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 - Advanced Level
Master advanced statistical analyses in R, including covariance analysis, logistic regression, and multidimensional scaling with our step-by-step course.
via
Udemy
Brief Summary
This course takes you deep into advanced statistical analyses using R. You'll learn everything from evaluating mean differences to logistic regression and grouping techniques, all in a fun, step-by-step way!
Key Points
- Advanced statistical analyses using R
- Techniques for mean differences and variances
- Logistic regression for categorical data
- Grouping techniques like clustering and correspondence analysis
- Expertise in sophisticated analysis techniques
Learning Outcomes
- Perform analysis of covariance.
- Run one-way and two-way within-subjects analyses of variance.
- Execute binomial, ordinal, and multinomial logistic regression.
- Conduct factor analysis and multidimensional scaling.
- Become proficient in clustering and discriminant analysis.
About This Course
Advanced statistical analyses using the R program
If you want to learn how to perform real advanced 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 an analysis of covariance or a mixed analysis of variance, how to execute a binomial logistic regression, how to perform a multidimensional scaling or a factor analysis. Everything is here, in this course, explained visually, step by step.
So, what’s covered in this course?
First of all, we are going to study some more techniques to evaluate the mean differences. If you took the intermediate course- which I highly recommend you – you learned about the t tests and the between-subjects analysis of variance. Now we will go to the next level and tackle the analysis of covariance, the within-subjects analysis of variance and the mixed analysis of variance.
Next, in the section about the predictive techniques, we will approach the logistic regression, which is used when the dependent variable is not continuous – in other words, it is categorical. We are going to study three types of logistic regression: binomial, ordinal and multinomial.
Then we are going to deal with the grouping techniques. Here you will find out, in detail, how to perform the multidimensional scaling, the principal component analysis and the factor analysis, the simple and the multiple correspondence analysis, the cluster analysis (both k-means and hierarchical) , the simple and the multiple discriminant analysis.
So after finishing this course, you will be a real expert in statistical analysis with R – you will know a lot of sophisticated, state-of-the art analysis techniques that will allow you to deeply scrutinize your data and get the most information out of it. So don’t wait, enroll today!
perform the analysis of covariance
run the one-way within-subjects analysis of variance
run the two-way within-subjects analysis of variance
Course Curriculum
1 Lectures
12 Lectures
11 Lectures
12 Lectures
1 Lectures
Instructor
More Courses By Bogdan Anastasiei
Review
José L. M. R.
Bien.. habrá que poner un contexto escrito de lo que se busca encontrar en cada ejercicio, hace cálculos, aplica comandos bueno seria llevar en mente lo que se esta buscando poniéndolo por escrito . de alli bien y conciso
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Miguel E.
EL curso es bastante completo, da la guĂa básica para incursionar en el mundo del análisis de datos.
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Leandro D.
molto buona!
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Richard H.
Too many errors in the first couple of section . . . could be cleaned up easily by introducing the "as.factor" function, or including it in the notes.
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Qasim A.
Covers advanced stats in R. Good course and highly recommended
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Eli E.
The instructor is knowledgeable in the subject matter being taught.
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Vaibhav J.
Awesome đź‘Ťđź‘Ť
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Bryden M.
The presenter provides an informative, practical course which is easily applied in the business environment. This course provides valuable skills and I recommend it to anyone who needs to apply mathematics to their problem solving.
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Van T.
This course is well prepared. I appreciate the lecturer who tries to explain the R scripts and interpret results or outputs from the scripts which is great to me and perhaps to some learners. I feel some R beginners may find some difficulties to follow. Hope that helps. Big thanks to lecturer for this great course.
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