Statistics and Probability

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About Course

I know, Statistics and Probability is difficult. But is there a way to make it easy? Of course. I for one managed that.

I know a lot of people struggle with it; a very small group of people are good at it. Back in university, I was in that bigger group, the group that struggled through Probability and Statistics lecture. I needed help; I couldn’t understand a thing, but I finally found help and turned my exam result around. I guess since you’re looking at this, you need help too.

This COMPLETE GUIDE course of Statistics and Probability contains everything you need to know to get started with Probability and Statistics. It’s packed with videos that have been categorized into different topics, hence easy for you to learn.

I’ve included lots of definitions, theorems, quizzes, examples, concise notes for EVERY single section, exercises, and a walkthrough of all the exercise sheets. Most importantly, It includes some additional questions that will strengthen your skill even more.

With this basic Statistics and Probability course, you will have a good core understanding to pursue a much more difficult Mathematics topic. In this course, everything has been broken down into a simple structure to make learning and understanding easy for you.

This COMPLETE guide is for those of you who are looking to get a full understanding of the basics; the important parts. You’ve already shown half of your determination by looking at the course, so if this course sounds right for you, boost your eagerness to learn and join me on this journey!

Tips:

1) It will be very useful if you also take notes of your own as you’re watching the lectures, it will help you understand everything better and quicker. Just pause if I move on to other topics too fast or if you haven’t fully understood the previous sub-topic before you move on to the next parts.

2) Use headphones for better sound. (I suggest you turn the volume up)

Who these Statistics and Probability course are for:

  1. high school students
  2. university students
  3. courses that require probability and statistics (e.g. computer science, and other sciences)
  4. Engineering
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What Will You Learn?

  • representation and characterisation of data
  • elementary probability theory
  • combinatorics
  • rules for computing probabilities
  • conditional probability and independence of events
  • discrete random variables and their probability distributions
  • expectation value of a discrete random variable
  • examples of discrete random variables
  • moment generating functions
  • continuous random variables and their probability distributions
  • expectation value of a continuous random variable
  • examples of continuous random variables
  • Chebyshev's theorem
  • bivariate probability distributions
  • expectations of functions of random variables
  • independent random variables

Course Content

Statistics and Probability

  • Overview Of Random Variable & Probability Distribution
    00:00
  • Joint Probability Distribution , Joint PMF, Marginal PMF, Statistical Independence
    00:00
  • Correlation Coefficient | Correlation Coefficient Example | Statistics
    00:00
  • Rank Correlation | Rank Correlation Coefficient | Spearman Rank Correlation
    00:00
  • Rank Correlation | Repeated Rank Correlation | Spearman Rank Correlation
    00:00
  • Regression Analysis, Regression Coefficient, Linear Regression Part-I
    00:00
  • Regression Analysis, Regression Coefficient, Linear Regression Part-II
    00:00
  • Regression Analysis, Angle Between Two Regression Lines, Proof
    00:00
  • 6 Tips To Get Motivated During Exam Preparations
    00:00
  • Unacademy Official Advertisement
    00:00
  • Assignment Problem | Hungarian Method | Example of Assignment Problem
    00:00
  • Assignment Problem | Hungarian Method | Unbalanced Assignment Problem
    00:00
  • Assignment Problem | Hungarian Method | Maximization Assignment Problem
    00:00
  • Assignment Problem | Hungarian Method | Restricted Assignment Problem
    00:00
  • Game Theory | Saddle Point In Game Theory | Pure Strategy Game Theory | Operation Research
    00:00
  • Game Theory | Two Person Zero Sum Game | Mixed Strategy Game Theory | Operation Research
    00:00
  • Joint Probability Distribution , Joint PMF, Marginal PMF, Bivariate RV
    00:00
  • Skewness & Kurtosis | Moments | Leptokurtic, Mesokurtic, Platykurtic | Examples
    00:00
  • Skewness & Kurtosis | Moments | Leptokurtic, Mesokurtic, Platykurtic
    00:00
  • Random Variable, Probability Mass Function, Distribution Function
    00:00
  • Random Variable, Probability Density Function, Cumulative Distribution Function
    00:00
  • Mathematical Expectation, Variance Of Continuous & Discrete Random Variable
    00:00
  • Binomial Distribution
    00:00
  • Fitting of Binomial Distribution | Examples
    00:00
  • Poisson Distribution | Proof Binomial Tends to Poisson Distribution
    00:00
  • Poisson Distribution | Mean & Variance
    00:00
  • Poisson Distribution | Poisson Distribution Examples with Solutions
    00:00
  • Poisson Distribution | Fitting of Poisson Distribution | Example
    00:00
  • Exponential Distribution | Mean & Variance | Moment Generating Function
    00:00
  • Normal Distribution | Mean and Variance of Normal Distribution
    00:00
  • Normal Distribution | Moment Generating Function | Mean & Variance By MGF
    00:00
  • Normal Distribution | Normal Distribution Table & Area Under Curve | Examples
    00:00
  • Normal Distribution | Normal Distribution Table & Area Under Curve | Examples Part-II
    00:00
  • Uniform Distribution | Rectangular Distribution | Mean & Variance | Moment Generating Function
    00:00
  • Game Theory | Game Theory Dominance Rule | Operation Research
    00:00

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