[-0% Off] Introduction to Probability and Statistics -Year 2022 Course CouponUpdated: 2022-02-06T16:00:46Z by saadmerie
Duration: 16.0 hours
16 Hours Course especially designed for the University Students who want to become Expert from very Basics Level.
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
Elementary Statistics by ALAN G. BLUMAN.(8th Edition)
Probability and Statistics for Engineers and Scientists by WALPOLE & MYERS YE.(9th Edition)
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.
Types of variables
Discrete versus Continuous Variables
Summary of Types of Variables
Relative Class Frequencies
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 Using Excel
Cumulative Frequency Distribution
Numerical Descriptive Measures (Measures of location and dispersion)
EXAMPLE – Population Mean
EXAMPLE – Sample Mean
Properties of the Arithmetic Mean
Properties of the Median
EXAMPLES - Median
Example – Mode
The Relative Positions of the Mean, Median and the Mode
The Geometric Mean
EXAMPLE – Geometric Mean
Samples of Dispersions
Types of Dispersion
Variance and Standard Deviation
The Empirical Rule
Coefficient of Variance (C.V)
Coefficient of Variance (C.V)
Finding the Mean for group data
Finding the Median for group data.
Finding the Mode for group data.
Finding the Variance & Standard Deviation for Grouped Data
Pearson coefficient of Skewness (PC)
Permutation Theorem #1
Solve the above example by theorem.
Permutation Theorem #2
Difference between permutation & combination
Mutually Exclusive and Independent Events
Special Rule for Multiplication
General Rule for Multiplication
Generalized Conditional Probability
Bayes’ rule for conditional probability
What is a Probability Distribution?
Probability Distribution of Number of Heads Observed in 3 Tosses of a Coin
Characteristics of a Probability Distribution
Types of Random Variables
Discrete Random Variables – Examples
Continuous Random Variables - Examples
Prob. Mass function (pmf)
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
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
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 –
Simple Linear Regression
Simple Linear Regression Model
Simple Linear Regression Equation
Positive, Negative and Non Relationship
Least Squares Method
Y-Intercept for the Estimated Regression Equation
What is Hypothesis Testing?
Hypothesis Testing Steps
The null and alternative hypothesis
One and Two-tailed test
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
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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