with Iliya Valchanov

Covering descriptive and inferential statistics, as well as hypothesis testing techniques and exercises, statistics puts the “scientist” in data scientist.

5 hours 44 lessons
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44 High Quality Lessons
25 Practical Tasks
5 Hours of Content
Certificate of Achievement

Course Overview

Statistics is the driving force in any quantitative career. It is the fundamental skill that a data scientist needs in order to understand and design statistical tests and analysis using modern software packages and programming languages. In this course, we start from the very basics and gradually build your statistical thinking. This, in turn, enables you to understand the more complex analyses carried out later in the program.

Topics covered

data analysisExcelTheory

What You'll Learn

This course begins with the very basics of statistics and builds up your arithmetic thinking. It gradually teaches you how to work with more complex analyses, statistical approaches, and hypothesis.

Distinguish between the diverse types of data and levels of measurement 
Understand what a distribution is 
Calculate confidence intervals 
Perform hypothesis testing 
Become familiar with the p-value 


Student feedback


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Overall, a good course. Given I didn't know what to expect, and a complete newbie to this, I felt this would be a good investment. While in some respects it has been, I did find it wasn't entirely beginner friendly. Some concepts were not properly explained, while some were glossed over(i.e null hypothesis). Given what I've had to learn in other places, I just felt it wasn't done well here. Sometimes it made me question myself when in fact it wasn't entirely my fault. I was very dissatisfied with its delivery as I could tell the author of the course wasn't thinking about his/her audience. If the author indeed was then the course clearly isn't for me; I am not confident recommending it to friends as their money will be best spent elsewhere as total newbies. It has led me to approach other courses in the career track with a bit of apprehension, thus forcing me to supplement them with other resources elsewhere on the internet. I hope this gets revised in the future as there is indeed some potential. The graphics really do help visually but depth, clarity and simplicity in content delivery is just as important. Thanks.
I feel like this course assumed some knowledge of statistics. Nothing was explained in depth and I had to use alot of outside resources to understand course material and I still dont feel like I fully understand. There was also several time that regression analysis was said to be taught but its never actually taught in this course. Also there are a few issues where the downloaded excel file was not the same as the file being used in the lesson such as during the practical example at the end, the teacher used sample variance in the course and in the file we are shown population variance which just makes everything more confusing. If I am going to pay for courses I should not have to use free outside sources to learn the material.
It was very easy to understand and I would've liked more excersises instead of one exercise and also I would love to see a detailed explaination on every answer in Q&A section after submitting the correct answer. I just followed the recommended course of Datascience where it from fundamentalas and then moved onto Descriptive Statistics Fundamentals where the statistical analysis is not explained or how to use excel is been skippped. Even without these I found it very easy but time consuming to finish the excersise part manually.
I liked the small quizzes at the end of each lesson but they became less frequent in other sections as the material got harder. This course has a lot of information packed into fewer lessons, but there's less explanation on the actual equations. It would be nice if, since we're using excel, that there would be follow along demonstrations with the formulas used. I believe this course should be longer with follow along examples or even a second course to further explain.
It's not very clear on a lot of things, simple things too, like how to create the charts you use and how the formulas are written. It's not impossible to complete the class or the assignments but you kinda need to look outside the class to do it. I haven't taken the test yet, but my guess is there's going to be questions on it that were either not covered or were covered too vaguely to be helpful.
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Iliya Valchanov

“Statistics is the foundation of any quantitative career. This course 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.”

Iliya Valchanov

Co-founder at 365 Data Science


with Iliya Valchanov

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