Statistics with R – Beginner Level
If you want to learn how to perform the basic 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 compute the statistical indicators in R, how to build a cross-table, how to build a scatterplot chart or how to compute a simple statistical test like the one-sample t test. 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 manipulate data in R, to prepare it for the analysis: how to filter your data frame, how to recode variables and compute new variables.
Afterwards, we will take care about computing the main statistical figures in R: mean, median, standard deviation, skewness, kurtosis etc., both in the whole population and in subgroups of the population.
Then you will learn how to visualize data using tables and charts. So we will build tables and cross-tables, as well as histograms, cumulative frequency charts, column and mean plot charts, scatterplot charts and boxplot charts.
Since assumption checking is a very important part of any statistical analysis, we could not elude this topic. So we’ll learn how to check for normality and for the presence of outliers.
Finally, we will perform some basic, one-sample statistical tests and interpret the results. I’m talking about the one-sample t test, the binomial test and the chi-square test for goodness-of-fit.
So after graduating this course, you will know how to perform the essential statistical procedures in the R program. So… enroll today!
Data Manipulation in R
How to filter your data frames with brackets (in base R).
How to filter your data frames using subsets.
How to filter your data set using the dplyr package
How to recode categorical variables in R
How to recode continuous variables in R
How to sort data sets using various criteria
How to compute new variables based on the existing ones
All the codes used in the lectures 2-8, for your reference
Practical exercises for the lectures 2-8
How to compute the statistical indicators (mean, median, standard deviation etc.) in base R
How to compute statistical indicators with the psych package
How to compute statistical indicators using the pastecs package
How to compute skewness and kurtosis in R
How to detemine the quantiles of a distribution
How to compute the mode of a distribution
How to compute the statistical indicators by groups using the DoBy package
How to compute the statistical indicators with the DescribeBy package
How to compute the statistical indicators with the stats package
All the codes used in the lectures 11-19, for your reference
Practical exercises for the lectures 11-19
Creating Frequency Tables and Cross Tables
How to build frequency tables
How to build frequency tables using the package plyr
Creating cross-tables with the xtabs command
Creating cross-tables with the CrossTable command
How to create a histogram for your distribution
How to create cumulative frequency line charts
How to build column charts
How to build mean plot charts
How to build scatterplot charts
How to build boxplot charts
Practical exercises for the lectures 28-33
How to check for normality using numerical methods
How to check for normality using graphical methods
How to detect the extreme values in your data series
All the codes used in the lectures 36-38, for your reference
Performing Univariate Analyses
How to run and interpret the one-sample t test
How to run and interpret the binomial test
How to perform the chi-square test for goodness-of-fit
All the codes used in the lectures 41-43, for your reference
Here you can download the csv files and the R files.