Introduction to Probability and Statistics

Introduction to Probability and Statistics, available at $19.99, with 31 lectures, 3 quizzes.

You will learn about Probability theory: Students will gain a solid foundation in probability theory, enabling them to analyze and quantify uncertainty in various scenarios. Statistical inference: Students will learn how to draw conclusions and make predictions based on data. S Data analysis: Essential techniques for analyzing and interpreting data. Students will learn about exploratory data analysis, descriptive statis Probability distributions: Students will delve into the characteristics and applications of various probability distributions. This course is ideal for individuals who are Designed for a broad range of students and professionals who seek to develop a solid understanding of probability and statistics. It is commonly taken by undergraduate students pursuing degrees in mathematics, statistics, engineering, computer science, economics, social sciences, or related fields. Additionally, professionals in fields such as data analysis, finance, market research, and quality control may also benefit from this course to enhance their analytical skills and decision-making abilities. It is particularly useful for Designed for a broad range of students and professionals who seek to develop a solid understanding of probability and statistics. It is commonly taken by undergraduate students pursuing degrees in mathematics, statistics, engineering, computer science, economics, social sciences, or related fields. Additionally, professionals in fields such as data analysis, finance, market research, and quality control may also benefit from this course to enhance their analytical skills and decision-making abilities.

Enroll now: Introduction to Probability and Statistics

Summary

Title: Introduction to Probability and Statistics

Price: $19.99

Number of Lectures: 31

Number of Quizzes: 3

Number of Published Lectures: 31

Number of Published Quizzes: 3

Number of Curriculum Items: 38

Number of Published Curriculum Objects: 38

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will Learn

Probability theory: Students will gain a solid foundation in probability theory, enabling them to analyze and quantify uncertainty in various scenarios.
Statistical inference: Students will learn how to draw conclusions and make predictions based on data. S
Data analysis: Essential techniques for analyzing and interpreting data. Students will learn about exploratory data analysis, descriptive statis
Probability distributions: Students will delve into the characteristics and applications of various probability distributions.

Who Should Attend

Designed for a broad range of students and professionals who seek to develop a solid understanding of probability and statistics. It is commonly taken by undergraduate students pursuing degrees in mathematics, statistics, engineering, computer science, economics, social sciences, or related fields. Additionally, professionals in fields such as data analysis, finance, market research, and quality control may also benefit from this course to enhance their analytical skills and decision-making abilities.

Target Audiences

Designed for a broad range of students and professionals who seek to develop a solid understanding of probability and statistics. It is commonly taken by undergraduate students pursuing degrees in mathematics, statistics, engineering, computer science, economics, social sciences, or related fields. Additionally, professionals in fields such as data analysis, finance, market research, and quality control may also benefit from this course to enhance their analytical skills and decision-making abilities.

The Statistics and Probability course is designed to provide students with a comprehensive understanding of fundamental statistical concepts and probabilistic principles. This course equips students with the necessary skills to analyze data, make informed decisions, and draw meaningful conclusions in various fields and real-world scenarios.

The course covers a wide range of topics, starting with the basics of descriptive statistics, where students learn to organize, summarize, and present data using graphical and numerical methods. They gain proficiency in calculating measures of central tendency, such as mean, median, and mode, as well as measures of dispersion, including variance and standard deviation.

Moving on to inferential statistics, students delve into probability theory, understanding the foundations of probability and its applications in uncertainty and randomness. They learn to calculate probabilities of events, study probability distributions, and explore the concepts of independence and conditional probability.

The course further explores discrete probability distributions, focusing on the binomial and Poisson distributions. Students learn how to apply these distributions to model the occurrence of events and understand real-world phenomena, such as the number of successes in a fixed number of trials and the occurrence of rare events in continuous time.

In addition, the course introduces students to the Poisson process, a powerful tool for modeling events that happen randomly and independently over continuous time. Students grasp the process’s key characteristics, including independent increments and varying intensity, and apply it to various fields, including queuing theory, telecommunications, and reliability engineering.

Throughout the course, practical applications and real-world examples are incorporated to help students develop a deep understanding of statistical concepts and their relevance in different domains. Hands-on exercises and projects enable students to gain proficiency in using statistical software and data analysis tools to extract meaningful insights from real datasets.

By the end of the Statistics and Probability course, students will have honed their ability to critically analyze data, perform statistical tests, and draw meaningful conclusions. They will be equipped with a solid foundation in statistical thinking, preparing them to make informed decisions and contribute to various fields, such as business, medicine, social sciences, and engineering.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Examples of Statistical Practice

Lecture 3: Final Words

Chapter 2: Descriptive Statistics

Lecture 1: What You'll Learn

Lecture 2: Dotplots

Lecture 3: Histograms

Lecture 4: Univariate Numerical Statistics

Lecture 5: Boxplots

Lecture 6: Paired Data

Chapter 3: Probability

Lecture 1: Framework

Lecture 2: Set Theory

Lecture 3: Three Definitions of Probability

Lecture 4: Conditional Probability

Lecture 5: Some Counting Rules

Chapter 4: Discrete Distributions

Lecture 1: Random Variables

Lecture 2: Example

Lecture 3: Expectations

Lecture 4: The Binomial Distribution

Lecture 5: The Poisson Distribution

Lecture 6: The Poisson Process

Chapter 5: Continuous Distributions

Lecture 1: CDF

Lecture 2: Expectations for Continuous RVs

Lecture 3: Examples

Lecture 4: The Normal Distribution

Lecture 5: The Normal Approximation to the Binomial

Lecture 6: The Gamma Distribution

Lecture 7: The Exponential Distribution

Lecture 8: Jointly Distributed Random Variables

Lecture 9: Statistics and their Distributions

Lecture 10: The Central Limit Theorem

Chapter 6: Video Review

Lecture 1: Video that encompasses the entire course

Instructors

Theo TT
Instructor at Udemy

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 0 votes
4 stars: 0 votes
5 stars: 0 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

Menu