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Introduction to Probability and Statistics -Year 2022 Coupon
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[-0% Off] Introduction to Probability and Statistics -Year 2022 Course Coupon

Updated: by saadmerie
Duration: 16.0 hours

16 Hours Course especially designed for the University Students who want to become Expert from very Basics Level.

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In this course, everything has been broken down into a simple structure to make learning and understanding easy for you.

Probability and statistics help to bring logic to a world replete with randomness and uncertainty. This course will give you the tools needed to understand data, science, philosophy, engineering, economics, and finance. You will learn not only how to solve challenging technical problems, but also how you can apply those solutions in everyday life and can solve many problems from the books for your exams.

With examples from our daily life and and from the famous books on these topics, you will gain a strong foundation for the study of statistical inference, stochastic processes, randomized algorithms, and other subjects where probability is needed.

As this course is specially designed for the University and High School Students who are facing difficulties in their studies and for those who want to boost up their skills in this field.

With this 16 Hours Probability and Statistics course,you can understand from very basic level and can become expert in this course.

Textbooks used for this course

  1. Elementary Statistics by ALAN G. BLUMAN.(8th Edition)

  2. Probability and Statistics for Engineers and Scientists by WALPOLE & MYERS YE.(9th Edition)

Lecture 1

  • What is meant by Statistics?

  • Formal Definition of Statistics and types of Statistics.

  • Uses of Statistics?

  • Population versus Sample.

    Why take a sample instead of studying every member of the population?

    Usefulness of a Sample in learning about a Population.

  • Variables

    Types of variables

    Discrete versus Continuous Variables

    Summary of Types of Variables

  • Frequency Table

  • Relative Class Frequencies

  • Bar Charts

  • Frequency Distribution

    EXAMPLE – Constructing Frequency Distributions: Quantitative Data

    Constructing a Frequency Table - Example

  • Class Intervals and Midpoints with Examples

  • Relative Frequency Distribution

  • Graphic Presentation of a Frequency Distribution

  • Histogram

    Histogram Using Excel

  • Frequency Polygon

  • Cumulative Frequency Distribution

Lecture 2

  • Numerical Descriptive Measures (Measures of location and dispersion)

  • Central Tendency

  • Population Mean

    EXAMPLE – Population Mean

  • Sample Mean

    EXAMPLE – Sample Mean

  • Properties of the Arithmetic Mean

  • The Median

    Properties of the Median

    EXAMPLES - Median

  • The Mode

    Example – Mode

  • The Relative Positions of the Mean, Median and the Mode

  • The Geometric Mean

    EXAMPLE – Geometric Mean


    Samples of Dispersions

    Types of Dispersion

  • Examples


    Mean Deviation

    Variance and Standard Deviation

    Sample Variance

  • The Empirical Rule

  • Coefficient of Variance (C.V)


Lecture 3

  • Coefficient of Variance (C.V)


  • Mean

    Finding the Mean for group data

  • Median

    Finding the Median for group data.

  • Mode

    Finding the Mode for group data.

  • Finding the Variance & Standard Deviation for Grouped Data


  • Skewness


  • Pearson coefficient of Skewness (PC)


Lecture 4

  • Permutation

    Permutation Theorem #1

    Solve the above example by theorem.

    Permutation Examples

    Permutation Theorem #2

  • Combination


  • Difference between permutation & combination

  • Definitions




  • Classical Probability


  • Mutually Exclusive and Independent Events

  • Empirical Probability


  • Addition Rule


  • Complement Rule


Lecture 5

  • Conditional Probability



  • Special Rule for Multiplication


  • General Rule for Multiplication


  • Contingency Table


  • Generalized Conditional Probability


  • Bayes’ rule for conditional probability


Lecture 6

  • What is a Probability Distribution?

  • Probability Distribution of Number of Heads Observed in 3 Tosses of a Coin

  • Characteristics of a Probability Distribution

  • Random Variables

    Types of Random Variables

    Discrete Random Variables – Examples

    Continuous Random Variables - Examples

  • Prob. Mass function (pmf)

  • Probability Distribution

    The Mean of a Discrete Probability Distribution

    The Variance, and Standard Deviation of a Discrete Probability Distribution

    Mean, Variance, and Standard Deviation of a Discrete Probability Distribution – Example

    Mean of a Discrete Probability Distribution - Example

    Variance and Standard Deviation of a Discrete Probability Distribution – Example

  • Discrete Probability Distribution

    Binomial Probability Distribution.


    Poisson Probability Distribution.


    -ve binomial and Geometric Probability Distribution


Lecture 7

  • Probability density function (PDF)

    Properties of PDF


  • Cumulative distribution function (CDF)

    Properties of CDF


  • The Family of Uniform Distributions

  • The Uniform Distribution

    Mean and Standard Deviation


Lecture 8

  • Normal probability distribution


    Characteristics of a Normal Probability Distribution

    The Normal Distribution – Graphically

    The Normal Distribution – Families

    The Standard Normal Probability Distribution

  • Areas Under the Normal Curve


  • The Empirical Rule

  • Normal Distribution – Finding Probabilities


  • Using Z in Finding X Given Area –


  • Alternate Method

  • Simple Linear Regression

  • Simple Linear Regression Model


  • Simple Linear Regression Equation

    Positive, Negative and Non Relationship

  • Estimation Process

  • Least Squares Method

    Y-Intercept for the Estimated Regression Equation

Lecture 9

  • Correlation


  • Hypothesis

    What is Hypothesis Testing?

    Hypothesis Testing Steps

  • The null and alternative hypothesis

  • One and Two-tailed test

Lecture 10

  • Important Things to Remember about H0 and H1

  • Left-tail or Right-tail Test?

  • Parts of a Distribution in Hypothesis Testing

  • One-tail vs. Two-tail Test

  • Test of Single POP Mean (σ Unknown)

    Test 1 and Test 2

  • Testing for a Population Mean with a Known Population Standard Deviation


  • Estimation and Confidence Intervals

  • Interval Estimates

    Factors Affecting Confidence Interval Estimates

    Confidence Interval Estimates for the Mean

    When to Use the z or t Distribution for Confidence Interval Computation

    Confidence Interval for the Mean – Example using the t-distribution

  • Student’s t-distribution Table

  • Two-sample Tests of Hypothesis

    Comparing two populations

    Comparing two populations (Mean of Independent Samples)

    Comparing Population Means with Unknown Population Standard Deviations (the Pooled t-test)

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