1. Introduction to Statistics and Data Analytics - Sample Vs. Population, Variables and Types of Data, Primary & Secondary Data, Data Collection and Sampling Techniques

1. Descriptive Statistics - Measure of Central Tendency - Mean, Median, Mode, Measure of Variance - Range, Inter Quartile Range, Variance & Standard Deviation, Coefficient of Variation, Dispersion, Kurtosis, Skewness, Chebyshev's Theorem, Measures of Positions - Percentile, Deciles, Quartiles.

2. Introduction to Random Variables (Discrete and Continuous Random Variables), Exploratory Data Analysis, Frequency Tables and Frequency Distributions, Type of Graphs

3. Inferential Statistics & Hypothesis Testing - Formulation of Hypothesis Statement, p-value, Type I and Type II Errors, Z-Test, t-Test, Chi-Square Test

4. Introduction to Statistical Estimation and Confidence Interval 

5. Probability Theory - Introduction to Probability Theory & Counting Rules

6. Probability Distributions - Discrete and Cumulative Probability Distribution, Sampling Distribution, Binomial Distribution, Standard Normal Distribution, Poisson Distribution. 

7. Chi-Square, F- Distribution, and ANOVA (One - Way and Two-Way ANOVA) 

8. Correlation and OLS/Multiple Regression (Logistic and Linear Regression) 
 

1. Statistical Analysis using Excel

2. Introduction to R software, and Statistical Analysis using R

3. Introduction to Tableau & its application in Analytics

4. Introduction to Python and its application in Analytics