Data Science and Business Analytics: Mastering Statistics

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Data Science and Business Analytics: Mastering Statistics

About Course

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!

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.

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?

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

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

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

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

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What Will You 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!

Course Content

Introduction

  • What does the course cover?
  • Download all resources

Sample or population data?

The fundamentals of descriptive statistics

Measures of central tendency, asymmetry, and variability

Distributions

Estimators and estimates

Confidence intervals: advanced topics

Hypothesis testing: Introduction

Hypothesis testing: Let’s start testing!

The fundamentals of regression analysis

Subtleties of regression analysis

Assumptions for linear regression analysis

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