Bogdan Anastasiei
Instructor
Bogdan Anastasiei is a skilled instructor known for providing valuable insights and expert guidance to learners seeking to enhance their knowledge and skills.
Statistics with R - Intermediate Level
Learn essential statistical analyses using R, from correlations to regression and reliability assessments. Enroll today for a comprehensive, step-by-step guide.
via
Udemy
Brief Summary
This course teaches you how to conduct essential statistical analyses using the R program. From correlation tests to regression and reliability measures, everything is laid out simply, making it fun and easy to learn.
Key Points
- Learn association tests in R: Pearson, Spearman, Kendall correlation
- Understand t tests and ANOVA for mean differences analysis
- Dive into multiple linear regression and hierarchical regression
- Check regression assumptions and compute reliability indicators
- Everything is visual and step-by-step for easy understanding
Learning Outcomes
- Perform parametric and non-parametric correlation tests confidently
- Execute t tests and ANOVA properly with clear interpretations
- Conduct multiple linear regression and check its assumptions
- Calculate reliability indicators like a pro in R
- Understand statistical concepts in a practical way
About This Course
Statistical analyses using the R program
If you want to learn how to perform the most useful statistical analyses in the R program, you have come to the right place.
Now you don’t have to scour the web endlessly in order to find how to do a Pearson or Spearman correlation, an independent t test or a factorial ANOVA, how to perform a sequential regression analysis or how to compute the Cronbach’s alpha. Everything is here, in this course, explained visually, step by step.
So, what will you learn in this course?
First of all, you will learn how to perform association tests in R, both parametric and non-parametric: the Pearson correlation, the Spearman and Kendall correlation, the partial correlation and the chi-square test for independence.
The test of mean differences represent a vast part of this course, because of their great importance. We will approach the t tests, the analysis of variance (both univariate and multivariate) and a few non-parametric tests. For each technique we will present the preliminary assumption, run the procedure and carefully interpret all the results.
Next you will learn how to perform a multiple linear regression analysis. We have assign several big lectures to this topic, because we will also learn how to check the regression assumptions and how to run a sequential (or hierarchical) regression in R.
Finally, we will enter the territory of statistical reliability – you will learn how to compute three important reliability indicators in R.
So after graduating this course, you will get some priceless statistical analysis knowledge and skills using the R program. Don’t wait, enroll today and get ready for an exciting journey!run parametric and non-parametric correlation (Pearson, Spearman, Kendall)
perform partial correlation
run the chi-square test for association
Course Curriculum
1 Lectures
6 Lectures
14 Lectures
6 Lectures
5 Lectures
1 Lectures
Instructor
More Courses By Bogdan Anastasiei
Review
Mr J. O.
Very concise course. Would benefit from a tutorial going over the practice exercises and explaining what the results mean.
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Reagan O.
Yes it has been a good match and it meet my expectations. Thanks very much for this.
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Juan P. A.
Creo que muestra de manera sencilla y practica como utilizar los códigos referentes a pruebas estadÃsticas
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Layla S.
It is easy to practice this instruction
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Eman M.
To the Point
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Eli E.
The instructor's explains step-by-step to implementing statistics in R. His explanations are lucid and clear.
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Raj K. D.
Really good experience. Very well explained
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Mashfika H.
I got to understand most of the lectures which I wanted from the course
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宇綺 �.
還ㄅ錯
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Iuliia A.
This is one is slightly better than the similar course for Beginners. However, all dataset are way too simple, so you don't practice on any real data set or experiments. The teacher, though, does explain how to interpret the tests output, which was somewhat useful for me. Again, there are not many exercices to practice and those present don't contain answers. The course is outdated, so I'd recommend choosing smth more fresh.