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30-Day Money-Back Guarantee

This course includes:

  • 5 hours on-demand video
  • 10 articles
  • 35 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
Development Data Science Statistics

Probability and Statistics for Business and Data Science

Learn how to apply probability and statistics to real data science and business applications!
Rating: 4.6 out of 54.6 (3,700 ratings)
18,960 students
Created by Jose Portilla
Last updated 9/2019
English
English [Auto], French [Auto], 
30-Day Money-Back Guarantee

What you'll 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
Curated for the Udemy for Business collection

Course content

9 sections • 53 lectures • 5h 14m total length

  • Preview05:18
  • FAQ - Frequently Asked Questions
    00:21

  • What is Data?
    09:17
  • Measuring Data
    13:09
  • Quiz #1 - Measuring Data
    4 questions
  • Measurements of Central Tendency
    05:28
  • Quiz #2 - Measures of Central Tendency
    2 questions
  • Measurements of Dispersion
    09:01
  • Quiz #3 - Measures of Dispersion
    1 question
  • Measurements - Quartiles
    05:55
  • Quiz #4 - Quartiles and IQR
    2 questions
  • Bi-variate Data and Covariance
    10:34
  • Pearson Correlation Coefficient
    07:20
  • Section Assessment - Data
    00:07

  • What is Probability?
    04:59
  • Permutations
    07:32
  • Quiz #5 - Permutations
    2 questions
  • Combinations
    06:50
  • Quiz #6 - Combinations
    2 questions
  • Intersections, Unions, and Complements
    06:21
  • Independent and Dependent Events
    05:28
  • Quiz #7 - Independent & Dependent Events
    1 question
  • Conditional Probability
    04:20
  • Quiz #8 - Conditional Probability
    3 questions
  • Addition and Multiplication Rules
    05:31
  • Bayes Theorem
    11:13
  • Quiz #9 - Bayes Theorem
    1 question
  • Section Assessment - Probability
    00:07

  • Introduction to Distributions
    01:14
  • Uniform Distribution
    01:57
  • Quiz #10 - Uniform Distribution
    2 questions
  • Preview12:21
  • Quiz #11 - Binomial Distribution
    2 questions
  • Poisson Distribution
    17:16
  • Quiz #12 - Poisson Distribution
    2 questions
  • Normal Distribution
    07:36
  • Quiz #13 - Normal Distribution
    3 questions
  • Normal Distribution - Formulas and Z Scores
    14:13
  • Quiz #14 - Z Score
    2 questions
  • Section Assessment - Distributions
    00:07
  • Optional Resource - Dash Scripts
    00:24

  • What is Statistics?
    02:24
  • Sampling
    10:40
  • Central Limit Theorem
    03:43
  • Quiz #15 - Sampling and CLT
    3 questions
  • Standard Error
    07:15
  • Hypothesis Testing
    11:43
  • Preview05:49
  • Hypothesis Testing Example Exercise #2
    04:27
  • Quiz #16 - Hypothesis Testing #1
    4 questions
  • Type 1 and Type 2 Errors
    03:38
  • Quiz #17 - Hypothesis Testing #2
    4 questions
  • Student's T Distribution
    10:21
  • Student's T Distribution Example Exercise
    08:24
  • Section Assessment - Statistics
    00:07

  • Introduction to ANOVA
    01:25
  • ANOVA - Analysis of Variance
    07:10
  • F Distribution
    05:22
  • Two Way ANOVA Overview
    06:59
  • Two Way ANOVA Example Exercise
    05:00
  • Two Way ANOVA with Replication
    08:05
  • Section Assessment - ANOVA
    00:07

  • Linear Regression
    11:24
  • Regression Example
    04:08
  • Multiple Regression
    08:48
  • Section Assessment - Regression
    00:07

  • Chi-Square Analysis
    07:15
  • Chi Squared Analysis - Exercise Example
    05:36
  • Section Assessment - Chi Square Analysis
    00:07

  • BONUS LECTURE
    00:10

Requirements

  • Paper and Pencil to take notes
  • Optional: Excel or Python to run simulations

Description

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: 

  • Measurements of Data

  • Mean, Median, and Mode

  • Variance and Standard Deviation

  • Co-variance and Correlation

  • Permutations and Combinations

  • Unions and Intersections

  • Conditional Probability

  • Bayes Theorem

  • Binomial Distribution

  • Poisson Distribution

  • Normal Distribution

  • Sampling

  • Central Limit Theorem

  • Hypothesis Testing

  • T-Distribution Testing

  • Regression Analysis

  • ANOVA

  • Chi Squared

  • 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!

Who this course is for:

  • Someone interested in learning how to apply probability and statistics to business or data science

Featured review

Chinmaya Acharya
Chinmaya Acharya
10 courses
5 reviews
Rating: 5.0 out of 5a year ago
Dear Jose, As you might check, I am an aspiring data scientist, I have subscribed to multiple courses in udemy by you. You are fabulous. In stats, please give more relevance to real world problems like server issue in chi square. Also the SSG, SST etc are briefly explained, please include more examples. Thank you for your generous help and making courses at low cost which are helping us. Thanks again and god bless you. Sincerely, Chinmaya Acharya chinmaya1982@gmail.com

Instructor

Jose Portilla
Head of Data Science, Pierian Data Inc.
Jose Portilla
  • 4.6 Instructor Rating
  • 703,473 Reviews
  • 2,151,438 Students
  • 31 Courses

  Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science and programming. He has publications and patents in various fields such as microfluidics, materials science, and data science technologies. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming the ability to analyze data, as well as present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Data Inc. and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, The New York Times, Credit Suisse, McKinsey and many more. Feel free to contact him on LinkedIn for more information on in-person training sessions or group training sessions in Las Vegas, NV.

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