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Statistics with R - Beginner Level

Basic statistical analyses using the R program
Rating: 4.3 out of 54.3 (1,302 ratings)
94,370 students
Created by Bogdan Anastasiei
Last updated 12/2020
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • 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)

Requirements

  • R and R studio
  • knowledge of basic statistics

Description

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!

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

Course content

8 sections • 46 lectures • 2h 48m total length

  • Preview05:45

  • Preview07:56
  • Filtering Data With the Subset Command
    05:07
  • Filtering Data With dplyr
    04:03
  • Recoding Categorical Variables
    05:46
  • Recoding Continuous Variables
    05:04
  • Sorting Data Frames
    04:10
  • Compute New Variables
    01:52
  • R Codes File for the First Chapter
    00:06
  • Practical Exercises for the First Chapter
    00:06

  • Using Base R to Generate Statistical Indicators
    03:36
  • Descriptive Statistics with the psych Package
    03:42
  • Descriptive Statistics with the pastecs Package
    04:56
  • Determining the Skewness and Kurtosis
    01:35
  • Computing Quantiles
    02:15
  • Determining the Mode
    01:29
  • Getting the Statistical Indicators by Group with DoBy
    05:12
  • Getting the Statistical Indicators by Group with DescribeBy
    02:42
  • Getting the Statistical Indicators by Group with stats
    04:29
  • R Codes File for the Second Chapter
    00:06
  • Practical Exercises for the Second Chapter
    00:06

  • Frequency Tables in Base R
    06:40
  • Frequency Tables with plyr
    05:00
  • Building Cross Tables using xtabs
    01:24
  • Building Cross Tables with CrossTable
    04:20
  • R Codes File for the Third Chapter
    00:06
  • Practical Exercises for the Third Chapter
    00:06

  • Histograms
    07:09
  • Cumulative Frequency Line Charts
    11:20
  • Column Charts
    05:36
  • Mean Plot Charts
    13:57
  • Scatterplot Charts
    11:22
  • Boxplot Charts
    06:02
  • R Codes File for the Fourth Chapter
    00:06
  • Practical Exercises for the Fourth Chapter
    00:06

  • Checking the Normality Assumption - Numerical Method
    02:22
  • Checking the Normality Assumption - Graphical Methods
    03:36
  • Detecting the Outliers
    02:05
  • R Codes File for the Fifth Chapter
    00:06
  • Practical Exercises for the Fifth Chapter
    00:06

  • One-Sample T Test
    03:41
  • Binomial Test
    06:07
  • Chi-Square Test For Goodness-of-Fit
    07:08
  • R Codes File for the Sixth Chapter
    00:06
  • Practical Exercises for the Sixth Chapter
    00:06

  • Download Links
    00:03

Instructor

Bogdan Anastasiei
University Teacher and Consultant
Bogdan Anastasiei
  • 4.4 Instructor Rating
  • 5,531 Reviews
  • 195,922 Students
  • 12 Courses

      My name is Bogdan Anastasiei and I am an assistant professor at the University of Iasi, Romania, Faculty of Economics and Business Administration. I teach Internet marketing and quantitative methods for business. I am also a business consultant. I have run quantitative risk analyses and feasibility studies for various local businesses and been implied in academic projects on risk analysis and marketing analysis. I have also written courses and articles on Internet marketing and online communication techniques. I have 24 years experience in teaching and about 15 years experience in business consulting. 

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