Every Data Scientist Needs to Master Statistics

But, unless you really know what you are doing and have proven analysis systems in place, you can find yourself making all kinds of mistakes and Not even knowing it! This leads to incorrect results, failed projects, you looking silly and is all-around just a bad time - No Bueno.

The Step By Step Statistical Analysis System, will teach you an innovative step by step framework for analyzing ANY data using statistics so that you NEVER pick the wrong test for your data or miss something out.

Everything is broken down step by step, all the way from receiving the data, analyzing it and reporting the results. No ambiguity or confusion, just plans, systems and darn good tuition.

Here is what you will learn inside the Course

The course will take you step by step through the process that every data scientist needs to follow in order to analyse their data.

You will learn theory lessons so that you understand the important concepts, and then you will< immediately apply those concepts on exercises using the highly in-demand Python programming language! There is no fluff, no filler, just valuable actionable learning.

Part 1: The Statistical Analysis Preparation Checklist

In order to pick the correct statistical test (and get correct results), you need to fully understand your data's properties.

Part 1 will teach you a simple, step-by-step process to fully characterise your data's properties perfectly every time. All without confusion or wondering whether you have missed anything out.

In Part 1:
  • The types of statistical methods
  • How to determine your study design
  • How to determine your question type
  • How to determine your null and alternative hypotheses
  • How to determine your test's significance level
  • How to test for normality
  • How to test for homogeneity of variance
  • Quizzes and Challenges!

Part 2a: Comparative tests

If you are looking to find differences, you need a comparative test.

Part 2a of the Step by Step Statistical Analysis System provides you with in-depth training on the most well-established comparative Statistical Tests.

No matter what comparative question you may have to solve, Part 2a of the step-by-step statistical analysis system has the answer.

In Part 2a:
  • The 1 Sample t-test (Theory and Practical)
  • The 2 Sample t-test (Theory and Practical)
  • The Welch test (Theory and Practical)
  • The Mann-Whitney test (Theory and Practical)
  • The Repeated-measure 2 Sample t-test (Theory and Practical)
  • The Wilcoxon Signed Rank Test (Theory and Practical)
  • The One-Way ANOVA (Theory and Practical)
  • The Kruskal Wallis test (Theory and Practical)
  • The Repeated-measure One-way ANOVA (Theory and Practical)
  • The Friedman test (Theory and Practical)
  • Post-hoc tests (Theory and Practical)
  • Downloadable Data sets!
  • Downloadable interactive Jupyter notebooks!

Part 2b: Associational tests

If you are trying to find links or trends in your data you need an associational statistical test.

Part 2a will show you the best associational tests and show you how to detect valuable hidden links in your data that will Wow your clients.

In Part 2b:
  • The Pearson Test (Theory and Practical)
  • The Spearman Rank Test (Theory and Practical)
  • Downloadable Data sets!
  • Downloadable interactive Jupyter notebooks!

Part 3: The 5 Step System for Reporting your statistics

Once you have gotten your perfectly analysed results, you will want a perfectly written report.

In part 3 you will learn an innovative 5 step process for reporting your statistics in a professional, comprehensive manner. This system is guaranteed to impress your boss and colleagues and boost your data science career (even if English grammar and spelling isn't your strong suit!)

In Part 3:
  • The 5 Step System for Reporting your statistics

Part 4: Final Project

There is no better way to learn, than by doing.

Project-based learning has been shown to be the most effective way of learning any skill, from data science to art.

We take advantage of this fact by providing you at the end of the course with a scenario and a dataset for you to tackle on your own! Along with the quizzes and practice you receive during the course, the project will allow you to stretch your wings and experience what it is like to solve a problem using data and see what it is all about.

In Part 4:
  • Final Project Brief
  • Downloadable Data Set

Your Instructors

Huda Alfardus, Data Scientist

Huda is a data scientist and has done data analysis projects for institutions such as Harvard University, Cambridge University, Oxford University, University College London (UCL) and more.

Ziyad Yehia, Python Programmer

Ziyad is a sessional tutor in computing at a UK University and an online python programming teacher. He has helped thousands of people from 138 countries to learn Python programming and level up their careers.

Complete Course Curriculum

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  Course Overview
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  Part 2 - The Statistical Analysis Roadmaps
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  Part 3: The 5 Step System for Reporting your statistics
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  Final Project
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How about a Rock-Solid guarantee?

ZERO RISK. 30 day 100% Money-Back Guarantee!
That's right! You can test-drive the course for a full 30 days, try it out, and if you aren’t happy, we will happily refund 100% of your money. No funny business.

We can do this because we know you are going to totally love the course, but yes, you have a rock-solid 30 day money back guarantee to give you that extra security :)!

Frequently Asked Questions

When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.

Get started now!