Session on Data Analytics

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Session on Data Analytics

Types of Statistics

  • Data Measurement Scales
  • Sources and Data And Types Of Data
  • Frequency Distributions- Histograms
  • Measure of Central Tendency
  • Measure of Dispersion – Range, Variation, Mean Absolute Deviation
  • Outlier Detection Using Quartiles and Boxplots

 Probability and Distributions

  • Concepts of Probability
  • Types of Probability – Classical, Relative And Subjective
  • Rules of Calculating Probability
  • Marginal, Joint and Conditional Probability Using Acontigency Table
  • Bayes Theorem And It’s Application
  • Use a Probability Tree With Sample Exercices
  • Concept of Probability Distribution
  • Types Of Probability Distribution – Discrete the Continuous
  • Binomial Distribution and its Role In Business Problems
  • Poisson Distribution and Its Uses
  • Normal Distribution and Its Role in Statistical Inferences
  • Concept Of Standard Normal Distribution And Its Role

 Basic of Sampling Distributions

  • Introduction to Sampling and Need For Sampling
  • Types of Sampling
  • Sampling Distribution
  • Concept of Standard Error

 Hypothesis Testing

  • Hypothesis Testing Procedure – Z-Test and T-Test
  • Type I and Type II Error
  • Hypothesis Testing – Univariate Case
  • Hypothesis Testing Bivariate Case

 Chi-Square Test and Analysis of Variance

  • Chi-Square Test – Goodness of Fit
  • Chi-Square Test – Test of Independence
  • ANOVA – One Way Classification
  • ANOVA- Two Way Classification
  • ANOVA and MANOVA

 Regression Analysis

  • Insights into Correlation and Coefficient
  • Scatter Diagram
  • Need For Regression
  • Assumption Involved In a Regression Model
  • Multiple Linear Regression
  • Dummy Regression
  • Limitations of Multiple Regression Model
  • Logistics Regression

 Classification Analysis

  • Decision Trees (CART)
  • Random Forests
  • Neural Networks

 Cluster Analysis

  • Iterative Portioning Clustering Methods
  • Hierarchical Clustering Method

 Association Analysis

  • Dimensionality Reduction Techniques
  • Factor Analysis
  • Discriment Analysis
  • Principal Component Analysis

Course Features

  • Lectures 0
  • Quizzes 0
  • Duration 50 hours
  • Skill level All levels
  • Language English
  • Students 0
  • Certificate No
  • Assessments Self
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