allows data from a variety of software, such as SQL, Excel, Python, R, SAS, etc.
The following screen gets displayed once SPSS software gets opened.
Just below the menu bar lies the toolbar. The Toolbar consists of the following options:
The menu bar is just above the toolbar and acts as the commands of SPSS. The details of the menu-bar are as follows:
At the bottom left of the SPSS window there are two options - Data View and Variable View. Let us discuss these two kinds of views.
By clicking on the data view, the data gets displayed with different variables in the columns and records in the rows.
The following figure shows how a data view would look like:
The Variable view displays the nature and specification of each variable in the data. It also shows-case whether there are any missing values variable-wise.
The following figure shows how a variable view would look like:
The different columns in the variable view are as follows:
After an analysis in SPSS, the output window gets displayed that gives us the result of the analysis process.
Data management could be done using the following tools:
Different types of high-quality statistical graphs like Histogram, Scatter Plot, Box-plot, Error bar chart, etc. could be created with the help of SPSS. The graph option in the menu bar gives us options for different types of graphs.
The analyze command in SPSS gives us many options to choose different types of statistical analysis. The following gives details of some of the analysis that could be performed in SPSS
Descriptive Statistics: To find the descriptive statistics of the data, we need to click on the Descriptive Statistics option in Analyze command. Descriptive statistics includes mean/median /mode or standard deviation/range or skewness/kurtosis, etc.
We need to follow the following steps to find the descriptive statistics of the data:
Analyze<-Descriptive Statistics->Descriptive.
Cross-Tabulation or Chi-Square analysis: In case of a relationship between two or more categorical variables, a cross-tabulation table could be considered. In SPSS we use the Crosstabs commands to do a test for independence between two categorical variables. For a Chi-Square test for independence, we can use SPSS to find the expected frequencies as well as the Chi-Square test statistic.
The following steps tell us how to execute a Cross-Tabulation:
Analyze->Descriptive Statistics->Crosstabs
One-way, Two-way, or Three-way ANOVA could be performed in SPSS. One-way ANOVA relates to a one-factor or one-independent variables, two-way ANOVA deals with two factors or two independent variables, and a three-way ANOVA model has three factors or three independent variables.
The following steps tell us how to execute ANOVA analysis:
Analyze->General Linear Model->Univariate
Simple Linear Regression, Multiple Regression Analysis, Logistic Regression, etc. could be carried out in SPSS.
In the case of Linear Regression Analysis we need to follow the following steps:
Analyze->Regression->Linear
In the case of Logistic Regression Analysis we need to follow the following steps:
Analyze->Regression->Binary Logistic
Apart from the above, there is much other statistical analysis that could be performed in SPSS
A step-by-step procedure for Multiple Regression Analysis has been given below:
Check on the box for desired result.
Exciting news for SPSS users or who really need SPSS Homework right at this moment.
the world standard for social science data analysis, SPSS is widely coveted due it's straightforward and English-like command language and impressively thorough user manual.
SPSS is used by market researchers, health researchers, survey companies, government entities, education researchers, marketing organizations, data miners, and many more for the processing and analyzing of survey data.
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