What you Will be taught ?
- carry out the evaluation of covariance
- run the one-way within-subjects evaluation of variance
- run the two-way within-subjects evaluation of variance
- run the blended evaluation of variance
- carry out the non-parametric Friedman check
- execute the binomial logistic regression
- run the multinomial logistic regression
- carry out the ordinal logistic regression
- carry out the multidimensional scaling
- carry out the principal element evaluation and the issue evaluation
- run the easy and a number of correspondence evaluation
- run the cluster evaluation (k-means and hierarchical)
- run the easy and a number of discriminant evaluation
If you wish to discover ways to carry out actual superior statistical analyses within the R program, you may have come to the correct place.
Now you don’t should scour the online endlessly so as to discover how one can do an evaluation of covariance or a blended evaluation of variance, how one can execute a binomial logistic regression, how one can carry out a multidimensional scaling or an element evaluation. Every thing is right here, on this course, defined visually, step-by-step.
So, what’s coated on this course?
To start with, we’re going to examine some extra strategies to guage the imply variations. Should you took the intermediate course- which I extremely suggest you – you discovered in regards to the t exams and the between-subjects evaluation of variance. Now we are going to go to the following stage and deal with the evaluation of covariance, the within-subjects evaluation of variance and the blended evaluation of variance.
Subsequent, within the part in regards to the predictive strategies, we are going to strategy the logistic regression, which is used when the dependent variable will not be steady – in different phrases, it’s categorical. We’re going to examine three sorts of logistic regression: binomial, ordinal and multinomial.
Then we’re going to deal with the grouping strategies. Right here you’ll find out, intimately, how one can carry out the multidimensional scaling, the principal element evaluation and the issue evaluation, the easy and the a number of correspondence evaluation, the cluster evaluation (each k-means and hierarchical) , the easy and the a number of discriminant evaluation.
So after ending this course, you can be an actual professional in statistical evaluation with R – you’ll know quite a lot of refined, state-of-the artwork evaluation strategies that can can help you deeply scrutinize your information and get probably the most data out of it. So don’t wait, enroll in the present day!
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- R and R studio
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