Statistics with R - Intermediate Level
Statistical analyses using the R program
Statistics with R - Intermediate Level udemy course
Statistical analyses using the R program
What you'll learn:
- run parametric and non-parametric correlation (Pearson, Spearman, Kendall)
- perform partial correlation
- run the chi-square test for association
- run the independent sample t test
- run the paired sample t test
- execute the one-way analysis of variance
- perform the two-way and three-way analysis of variance
- run the one-way multivariate analysis of variance
- run non-parametric tests for mean difference (Mann-Whitney, Kruskal-Wallis, Wilcoxon)
- execute the multiple linear regression
- compute the Cronbach's alpha
- compute other reliability indicators (Cohen's kappa, Kendall's W)
Requirements:
- R and R studio
- knowledge of statistics
Description:
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. Statistics with R - Intermediate Level Udemy
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!
Who this course is for:
- students
- PhD candidates
- academic researchers
- business researchers
- University teachers
- anyone looking for a job in the statistical analysis field
- anyone who is passionate about quantitative analysis
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Course Details:
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2.5 hours on-demand video
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9 articles
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8 downloadable resources
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Full lifetime access
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Access on mobile and TV
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Certificate of completion
Statistics with R - Intermediate Level udemy free download
Statistical analyses using the R program
Demo Link: https://www.udemy.com/course/statistics-with-r-intermediate-level/
