The following topics will be covered as part of this series. Each topic is described in detail with hands-on exercises done on SPSS to help students learn with ease. We will cover all the nitty-gritty that you need to know to get started with SPSS along with the correction and handling of errors as and when they pop-up. The program builds a solid foundation by covering the most popular and widely used data science technologies and its applications.
The topics that are covered in this tutorial are as follows:
Introduction to Analytics
Understanding Probability and Probability Distributions
Introduction to Sampling Theory and Estimation
Introduction to Segmentation Techniques: Factor Analysis in SPSS
Introduction to Segmentation Techniques: Cluster Analysis in SPSS
Correlation and Linear Regression in SPSS
Introduction to categorical data analysis and Logistic Regression in SPSS
Introduction to Time Series Analysis
Statistical Significance T Test Chi Square Tests and Analysis of Variance.
PhD Research Scholars who need a knowledge of SPSS for their research and coursework will have a complete knowledge of the tool.
No prior knowledge required