Probability and Statistics for Business and Data Science
Probability and Statistics for Business and Data Science, available at $99.99, has an average rating of 4.62, with 53 lectures, 17 quizzes, based on 7133 reviews, and has 37519 subscribers.
You will learn about Understand the basics of probability Be able to implement basic statistics Understand how to use various statistical distributions Apply statistical methods and hypothesis testing to business problems Understand how regression models work Implement one way and two way ANOVA Understand Chi Squared Tests Be able to understand different types of data This course is ideal for individuals who are Someone interested in learning how to apply probability and statistics to business or data science It is particularly useful for Someone interested in learning how to apply probability and statistics to business or data science.
Enroll now: Probability and Statistics for Business and Data Science
Summary
Title: Probability and Statistics for Business and Data Science
Price: $99.99
Average Rating: 4.62
Number of Lectures: 53
Number of Quizzes: 17
Number of Published Lectures: 53
Number of Published Quizzes: 17
Number of Curriculum Items: 70
Number of Published Curriculum Objects: 70
Original Price: $189.99
Quality Status: approved
Status: Live
What You Will Learn
- Understand the basics of probability
- Be able to implement basic statistics
- Understand how to use various statistical distributions
- Apply statistical methods and hypothesis testing to business problems
- Understand how regression models work
- Implement one way and two way ANOVA
- Understand Chi Squared Tests
- Be able to understand different types of data
Who Should Attend
- Someone interested in learning how to apply probability and statistics to business or data science
Target Audiences
- Someone interested in learning how to apply probability and statistics to business or data science
Welcome to Probability and Statistics for Business and Data Science!
In this course we cover what you need to know about probability and statistics to succeed in business and the data science field!
This practical course will go over theory and implementation of statistics to real world problems. Each section has example problems, in course quizzes, and assessment tests.
We’ll start by talking about the basics of data, understanding how to examine it with measurements of central tendency, dispersion, and also building an understanding of how bivariate data sources can relate to each other.
Afterwards we’ll dive into probability , learning about combinations and permutations, as well as conditional probability and how to apply bayes theorem.
Then we’ll move on to discussing the most common distributions found in statistics, creating a solid foundation of understanding how to work with uniform, binomial, poisson, and normal distributions.
Up next we’ll talk about statistics, applying what we’ve learned so far to real world business cases, including hypothesis testing and the student’s T distribution.
We’ll end the course with 3 sections on advanced topics, such as ANOVA (analysis of variance), understanding regression analysis, and finally performing chi squared analysis.
The sections are modular and organized by topic, so you can reference what you need and jump right in!
Our course includes HD Video with clear explanations and high quality animations, we also include extensive case studies to show you how to apply this knowledge to the real world.
We’ll cover everything you need to know about statistics and probability to clearly tackle real world business and data science problems!
Including:
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Measurements of Data
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Mean, Median, and Mode
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Variance and Standard Deviation
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Co-variance and Correlation
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Permutations and Combinations
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Unions and Intersections
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Conditional Probability
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Bayes Theorem
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Binomial Distribution
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Poisson Distribution
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Normal Distribution
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Sampling
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Central Limit Theorem
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Hypothesis Testing
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T-Distribution Testing
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Regression Analysis
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ANOVA
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Chi Squared
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and much more!
Not only do you get great technical content, but you’ll also have access to our online QA forums as well as our student chat channel. Where the TAs and myself are happy to help out with any questions you encounter! Upon finishing this course you’ll receive a certificate of completion you can post on your linkedin profile to show off to your colleagues, or even potential employers!
All of this content comes with a 30 day money back guarantee, so you can try out the course risk free!
So what are you waiting for? Enroll today and we’ll see you inside the course!
Course Curriculum
Chapter 1: Introduction
Lecture 1: Course Overview Lecture – PLEASE DO NOT SKIP THIS!
Lecture 2: FAQ – Frequently Asked Questions
Chapter 2: Data
Lecture 1: What is Data?
Lecture 2: Measuring Data
Lecture 3: Measurements of Central Tendency
Lecture 4: Measurements of Dispersion
Lecture 5: Measurements – Quartiles
Lecture 6: Bi-variate Data and Covariance
Lecture 7: Pearson Correlation Coefficient
Lecture 8: Section Assessment – Data
Chapter 3: Probability
Lecture 1: What is Probability?
Lecture 2: Permutations
Lecture 3: Combinations
Lecture 4: Intersections, Unions, and Complements
Lecture 5: Independent and Dependent Events
Lecture 6: Conditional Probability
Lecture 7: Addition and Multiplication Rules
Lecture 8: Bayes Theorem
Lecture 9: Section Assessment – Probability
Chapter 4: Distributions
Lecture 1: Introduction to Distributions
Lecture 2: Uniform Distribution
Lecture 3: Binomial Distribution
Lecture 4: Poisson Distribution
Lecture 5: Normal Distribution
Lecture 6: Normal Distribution – Formulas and Z Scores
Lecture 7: Section Assessment – Distributions
Lecture 8: Optional Resource – Dash Scripts
Chapter 5: Statistics
Lecture 1: What is Statistics?
Lecture 2: Sampling
Lecture 3: Central Limit Theorem
Lecture 4: Standard Error
Lecture 5: Hypothesis Testing
Lecture 6: Hypothesis Testing Example Exercise #1
Lecture 7: Hypothesis Testing Example Exercise #2
Lecture 8: Type 1 and Type 2 Errors
Lecture 9: Student's T Distribution
Lecture 10: Student's T Distribution Example Exercise
Lecture 11: Section Assessment – Statistics
Chapter 6: Analysis of Variance (ANOVA)
Lecture 1: Introduction to ANOVA
Lecture 2: ANOVA – Analysis of Variance
Lecture 3: F Distribution
Lecture 4: Two Way ANOVA Overview
Lecture 5: Two Way ANOVA Example Exercise
Lecture 6: Two Way ANOVA with Replication
Lecture 7: Section Assessment – ANOVA
Chapter 7: Regression
Lecture 1: Linear Regression
Lecture 2: Regression Example
Lecture 3: Multiple Regression
Lecture 4: Section Assessment – Regression
Chapter 8: Chi-Square Analysis
Lecture 1: Chi-Square Analysis
Lecture 2: Chi Squared Analysis – Exercise Example
Lecture 3: Section Assessment – Chi Square Analysis
Chapter 9: BONUS SECTION: THANK YOU!
Lecture 1: BONUS LECTURE
Instructors
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Jose Portilla
Head of Data Science at Pierian Training -
Pierian Training
Data Science and Machine Learning Training
Rating Distribution
- 1 stars: 35 votes
- 2 stars: 77 votes
- 3 stars: 586 votes
- 4 stars: 2604 votes
- 5 stars: 3838 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!
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