- Bachelors Students (Completed or Pursuing) from any background
- Masters students (Completed or Pursuing) from any background
- Professionals working from any background
Syllabus of Program :
Introduction to Statistics
- What are statistics?
- Types of statistics- descriptive and inferential statistics.
- Basics of SPSS and R
- Graphical representation on SPSS and R.
- Use of different Graphs
- What are parametric techniques?
- Correlation- What is correlation? Types of correlation. Why do we use correlation? Doing correlation on R. Doing correlation on SPSS
- Regression analysis- What is Regression? Types of Regression analysis. Why do we use regression analysis? Doing regression analysis on R. Doing regression analysis on SPSS.
- ANOVA- What is anova? Analysis of variance and multiple analysis of variance. Why do we use it? Doing ANOVA on R. Doing ANOVA on SPSS
- Student’s t- What is t? Why o we use it? Doing t on R. Doing t on SPSS
- Moderation and Mediation- what are moderator and mediator? Why do we use them? Using R and SPSS for mediation and moderator.
- Factor Analysis – what is factor analysis? Why do we use it? Using R and SPSS for factor analysis
- What is non-parametric statistics?
- Mann Whitney U- what is Mann Whitney U? Why do we use it? Using R and SPSS for Mann- Whitney U
Key Learnings of the Program :
- Students will be able to understand the concept of statistics.
- Students will be able to understand and use parametric and nonparametric techniques to analyze the data.
- Students will able to apply different techniques with data to analyze and describe the data
- Students will able to use SPSS and R as software for analysis