Applied Statistical Modeling for Data Analysis in R
$129.99 Track price
APPLIED STATISTICAL MODELING FOR DATA ANALYSIS IN R
COMPLETE GUIDE TO STATISTICAL DATA ANALYSIS & VISUALIZATION FOR PRACTICAL APPLICATIONS IN R
Confounded by Confidence Intervals? Pondering Over p–values? Hankering Over Hypothesis Testing?
Hello, My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).
I have several years of experience in analyzing real life data from different sources using statistical modeling and producing publications for international peer reviewed journals. If you find statistics books & manuals too vague, expensive & not practical, then you re going to love this course!
I created this course to take you by hand and teach you all the concepts, and take your statistical modeling from basic to an advanced level for practical data analysis.
With this course, I want to help you save time and learn what the arcane statistical concepts have to do with the actual analysis of data and the interpretation of the bespoke results. Frankly, this is the only one course you need to complete in order to get a head start in practical statistical modeling for data analysis using R.
Courses : 17
Specification: Applied Statistical Modeling for Data Analysis in R
16 reviews for Applied Statistical Modeling for Data Analysis in R
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DONNIE MINNICK –
seems like good material
Christopher Rangarirai Chimombe Musiiwa –
Yes its a good match for me
Sawom Tweety –
The class is awesome! The instructor spoke very clear and was very knowledgeable and patient. Good curriculum and resources. One of the best training classes I have ever done!!
Sadia mumu –
I’ve never completed a course like this before and I cannot express how great the instructor was and the overall content of the material. I would definitely recommend this to my co workers.
Mustakim Tashfi –
So far, so good ! Glad I chose this statistical modeling course. Lot’s of information and premium tricks are explained elaborately! Hats off instructor!
Sanjida Tasnim –
Thanks very much for everything. All good, learnt lots. In depth understanding sections of Statistical Modeling & applying this practically in R.
Rainuma naurin –
I thing there should be a 6star option for such delightful course! All the contents are super useful for statistical modeling. Course syllabus covered almost everything. Enjoyed the course very much from first to last!
Ariel Sell s Gras –
Un recorrido por un amplio conjunto de herramientas, como punto de partida para analizar las necesidades de mi proyecto.
Wyatt Wilson –
Would appreciate zooming in on the code a bit more
Micah Shull –
Very informative lectures with lots of examples and useful resources!
Sirajem Munira –
This has been totally easy and fun to learn as topics are broken into tiny chunks of information. Great and easily understandable course content. I found the course concise, robust, and informative. Highly recommended!
Dipongkor Sen –
I honestly loved this course and having tried other places I can safely and confidently say this was the best. The instructor is lively and enthusiastic and is a gifted teacher. I love the frequent quizzes and code challenges and the final code challenge was a challenge. Resources were awesome!
Nishat Jahan –
This instructor seriously puts everything in the simplest of terms. I love the fact I was able to actually complete the sessions! I got a little stuck and I was intimidated by the quizzes, but I got it. I literally had it. Thank you!
Anna Mudumala –
I thought it was for beginners but the instructor said we should have some prior knowledge.
George Via –
She does a very good job in explaining the coding.
Helena Rolle –
Lectures were progressive in content; Fair balance of materiaL length; Lecturer well voiced and may in a few cases, have provided further explanations; Expected a bit more of the quizzes given the content (and background) of the sectional materials; Course basically encompassed 1st year statistical concepts in a precise way; Demos were comprehensive pulling from a variety of dataset which one could visualize.