Learn Probability concepts and counting techniques
- 3 hours on-demand video
- 2 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
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- By the end of this course you will understand probability concepts and be able to solve commons probability problems
- By the end of this course, you will be able to compute conditional probabilities
- By the end of this course, you will be able to understand how to solve probability problems using the addition and multiplicative rules.
- By the end of this course, you will be able to solve basic counting problems using permutations and combinations formulas
- By the end of this course, you will be able to compute probabilities using the Poisson distribution
- By the end of this course, you will be able to compute probabilities using the Binomial distribution
- By the end of this course you will understand how to solve problems using the Hypergeometric distribution
- By the end of this course, you will be able to compute probabilities using the multinomial distribution
- By the end of this course, you will be able to compute probabilities using the Geometric and Negative Binomial (or Pascal) distribution
- General knowledge of descriptive statistics, basic algebra
- A strong desire to learn probability concepts.
This course covers the fundamental concepts of probability, basic counting and discrete random variables as taught in a first year introductory basic statistics class in colleges.
It is intended to students who want to learn at their own space or supplement a course note. It is also intended to anyone who wants to understand the concepts of probability through hands-on carefully selected problems that explain in plain English the concepts.
This class is a result of many years of teaching college level introductory statistics courses and it designed to help students understand probability concepts and especially to pay attention to the technical English language and the logic of probability.
Whether you are trying to pass an Introductory statistic course or you want to understand probability concepts, this is the course for you. It is a must for everyone especially people aspiring to programming careers, nursing, business, and especially to fields where logical thinking is important.
- College students, programmers and anyone interested in understanding probablity
- People studying liberal arts, law and any other field where critical reasoning and logical thinking is very important
- Anyone interested in understanding basic probability theory
In this lecture, we cover detailed explanations about the concept of a sample space in probability, sample points and events. These concepts are essential for solving probability problems.
In this lecture, we provide the definition of a probability using the relative frequency approach. Several examples about computing probabilities based on dices being rolled or coins being tossed are given. We conclude the video by showing all the cards in a deck of 52 cards and discuss at length the composition of the deck which is important for computing probabilities about cards being drawn from a deck of 52 cards.
In this video, we discuss the computation of basic probability about cards being selected from a deck of 52 cards. We discuss the addition rule of probability and solve related problems to ensure that the concept is well understood.
In this lecture, we cover the concept of conditional probability and Independent events. Solved problems are presented to explain in details how to solve conditional probabilities. We also cover the multiplication rule of probability and explain the concept with examples.
In this video, we talk about discrete random variables and the probability distribution of discrete random variable. We explain the conditions that must be satisfied for a probability distribution to be valid. In addition, we cover the concepts of the expected value of discrete random variables, the variance and standard deviation of the discrete random variable.
In this lecture, we talk about the Binomial distribution experiment an introduce important concepts about the distribution such as the failure and success probability, dichotomous outcomes and independent events.
The student can identify a binomial distribution problem after following this lecture.
This lecture illustrates how to compute probabilities using the Hypergeometric distribution. We show the differences between the Binomial distribution and the Hypergeometric distribution and use a practical example to explain how the distribution is used in solving probabilities.
We explain in detail The Negative Binomial distribution which is a discrete probability distribution that measures the number of failures until the rth success , where r >= 1. When r = 1, the Negative Binomial is the same as the geometric distribution. Exercises are used to explain how in practice the Negative Binomial distribution.