Applied Statistics Masterclass

Course Curriculum

Chapter 1: Advance Theory of Distribution

Lecture 1: Know your Instructor

Lecture 2: Concept of data distribution

Lecture 3: Uniform Distribution

Lecture 4: Binomial Distribution

Lecture 5: Theoretical Frequency Distribution vs Binomial Distribution

Lecture 6: Application of Binomial Distribution

Lecture 7: Properties of Binomial Distribution

Lecture 8: Poison Distribution

Lecture 9: Application of Poison Distribution

Lecture 10: Poisson Distribution: Partial Interval

Lecture 11: Properties of Poison Distribution

Lecture 12: Normal Distribution,Standard Normal Distribution & formulae

Lecture 13: Normal Distribution & Standard Normal Distribution

Lecture 14: Z-Score & solving Business problems

Chapter 2: Advance Correlation Analysis

Lecture 1: Concept of Correlation Analysis

Lecture 2: Scattered Diagram

Lecture 3: Karl Pearson's Correlation coefficient

Lecture 4: KP solved problem

Lecture 5: KP solved problem-2

Lecture 6: Covariance & KP correlation coefficient

Lecture 7: Properties of correlation coefficient

Lecture 8: Spearmans rank Correlation Coefficient

Lecture 9: Spearman's Correlation Solved problem

Lecture 10: Coefficient of Concurrent Deviation

Chapter 3: Regression Analysis & making predictions

Lecture 1: Concept of Linear, Multiple & Ordinal Regression

Lecture 2: Linear Regression

Lecture 3: Minimum Least Square Method

Lecture 4: Calculating coefficients values

Lecture 5: Ascombe's Quartet: Limitation of Regression Analysis

Lecture 6: Regression Equations: 'x on y' & 'y on x'

Lecture 7: Regression Solved problem-1

Lecture 8: Predicting mom's height based on daughter's height & vs

Lecture 9: Regression Solved problem-2

Lecture 10: Probable Error- Calculating correlation coefficient of POPULATION

Lecture 11: Solved Problem_Calculation of Probable Error

Lecture 12: Spurious Correlation & Coefficient of Determination

Chapter 4: Hypothesis Testing

Lecture 1: Concept of Hypothesis Testing

Lecture 2: Burden of proof

Lecture 3: Standard Error

Lecture 4: Why do we need Hypothesis testing?

Lecture 5: Difference between Std Error & std Deviation

Lecture 6: Type1 & Type 2 errors

Lecture 7: Forming Hypothesis correctly

Lecture 8: Examples-Forming Null & Alternate Hypothesis

Lecture 9: Lower, Upper & 2 tailed Test

Lecture 10: How to prove Hypothesis

Lecture 11: What if researchers set 0% error?

Chapter 5: Chi- Squared Analysis ( Non- Parametric Test)

Lecture 1: Chi-Squared Test concept clarified

Lecture 2: Further clarification of Chi-Squared Test

Lecture 3: Understanding Chi- Square Test Hypothesis

Lecture 4: Solved problem 1

Lecture 5: Solved problem 2

Chapter 6: ANOVA : Parametric Test

Lecture 1: Concept of ANOVA

Lecture 2: Degree of Freedom

Lecture 3: How to prove Hypothesis in ANOVA

Lecture 4: Calculating F cal Value

Lecture 5: Calculating F critical Value

Lecture 6: Solved problem of ANOVA

Lecture 7: AN7-1 way, 2 way & n-way Anova

Chapter 7: Time series analysis and Forecasting

Lecture 1: Concept of time series analysis

Lecture 2: Additive & Multiplicative Model

Lecture 3: Trend Analysis: Graphical Method

Lecture 4: Trend Analysis: Semi Average Method

Lecture 5: Trend Analysis: 3 Years Moving Average Method

Lecture 6: Trend Analysis: Weighted Moving Average Method