Data Science Topics
Financial Analysis and Time Series Forecasting
- ARIMA and Holt-Winters Forecasting
- GARCH Volatility Modelling
- Momentum Forex Trading Using The R Quantmod Library
- Decision Trees: Classification and Regression Trees in R
- K-Means Clustering: An Example of Stock Returns and Dividend Yields
- Neural Network Modelling Using R
- Handling of Non-Normal Data: Use of Box-Cox Transformation
- OLS: Running an Ordinary Least Squares regression in R
- Python: How To Use statsmodels Library To Regress With Multiple Independent Variables
Python and R
- Data Cleaning and Merging in R
- MySQLdb: Connecting Python and mySQL Together
- Python: Monte Carlo Stock Price Simulation Using Random Walk
Get my free e-book!
Please don’t forget to subscribe to my mailing list to receive your free copy of my e-book; “R: Regression Analysis and Data Structuring Methods”.
The book covers how to:
► Run an OLS Regression in R and test for violations
► Conduct time series analysis including cointegration techniques
► Strucuture data effectively using data frames
Along with this e-book, you will also gain access to customised templates demonstrating how to conduct statistical analysis using the R Programming Language.
About Me (Michael Grogan)
My name is Michael Grogan, I am a data scientist with a passion for statistics and programming.
My background is originally in economics, having graduated with a Master’s degree. However, as time went on I increasingly found myself drawn to the more statistical elements of the subject, such as econometrics, business analytics and quantitative finance.
I frequently began to improve my knowledge in programming languages linked to statistics and big data, including Python, R and SQL, which I have increasingly utilised when working on data science projects for a variety of clients, both in an individual and commercial capacity. If you have a project you need assistance with, or even just have general questions about data science, I would love to hear from you.
I founded this website to illustrate the use of the primary data science languages in conducting statistical analysis and implementing machine learning algorithms. Additionally, my website goes into depth on a range of cross-sectional and time series methods of analysis, including probability and forecasting methods.
Please contact me at firstname.lastname@example.org.
“Michael’s website is a fantastic reference point for anyone interested in Data Science. He provides real world problems and solutions, showing practical applications often lacking in online resources. He approaches Data Science from a strong mathematics background, providing a fresh perspective not found in the mostly computer science based tutorials.”
Ben Larson – Founder of Analytics4all
“This is a superb effort, and we certainly want to publish this. To be honest, I don’t get many article drafts as well written, structures and crafted as this, so special kudos for that.”