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Statistical Analysis Using R
By: Michael Grogan
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  •    DURATION: 2h 00min
  •  LANGUAGE: English
  •  EXPERTISE LEVEL: Advanced
  •  CATEGORY: Data Science

Online Course Description

Want to vastly improve your knowledge of statistics and R? This class will show you how.

You will learn how to use R to analyse cross-sectional datasets, and generate valuable data-driven insights.

My two-hour session will go through:

1. How to work with data using the RStudio platform.

2. Analysing data using linear models (Ordinary Least Squares, Logistic Regressions).

3. Violations of Ordinary Least Squares models and how to correct them.

4. An introduction to time series modelling.

In addition to a live session, you will also get access to important course materials such as code scripts and datasets which you can use to replicate the examples that we cover in class.

Look forward to working with you!


  • Live video call and screen sharing with Michael Grogan
  • Schedule a call at a time convenient for you
  • Prior to session you will be able to get in touch with Michael Grogan to explain your background and what you are trying to achieve
  • Prior to session, Michael Grogan will provide list of resources and materials needed to prepare for session
  • You will be able to cancel a class and get a refund up to 24h before the scheduled session
  • Moneyback guarantee

Statistical Analysis Using R

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Michael Grogan

Murcia | Member since May 13, 2017
I am a data scientist with a passion for statistics and programming, specialising mainly in Python and R. I currently work as a data science consultant, and my clients have included individuals, startup firms, as well as larger corporate clients. I have worked on projects across a range of industries, including finance, sales and marketing, healthcare, and government policy. Through my classes, you will benefit from my expertise in both programming knowledge in Python and R, as well as gain in-depth insights into statistics and machine learning techniques. Here is an overview of my skills: Programming Experience: Python (3 years), R (4 years), Shiny (1 year), mySQL (4 years), C++ (1 year), SPSS (2 years), STATA (2 years), Microsoft Azure (1 year) Statistics and Machine Learning: ANOVA, ARIMA and Holt-Winters, Decision Trees, Fixed Effects Estimation, GARCH, K-Means Clustering, Linear Regression Modelling (OLS and Logistic Regressions), Monte Carlo Simulations, Neural Network Modelling, Probability Distributions, Stationarity Testing and Cointegration Analysis, Time Series Decomposition Libraries: car, corpcor, covmat, egcm, lmtest, neuralnet, pandas, matplotlib, MySQLdb, numpy, pyodbc, rpart, rvest, Scikit-learn, scipy, statsmodels, tseries
Data Analysis Mysql Python Statistics Machine Learning

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