Course Information
Course Overview
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!
Course Content
- 5 section(s)
- 37 lecture(s)
- Section 1 Introduction
- Section 2 Mean Difference Tests
- Section 3 Predictive Techniques
- Section 4 Grouping Methods
- Section 5 Course Materials
What You’ll Learn
- perform the analysis of covariance
- run the one-way within-subjects analysis of variance
- run the two-way within-subjects analysis of variance
- run the mixed analysis of variance
- perform the non-parametric Friedman test
- execute the binomial logistic regression
- run the multinomial logistic regression
- perform the ordinal logistic regression
- perform the multidimensional scaling
- perform the principal component analysis and the factor analysis
- run the simple and multiple correspondence analysis
- run the cluster analysis (k-means and hierarchical)
- run the simple and multiple discriminant analysis
Skills covered in this course
Reviews
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JJosé Luis Martínez Ramírez
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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RRichard Heller
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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TTim Clark
Very good course. Clear explanations. The only criticism is that there are no worked answers to the exercises. Therefore only 4 stars.
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VVarvara Vladimirova
Consistent way of teaching. Very good for those who like to practice with various examples. He explains everything quite thoroughly. However, for those of you who are impatient, it is not for you, as he will be repeating himself, and reminding about formulas that he previously explained. It would be good if he provided the data that he was using as well, so I can practice doing it myself (I had to create my own fake data). I have not done the exercises yet, will update when I do