RStudio Bootcamp- for Data Management, Statistics & graphics

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Soumyajit Halder

12:38:36

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01 - Installation and Introduction to R Studio

001 Course Introduction.mp4

07:17

002 How to install R Studio.mp4

08:13

003 Introduction To R Studio.mp4

17:57

003 introduction-to-rstudio.zip

02 - Inputs and Outputs

001 Input Techniques.mp4

29:11

001 inputs-code.zip

002 Outputs-Rstudio.txt

002 Output Techniques.mp4

11:43

03 - Data Management

001 IncomeData.xlsx

001 Structure and Metadata.mp4

14:40

001 unit-2-data-management.zip

001 usedcarsales.xlsx

002 Derived Variables and Data Manipulation.mp4

11:20

003 Merging, Combining and Subsetting Datasets.mp4

46:30

004 Date and Time Variables.mp4

05:25

04 - Statistical and Mathematical Functions

001 Probability Distribution and Random Number Generation.mp4

19:40

001 Unit3-Statistical-and-Mathematical-Functions.txt

001 unit3.zip

001 usedcarsales.xlsx

002 Mathematical Functions.mp4

19:03

003 Matrix Operations.mp4

13:09

05 - Programming and Operating System (OS) Interface

001 Programming and OS interface.mp4

16:52

001 Unit4.txt

001 unit4.zip

001 usedcarsales.xlsx

06 - Common Statistical Procedures

001 GDPandCPI.xlsx

001 Summary Statistics.mp4

35:55

001 Unit5.txt

001 unit5.zip

001 usedcarsales.xlsx

002 Bivariate Statistics and Tests for Continuous Variables.mp4

18:28

07 - Linear Regression and ANOVA

001 Regression Basics.mp4

22:34

001 Regression-Basics.docx

002 Linear Regression and ANOVA.mp4

26:13

002 Unit6.txt

002 unit6.zip

002 usedcarsales.xlsx

003 Residuals and Diagnostic Plots.mp4

19:08

08 - Regression Generalizations and Modeling

001 Binary Logistic Regression - Basics.mp4

11:50

001 Binary-Logistic-Regression-Basics.docx

002 Binary Logistic Regression - R Studio.mp4

49:38

002 Binomial-Logistic-Regression-Code.txt

002 binomial-logistic-regression.zip

002 gender-submission.csv

002 test.csv

002 train.csv

003 Poisson Regression - R Studio.mp4

40:50

003 Poisson-Regression.txt

003 lungcancerdata.xlsx

003 poisson-regression.zip

004 Factor Analysis Using R Studio.mp4

31:00

004 Factor-Analysis-using-R.txt

004 factor-analysis-using-r.zip

004 places.csv

005 Survival Analysis in R - Using Kaplan-Meier Plot.mp4

36:10

005 survival-analysis-on-r.zip

005 turnover.csv

006 Survival Analysis in R - Cox Hazard Regression.mp4

06:21

09 - Graphical Compendium

001 Univariate Plots.mp4

31:23

001 graphical-compendium.zip

001 usedcarsales.xlsx

002 Bivariate Plots.mp4

08:38

003 Some Special Purpose Plots - Maps and Interaction Plots.mp4

18:48

004 Some Special Purpose Plots - Circular and Normal Q-Q Plots.mp4

04:14

005 ROC Curve.mp4

08:04

005 studentmarks.xlsx

10 - Graphical Options and Configurations

001 Graphical Options in Detail.mp4

30:50

001 Scatterplot-Price-vs-Age.pdf

001 graphical-options-and-configuration.zip

001 usedcarsales.xlsx

002 Options and Paramters.mp4

09:51

11 - Time Series Analysis

001 Section-05-Carsales.csv

001 Section-05-Carsales.xlsx

001 Time Series Analysis Using R - Part I.mp4

30:51

001 time-series-analysis.zip

002 Time Series Analysis Using R - Part II.mp4

41:56

12 - Simulation

001 Simulation Part I - Categorical Data, tTest & Logistic Regression Simulation.mp4

30:49

001 simulation.zip

002 Simulation Part II - Monty Hall Simulation.mp4

24:05

Description

A complete guide to RStudio- from performing simple operations, to developing complex models, visualization & simulation

What You'll Learn?

Primary goal is to provide users with an easy way to learn how to perform an analytics task in RStudio.
Includes many common tasks, including data management, descriptive summaries, inferential procedures, regression analysis, multivariate methods and graphics.
Includes some complex applications such as Simulation
Tried to provide a simple classroom type approach that is easy to understand for a new user, and supplied several solutions where deemed necessary.

Who is this for?

If you intend to be a professional analyst, who use multiple statistical packages daily, this course is for you !

Useful for statisticians, epidemiologists, economists, engineers, physicians, sociologists and others engaged in data analysis.

This course intends to bolster the analytic abilities of a new user as well

What You Need to Know?

Those who have an understanding of Basic Statistics upto the level of Multiple Regression Analysis. If not, don't worry as this course covers basics before climbing up the ladder.

More details

Description
R is a general purpose statistical software package used in many fields of research. It is licensed for free - an open source software. It has large user and growing developer base.
I have developed this course for users of R. My primary goal is to provide an easy way to learn how to perform an analytic task in this system, without having to go through complex documentations. This course will give you a classroom like training experience and covers vast topics such as data management, descriptive summaries. inferential procedures, regression analysis, time series analysis, multivariate methods, simulation and graphics.
Therefore this course not only teaches you to clean and analyze data, it also gives you a pavement to develop colorful reports for the purpose of management communication.
I did not attempt to complicate things in as many ways as possible to keep the understanding sweet and simple. I have given a simple approach that is easy to understand for a new user, and have tried to provide several solutions where deemed possible.
I request you to watch the lectures at your own pace and practice the codes one by one with the given and new datasets. This will enhance your learning even more.
Who this course is for:
If you intend to be a professional analyst, who use multiple statistical packages daily, this course is for you !
Useful for statisticians, epidemiologists, economists, engineers, physicians, sociologists and others engaged in data analysis.
This course intends to bolster the analytic abilities of a new user as well

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Hi, I'm Soumyajit Halder, completed my MBA from one of the esteemed institutions in India. I completed my undergraduation in Aerospace Engineering where I took project related to Computer Aided Design, MATLAB Coding and Drop Test Analysis using MSC ADAMS.I also managed a health checkup campaign for about a week where I applied management skills and also handled and uploaded Data regularly. I also have experience working as a call center data analyst in a hospital. I'm a keen enthusiast towards Analytics and Data Science and have got certifications for R software and Supply Chain Analytics. I am also a beginner in Python (Pandas and Jupyter) and Android Studio App Development. I also participated in Kaggle Competition where I forecasted Walmart's sale for next 30 days.I also love to meet new people and discuss new ideas. Ping if you want to discuss something, always happy to help and looking for a mutual connection.

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