Description
What you’ll learn

You will first learn the basic statistical concepts, followed by application of these concepts using R Studio. This course is a nice combination of theory and practice.

Descriptive Statistics – Mean, Mode, Median, Skew, Kurtosis

Inferential Statistics – One and two sample z, t, Chi Square, F Tests, ANOVA, TukeyHSD and more.

Probability Distributions – Normal, Binomial and Poisson

You will learn R programming from the beginning level.
Perform simple or complex statistical calculations using R Programming! – You don’t need to be a programmer for this 🙂
Learn statistics, and apply these concepts in your workplace using R.
The course will teach you the basic concepts related to Statistics and Data Analysis, and help you in applying these concepts. Various examples and datasets are used to explain the application.
I will explain the basic theory first, and then I will show you how to use R to perform these calculations.
Following areas of statistics are covered:
Descriptive Statistics – Mean, Mode, Median, Quartile, Range, Inter Quartile Range, Standard Deviation. (Using base R function and the psych package)
Data Visualization – 3 commonly used charts: Histogram, Box and Whisker Plot and Scatter Plot (using base R commands)
Probability – Basic Concepts, Permutations, Combinations (Basic theory only)
Population and Sampling – Basic concepts (theory only)
Probability Distributions – Normal, Binomial and Poisson Distributions (Base R functions and the visualize package)
Hypothesis Testing – One Sample and Two Samples – z Test, tTest, F Test, ChiSquare Test
ANOVA – Perform Analysis of Variance (ANOVA) step by step doing the manual calculation and by using R.
Who this course is for:
 Anyone who want to use statistics to make fact based decisions.
 Anyone who wants to learn R and R Studio for career in data science.
 Anyone who thinks Statistics is confusing and wants to learn it in plain and simple language.
Course content
 1. Getting Started with R and R Studio
 2. Bonus Section: Descriptive Statistics Theory (lessons from my other course)
 3. Descriptive Statistics Using R
 4. Vectors, Factors, Lists, Matrix and Data Frames in R
 5. Data Visualization
 6. Descriptive Statistics Revisited
 7. Bonus Section: Basic Probability Theory (lessons from my other course)
 8. Probability Distributions
 9. Inferential Statistics – Hypothesis Tests
 Bonus Section
Donny Phan –
Super practical. Lessons are catered towards anyone looking to find work in this industry. It felt very comprehensive and gave me a broad understanding of the programming spectrum
Madhav raj Verma –
Thanks for your great effort. i am fully satisfied with this course the way you teach and your explanation are very clear ,The content you provide in your course no one can do this at this price.
Sachin Gupta –
I really didn’t want to leave a low rating as Angela is a great teacher. The 1st half of this course was terrific. The 2nd half was terrible. Under the justification of “teaching students how to figure things out on their own”, pretty much all videos and all explanations were dropped. You were just told what to do, given links to documentation and told to figure it out on your own. I understand doing that to some degree, but to revert to that entirely for nearly half the content barely makes this a course. It’s just a list of things for you to learn, then you’re left on your own to learn them. The 2nd half was so bad, especially the data science component, that I didn’t bother finishing the course.
Vincent Beaudet –
Amazing 40 days course.
Angela is a great teacher.
The other 60 days are all about web developement, interacting with web pages, on your own with little to no explanations. I did not expect that at all. I wanted to learn more about software and scripting.
This left me disappointed , confused and i started to doubt myself. Not a fun experience after the amount of effort i’v put in this course.
Exercices format and explanations for the first 40 days were worth it tho.
Ben K –
Not just an introduction to python, but really helps you learn fundamental aspects of python and coding in general. Some parts may require some knowledge on the subject (data science comes to mind) and there is quite some web development in the course. So, a few areas were not completely to my liking (I would have liked to see it done differently), but this course deserves the 5 stars in my opinion.
Omid Alikhel –
I found the method a bit difficult when a code is written and then changed back to something different, with no enough explanation of how something happened and where it came from or a step by step explanation of why something is happening, i have no doubt in the instructors talent, but we are beginners!
Devang Jain –
The course is not updated and most of the solution codes don’t work and there are no video solutions towards the end
Szymon Kozak –
I think that the course tutor is really good in giving right information to learn at the right time. Thanks to this fact, my understanding of coding in python after 29 days of learning is above my expectations.
Begoña Ruiz Diaz –
Ha sido la mejor elección que podría haber hecho.
Vaibhav Sachdeva –
I want to thank Angela for making such an amazing course. It really helped me explore more things with python.