In a previous tutorial, we looked at how to create a simple PostgreSQL database of temperature across different world cities. The PostgreSQL database was created through a Linux terminal, and the same was then connected to R to import data/commit […]

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# Create PostgreSQL Database In Linux And Connect To R – Part I

PostgreSQL is a commonly used database language for creating and managing large amounts of data effectively. Here, you will see how to: 1) create a PostgreSQL database using the Linux terminal 2) connect the PostgreSQL database to R using the […]

Continue reading »# Creating functions in R

Functions are used to simplify a series of calculations. For instance, let us suppose that there exists an array of numbers which we wish to add to another variable. Instead of carrying out separate calculations for each number in the […]

Continue reading »# Poisson and Cumulative Binomial Probabilities

A Poisson Distribution is a probability distribution which calculates the probability of a set of independent occurrences within a fixed time or space. e.g. Let us suppose that a prestigious college receives 1000 applications in a particular time interval. On […]

Continue reading »# Creating maps in R using ggplot2 and maps libraries

Here is how we can use the maps, mapdata and ggplot2 libraries to create maps in R. In this particular example, we’re going to create a world map showing the points of Beijing and Shanghai, both cities in China. For […]

Continue reading »# Python: Implementing a K-Means Algorithm With sklearn

The below is an example of how sklearn in Python can be used to develop a k-means clustering algorithm. The purpose of k-means clustering is to be able to partition observations in a dataset into a specific number of clusters […]

Continue reading »# Variance-Covariance Matrix in R (corpcor, covmat)

The following tutorial demonstrates how to calculate a variance-covariance matrix in R, along with shrinkage estimate of covariance and the calculation of a covariance into a correlation matrix. The purpose of a variance-covariance matrix is to illustrate the variance of […]

Continue reading »# Linear Models in R: OLS and Logistic Regressions

We use linear models primarily to analyse cross-sectional data; i.e. data collected at one specific point in time across several observations. We can also use such models with time series data, but need to be cautious of issues such as serial […]

Continue reading »# Cross-Correlation Function In R (ccf)

When working with a time series, one important thing we wish to determine is whether one series “causes” changes in another. In other words, is there a strong correlation between a time series and another given a number of lags? […]

Continue reading »# Machine Learning and Statistics: Recommended Texts

For learning the latest machine learning and statistics techniques, I’ve found certain guides to be much more useful than others. The two main languages that I currently rely on are R and Python. I’ve found that R comes out on […]

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