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Data Science Statistics for Data Scientists and Business Analysis

(12 customer reviews)
Product is rated as #18 in category Data Science

What you’ll learn

  • Understand the fundamentals of statistics
  • Learn how to work with different types of data
  • How to plot different types of data
  • Calculate the measures of central tendency, asymmetry, and variability
  • Calculate correlation and covariance
  • Distinguish and work with different types of distributions
  • Estimate confidence intervals
  • Perform hypothesis testing
  • Make data driven decisions
  • Understand the mechanics of regression analysis
  • Carry out regression analysis
  • Use and understand dummy variables
  • Understand the concepts needed for data science even with Python and R!

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Do you want to work as a Marketing Analyst, a Business Intelligence Analyst, a Data Analyst, or a Data Scientist?

And you want to acquire the quantitative skills needed for the job?

Well then, you’ve come to the right place!

Statistics for Data Science and Business Analysis is here for you! (with TEMPLATES in Excel included)

This is where you start. And it is the perfect beginning!  

In no time, you will acquire the fundamental skills that will enable you to understand complicated statistical analysis directly applicable to real-life situations. We have created a course that is:

  • Easy to understand
  • Comprehensive
  • Practical
  • To the point
  • Packed with plenty of exercises and resources
  • Data-driven
  • Introduces you to the statistical scientific lingo
  • Teaches you about data visualization
  • Shows you the main pillars of quant research

It is no secret that a lot of these topics have been explained online. Thousands of times. However, it is next to impossible to find a structured program that gives you an understanding of why certain statistical tests are being used so often. Modern software packages and programming languages are automating most of these activities, but this course gives you something more valuable – critical thinking abilities. Computers and programming languages are like ships at sea. They are fine vessels that will carry you to the desired destination, but it is up to you, the aspiring data scientist or BI analyst, to navigate and point them in the right direction.

Teaching is our passion

We worked full-time for several months to create the best possible Statistics course, which would deliver the most value to you. We want you to succeed, which is why the course aims to be as engaging as possible. High-quality animations, superb course materials, quiz questions, handouts and course notes, as well as a glossary with all new terms you will learn, are just some of the perks you will get by subscribing.

What makes this course different from the rest of the Statistics courses out there?

  • High-quality production – HD video and animations (This isn’t a collection of boring lectures!)
  • Knowledgeable instructor (An adept mathematician and statistician who has competed at an international level)
  • Complete training – we will cover all major statistical topics and skills you need to become a marketing analyst, a business intelligence analyst, a data analyst, or a data scientist
  • Extensive Case Studies that will help you reinforce everything you’ve learned
  • Excellent support – if you don’t understand a concept or you simply want to drop us a line, you’ll receive an answer within 1 business day
  • Dynamic – we don’t want to waste your time! The instructor sets a very good pace throughout the whole course

Why do you need these skills?

  1. Salary/Income – careers in the field of data science are some of the most popular in the corporate world today. And, given that most businesses are starting to realize the advantages of working with the data at their disposal, this trend will only continue to grow
  2. Promotions – If you understand Statistics well, you will be able to back up your business ideas with quantitative evidence, which is an easy path to career growth
  3. Secure Future – as we said, the demand for people who understand numbers and data, and can interpret it, is growing exponentially; you’ve probably heard of the number of jobs that will be automated soon, right? Well, data science careers are the ones doing the automating, not getting automated
  4. Growth – this isn’t a boring job. Every day, you will face different challenges that will test your existing skills and require you to learn something new

Please bear in mind that the course comes with Udemy’s 30-day unconditional money-back guarantee. And why not give such a guarantee? We are certain this course will provide a ton of value for you.

Click ‘Buy now’ and let’s start learning together today!

Who this course is for:

  • People who want a career in Data Science
  • People who want a career in Business Intelligence
  • Business analysts
  • Business executives
  • Individuals who are passionate about numbers and quant analysis
  • Anyone who wants to learn the subtleties of Statistics and how it is used in the business world
  • People who want to start learning statistics
  • People who want to learn the fundamentals of statistics

12 reviews for Data Science Statistics for Data Scientists and Business Analysis

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  1. Gagan Sarathi

    Most of the times i had to look into Q&A section to get my doubts rectified, could have included all the necessary things explained in lesson to reduce time spent on Q&A to understand better

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  2. Sourabh Kumar

    the course was bit faster to understand. I think it should be a little slower and more detailed, and the most important key was missing is that was the solution part i.e. the instructor should also explain the solution in video format. It would have been a great help to a student, atleast for me.

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  3. Lea Ben Zvi

    Excellent course! All the sunject (even the complex ones) are CLEARLY explained, providing relevant examples and followed by exercices. Very recommended for assipiring Data Scientists as it covers the most relevant concepts.

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  4. Breno Ingwersen Santos

    The course goes through all fundamentals but not as deep as expected and all the examples are a bit too basic and unrealistic. However it’s a good course to get the basic idea to later deepen yourself with other sources.

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  5. Amanda Mei

    I struggled with some concepts, and math is difficult for me in general. I think there should be some step-by-step guided homework solutions. The excel solutions were handy to see the formulas/cells used, but I felt like I was missing some excel prerequisite for this course.

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  6. Wee Chien Yi

    Explanations were clear. The practical examples were useful in provoking statistical thinking.

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  7. Jiaping Chen

    it would be better to demonstrate out the steps of some formula from the examples would make it more clear.

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  8. Christopher Henry

    A brief explanation how 7 where the results of calculation come about would be helpful as sometimes results of the exercises differs from the lectured solutions with no clue how they come about. Makes it confusing if what you are doing is correct.

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  9. Marinath Jeevanantham

    This course is the first time I understood statistics since being introduced 15 years ago. The concepts were clear and explained in a way that the basics get etched. My only suggestion would be to have explained Linear Regression with more examples as it would have helped in approaching the linearity assumptions better.

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  10. Rahul Balakrishnan

    Good beginner level statistics course. Filled with examples and exercises that make the concepts easy to understand.

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  11. Arvind Mishra

    Very good course. It is easy to understand and provide good knowledge. The instructor of this course is very knowledgeable and his way of teaching makes this course easy to understand

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  12. Linda Marc

    Multicollinearity might be easy to spot but it is not easy to fix because the contruct (variable) being removed is not exactly measuring the same construct that remains in the model.

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    Data Science Statistics for Data Scientists and Business Analysis
    Data Science Statistics for Data Scientists and Business Analysis

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