Statistics for Data Science and Business Analysis Bootcamp

Master Probability and Statistics from Scratch, Learn Distributions, Hypothesis Testing, ANOVA, Chi-Square with examples

Instructed by Vijay Gadhave

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$ 299/yr
Billed Annually
  • One year Unlimited Access
  • Access to all courses
    You will be able to access all the courses from any category on the platform.
  • Learning paths access
  • Access Assignments & Projects
  • Access on Mobile, PC and Tablet
  • Pause & Resume Courses Anytime
  • Offline viewing
  • Instructor Support
  • Course Completion Certificates
Subscribe Now
  • Understand the Fundamentals of Statistics
  • Understand the basics of Probability
  • Learn how to work with Different Types of Data
  • Distinguish and work with Different Types of Distributions
  • Apply statistical methods and hypothesis testing to business problems
  • Understand all the concepts needed for data science
  • Understand the working of Regression Analysis
  • mplement one way and two way ANOVA
  • Learn Chi-Square Analysis

If you are starting a career in Data Science or Business Analysis, then this course will help you to Built a Strong Foundation

This course is Very Practical, Easy to Understand and Every Concept is explained with an example

I have specifically included real-world examples to show, how you could apply this knowledge to boost YOUR career

 

We'll cover everything you need to know about statistics and probability for Data Science and Business Analysis!

Including:

1) Levels of Measurement

2) Measures of Central Tendency

3) Population and Sample

4) Population Standard Variance

5) Quartiles and IQR

6) Permutations,Combinations

7) Intersection, Union and Complement

8) Independent and Dependent Events

9) Conditional Probability

10) Bayes’ Theorem

11) Uniform Distribution, Binomial Distribution

12) Poisson Distribution, Normal Distribution, Skewness

13) Standardization and Z Score

14) Central Limit Theorem

15) Hypothesis Testing, Type I and Type II Error

16) Students T-Distribution

17) ANOVA - Analysis of Variance

18) F Distribution

19) Linear Regression and much more...

So what are you waiting for?

Enroll now and empower your career!

  • Basic knowledge of high school Mathematics
  • People who want to pursue their career in Data Science
  • Business Intelligence
  • Business analysis
  • Business executives
  • Anyone who wants to learn Statistics and how to use it in Business World
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Section 1 : Unpublished Section

  • Lecture 1 :

Section 2 : Statistic Basics

  • Lecture 1 :
  • Data
  • Lecture 2 :
  • Levels of Measurement
  • Lecture 3 :
  • Measures of Central Tendency
  • Lecture 4 :
  • Population and Sample
  • Lecture 5 :
  • Measures of Dispersion
  • Lecture 6 :
  • Quartiles and IQR

Section 3 : Probability

  • Lecture 1 :
  • Introduction to Probability
  • Lecture 2 :
  • Permutations
  • Lecture 3 :
  • Combinations
  • Lecture 4 :
  • Intersection, Union and Complement
  • Lecture 5 :
  • Independent and Dependent Events
  • Lecture 6 :
  • Conditional Probability
  • Lecture 7 :
  • Addition and Multiplication Rules
  • Lecture 8 :
  • Bayes’ Theorem

Section 4 : Distribution

  • Lecture 1 :
  • Introduction to Distribution
  • Lecture 2 :
  • Uniform Distribution
  • Lecture 3 :
  • Binomial Distribution
  • Lecture 4 :
  • Poisson Distribution
  • Lecture 5 :
  • Skewness
  • Lecture 6 :
  • Standardization and Z Score

Section 5 : Central Limit Theorem

  • Lecture 1 :
  • Central Limit Theorem

Section 6 : Hypothesis Testing

  • Lecture 1 :
  • Hypothesis Testing and Hypothesis Formulation
  • Lecture 2 :
  • Important Concepts in Hypothesis Testing
  • Lecture 3 :
  • Exercise 1
  • Lecture 4 :
  • Exercise 2
  • Lecture 5 :
  • Type I and Type II Error
  • Lecture 6 :
  • Students T-Distribution
  • Lecture 7 :
  • Exercises on Students T-Distribution

Section 7 : ANOVA - Analysis of Variance

  • Lecture 1 :
  • ANOVA - Analysis of Variance
  • Lecture 2 :
  • F Distribution
  • Lecture 3 :
  • One-Way ANOVA
  • Lecture 4 :
  • Two-Way ANOVA
  • Lecture 5 :
  • Two-Way ANOVA Exercise
  • Lecture 6 :
  • Two-Way ANOVA with Replication

Section 8 : Regression Analysis

  • Lecture 1 :
  • Linear Regression
  • Lecture 2 :
  • Exercise on Linear Regression
  • Lecture 3 :
  • Multiple Regression

Section 9 : Chi-Square Analysis

  • Lecture 1 :
  • Chi-Square Test

Vijay Gadhave,

Hello Everyone, I am Vijay Gadhave. I am a Data Scientist. I have 5 plus years of experience in the field of Data Science. I have Professional experience of training students in the Field of Data Science and Software Development I am passionate about various fields of Data Science, Software Development and instructing  students/Professionals with the cutting edge technologies Regards, Vijay Gadhave
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