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Statistics with R – Beginner Level

Basic statistical analyses using the R program
Instructor:
Bogdan Anastasiei
89,518 students enrolled
English [Auto]
manipulate data in R (filter and sort data sets, recode and compute variables)
compute statistical indicators (mean, median, mode etc.)
determine skewness and kurtosis
get statistical indicators by subgroups of the population
build frequency tables
build cross-tables
create histograms and cumulative frequency charts
build column charts, mean plot charts and scatterplot charts
build boxplot diagrams
check the normality assumption for a data series
detect the outliers in a data series
perform univariate analyses (one-sample t test, binomial test, chi-square test for goodness-of-fit)

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!

Introduction

1
Introduction

Data Manipulation in R

1
Filtering Data Using Brackets

How to filter your data frames with brackets (in base R).

2
Filtering Data With the Subset Command

How to filter your data frames using subsets.

3
Filtering Data With dplyr

How to filter your data set using the dplyr package

4
Recoding Categorical Variables

How to recode categorical variables in R

5
Recoding Continuous Variables

How to recode continuous variables in R

6
Sorting Data Frames

How to sort data sets using various criteria

7
Compute New Variables

How to compute new variables based on the existing ones

8
R Codes File for the First Chapter

All the codes used in the lectures 2-8, for your reference

9
Practical Exercises for the First Chapter

Practical exercises for the lectures 2-8

Descriptive Statistics

1
Using Base R to Generate Statistical Indicators

How to compute the statistical indicators (mean, median, standard deviation etc.) in base R

2
Descriptive Statistics with the psych Package

How to compute statistical indicators with the psych package

3
Descriptive Statistics with the pastecs Package

How to compute statistical indicators using the pastecs package

4
Determining the Skewness and Kurtosis

How to compute skewness and kurtosis in R

5
Computing Quantiles

How to detemine the quantiles of a distribution

6
Determining the Mode

How to compute the mode of a distribution

7
Getting the Statistical Indicators by Group with DoBy

How to compute the statistical indicators by groups using the DoBy package

8
Getting the Statistical Indicators by Group with DescribeBy

How to compute the statistical indicators with the DescribeBy package

9
Getting the Statistical Indicators by Group with stats

How to compute the statistical indicators with the stats package

10
R Codes File for the Second Chapter

All the codes used in the lectures 11-19, for your reference

11
Practical Exercises for the Second Chapter

Practical exercises for the lectures 11-19

Creating Frequency Tables and Cross Tables

1
Frequency Tables in Base R

How to build frequency tables

2
Frequency Tables with plyr

How to build frequency tables using the package plyr

3
Building Cross Tables using xtabs

Creating cross-tables with the xtabs command

4
Building Cross Tables with CrossTable

Creating cross-tables with the CrossTable command

5
R Codes File for the Third Chapter
All the codes used in the lectures 22-25, for your reference
6
Practical Exercises for the Third Chapter
Practical exercises for the lectures 22-25

Building Charts

1
Histograms

How to create a histogram for your distribution

2
Cumulative Frequency Line Charts

How to create cumulative frequency line charts

3
Column Charts

How to build column charts

4
Mean Plot Charts

How to build mean plot charts

5
Scatterplot Charts

How to build scatterplot charts

6
Boxplot Charts

How to build boxplot charts

7
R Codes File for the Fourth Chapter
All the codes used in the lectures 28-33, for your reference
8
Practical Exercises for the Fourth Chapter

Practical exercises for the lectures 28-33

Checking Assumptions

1
Checking the Normality Assumption - Numerical Method

How to check for normality using numerical methods

2
Checking the Normality Assumption - Graphical Methods

How to check for normality using graphical methods

3
Detecting the Outliers

How to detect the extreme values in your data series

4
R Codes File for the Fifth Chapter

All the codes used in the lectures 36-38, for your reference

5
Practical Exercises for the Fifth Chapter
Practical exercises for the lectures 36-38

Performing Univariate Analyses

1
One-Sample T Test

How to run and interpret the one-sample t test

2
Binomial Test

How to run and interpret the binomial test

3
Chi-Square Test For Goodness-of-Fit

How to perform the chi-square test for goodness-of-fit

4
R Codes File for the Sixth Chapter

All the codes used in the lectures 41-43, for your reference

5
Practical Exercises for the Sixth Chapter
Practical exercises for the lectures 41-43

Course Materials

1
Download Links

Here you can download the csv files and the R files.

You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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