## SPSS

### What is ANALYTICS?

The purpose of analytics is to take existing data collected from either a single source or multiple sources and use it to arrive at the optimal decision. Essentially, analytics can be best defined as a science of analysis.

Commonly, one of the most frequent uses of analytics is in the field of business. Managers or researchers for an analytics company can use various data mining techniques combined with historical patterns to make predictions about the performance of a particular market or business.

10 most popular analytic tools in business

Business analytics is a fast growing field and there are many tools available in the market to serve the needs of organizations. The range of analytical software goes from relatively simple statistical tools in spreadsheets (ex-MS Excel) to statistical software packages (ex-SAS, SPSS).
To sophisticated Business Intelligence suites (ex-SAS, Oracle, SAP, IBM among the big players).

### Data File Creation and Data Processing.

Create, Edit, and Save SPSS Data File
Delete Data Values and Declare Missing Values
SPSS Data Editor
Label Values for a Variable and Save Data File
Importing & Exporting file from different source

### Data Manipulation.

Merging
Splitting
Selecting Cases
Data Transformation

### Descriptive Statistics.

Mean, Standard Deviation, Histogram, Boxplot, Stemplot, Normality Test, Frequency Table, Bar Chart, Pie Chart
Scatter Plot
Cross Tabulation (Contingency Table), Cluster Bar Chart
Means for Subgroups and Side-by-side Boxplot
Line Chart for Time Series Data

### Inference on One Population.

Confidence Interval Estimate for Population Mean
One Sample t-Test for Population Mean
Confidence Interval Estimate for Population Proportion

### Two Independent Samples t-Test.

Two Independent Samples t-Test Procedure
Tests of Normality from Two Samples
Interpretation of SPSS Output

### Paired Sample t-Test and Normality Check.

Paired Sample t-Test
Normality Test for the Paired-Difference

### One-way ANOVA and Multiple Comparisons.

Basic learning/mining tasks
Inferring rudimentary rules: 1R algorithm
Decision trees
Covering rules
Experiments with Weka – decision trees, rules

### Data mining algorithms: Prediction

One-way ANOVA
Interpretation of SPSS Output on One-way ANOVA

### Nonparametric Tests.

Sign (Binomial) Test
Wilcoxon Signed Rank Test
Wilcoxon Rank Sum Test

### Chi-Square Tests and Contingency Tables.

Chi-square Test of Independence for Organized Data (Weight Cases)
Chi-square Test of Independence for Un-organized Data
Interpret SPSS Output for Chi-square Test

### Correlation & Regression.

Correlation & Regression
Simple Linear Regression, Prediction, Residual Plot

### Logistic Regression.

Logistic Regression: Variables Definitions
Logistic Regression: Use of SPSS and Interpretation of the
Logistic Regression: Interpretation of Odds Ratio
Logistic Regression: Probability Estimation

### What is SPSS?

SPSS (Statistical Package for the Social Sciences) is a computer application that provides statistical analysis of data. It allows for in-depth data access and preparation, analytical reporting, graphics and modelling.
Please note that in 2009 SPSS Inc. decided to change their product name from SPSS to Predictive Analytics Software (PASW) More analytical power can be added by using optional PASW (SPSS) modules.
A commercially produced statistical software package that is widely used in the fields of Education and Psychology.

### SPSS Strengths.

Easily opens data from other programs such as Excel and SAS.
Variable view screen allows for quick overview of file contents and allows for easy modifications of names, formats, labels, and variable order.
Having all data information in a single file allows sharing files on a project to be very easy.
Point-and-click menus do not require memorizing syntax for majority of procedures.
Many procedures can be expanded beyond the menu options in syntax.
Split-file command allows all output to be replicated for various groups through a single command.
Journal file tracks all commands used for life of program, with good resources to find code accidentally deleted.