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**What is SPSS?****Where is it used?****Extension and Import of data from other software:****The Initial Screen of SPSS:****The Toolbar:****The Menu bar:**- File: It works as a normal File option just like other software, where we can open, read, and save a file.
- Edit: With this one can copy, paste, find, and replace.
- View: It gives the option of how the screen will appear.
- Data: Gives access to varieties of operations like entering and defining the data. With Data, we can also sort cases, merge files, aggregate filed, select cases, etc.
- Transform: With this, we can transform previously entered data. It also deals with recoding, reordering, computation of new variable, and managing missing values
- Analyze: Different kinds of data analyses could be carried out with this command.
- Graphs: As the name suggests all the different types of statistical graphs could be created by using this command.
- Utilities: Allows simplification of complex data
- Add-ons: Any additional advanced statistics that isn't available in SPSS, could be added from this command.
- Windows: The format, position, and status of the windows could be adjusted with the help of this.
- Help: All kinds of help, which includes tutorials on how to analyse data using SPSS could be found here.
**Data View and Variable View:****Data View:****Variable View:**- Name: It is the name of the variable or the column name that gets displayed in the data view.
- Type: It is the type of the variable, i.e. whether it is an integer or a string or a date, etc.
- Width: The largest number or the largest string that can occur for the variable
- Decimals: The number of the desired decimal places for the variable
- Label: Label is the same as name. However, sometimes name is not enough to define the meaning of the variable, then we use the labels.
- Values: Values help us to find the levels of the variable. For example, in the case of a binary variable, male is assigned 1 and female 2, or weekday as 1 and weekend as 0 and so on.
- Missing: In rare cases, if there are missing values found for any variable, it gets reflected in this column.
- Columns: This is the space that we allow for data and labels. For wide columns, the entire variable name will be visible. In the case of narrow columns, all the variables could be seen at one time, but the variable name will tend to get truncated.
- Align: It manages the alignment. By default, a numeric value would be aligned to the right and a string variable would be aligned to the left.
- Measure: This gives details about the level of measurement. There are 3 options - nominal, ordinal, and scale.
- Role: Researchers may wish to define a variable as undesignated (Default or Input) or as a dependent variable (Target). The role column allows the user to do so.
**The Output Window:****Data Management in SPSS:**- Case Summaries: Allows proofing and editing of data.
- Replace_ Missing Values: Gives the option to replace missing values.
- Transform and Compute Variable: Transform command and Compute Variable sub command helps to create or compute new variables from existing data.
- Recode: Allows change in the coding of the variables.
- Select cases: It helps to select that part of the data which requires analysis.
- Sort cases: With this, we can re-order the data.
- Merge Files: New variables or new cases could be added to the existing file using this.
**Graphs:****Analysis in SPSS:****ANOVA analysis:****Regression Analysis:****Step 1: Analyze->Regression-> Linear****Step 2: The following screen will appear as we click on Linear option.****Step 3: We click on the Statistics button and the following window will appear:****Step 4: Click on the continue button and the Linear Regression dialogue box will open. Finally, click on OK to get the output.**

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.

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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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