BUSINESS ANALYTICS USING SPSS

BUSINESS ANALYTICS
USING SPSS

COURSE ID – DBAL-102     DURATION – 32 Hours

 
Program Objective
SPSS is most widely used tool in the field of Quantitative market research. This course encompasses basic statistical concepts to advanced analytics and predictive modeling techniques. In-depth knowledge of core concepts will be covered in the course along with implementation on varied industry use-cases
After the completion of Business Analytics using SPSS course, you will be able to:

  • Use SPSS to get the data files into SPSS, File handling, transformations, output with other data preparation and data manipulation
  • Use SPSS to calculate Frequencies, Descriptives and Crosstabs
  • Use SPSS to perform statistical methods
  • Use SPSS to perform advanced/Predictive analytics
  • Work on end to end data science projects using SPSS
Who Should do this course?
This Business Analytics using SPSS certification course is for all those aspirants who want to switch into the field of business analytics and are keen to enhance their technical skills with exposure to cutting-edge practices
The Students/professionals/Candidates from various quantitative backgrounds, like Engineering, Finance, Maths, Statistics, Business Management who want to head start their career in analytics.
Pre-requisites
There are no prerequisites for this course. Knowledge of any programming and data analytics exposure would be an advantage. For beginners, its highly recommend to complete the “Data Analytics using Excel – Tableau” course prior to this course.
Modules & Topics

SPSS

  • Introduction to SPSS Software
  • Data files and Editor in SPSS
  • Data preparation and transformations
  • Working with command syntax
  • File handling, transformations and output
  • Frequencies, Descriptive, Explore, Crosstabs

Basic & Advanced Statistics

  • T tests and paired t-tests
  • ANOVA and Chi-Square
  • Bivariate and partial correlations
  • Factor analysis
  • Cluster analysis (Hierarchical and K-Means)
  • Linear regression (simple and multiple)
  • Logistic regression
  • Predictive Analytics

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