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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.

  • One-way ANOVA/li>
  • 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.