There is an ocean of books on statistics; where do you start? A big problem in choosing a beginner book on statistics is that a book may suffer one of two common problems. It may be a mathematical textbook filled with derivations, special cases, and proofs for each statistical method with little idea for the […]
Tom Mitchell’s classic 1997 book “Machine Learning” provides a chapter dedicated to statistical methods for evaluating machine learning models. Statistics provides an important set of tools used at each step of a machine learning project. A practitioner cannot effectively evaluate the skill of a machine learning model without using statistical methods. Unfortunately, statistics is an […]
Statistics is a collection of tools that you can use to get answers to important questions about data. You can use descriptive statistical methods to transform raw observations into information that you can understand and share. You can use inferential statistical methods to reason from small samples of data to whole domains. In this post, […]
Statistical hypothesis tests can be used to indicate whether the difference between two samples is due to random chance, but cannot comment on the size of the difference. A group of methods referred to as “new statistics” are seeing increased use instead of or in addition to p-values in order to quantify the magnitude of […]
Statistical methods are used at each step in an applied machine learning project. This means it is important to have a strong grasp of the fundamentals of the key findings from statistics and a working knowledge of relevant statistical methods. Unfortunately, statistics is not covered in many computer science and software engineering degree programs. Even […]
You do not need to know statistics before you can start learning and applying machine learning. You can start today. Nevertheless, knowing some statistics can be very helpful to understand the language used in machine learning. Knowing some statistics will eventually be required when you want to start making strong claims about your results. In […]
Data transformations enable data scientists to refine, normalize, and standardize raw data into a format ripe for analysis. These transformations are not merely procedural steps; they are essential in mitigating biases, handling skewed distributions, and enhancing the robustness of statistical models. This post will primarily focus on how to address skewed data. By focusing on […]
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In the world of real estate, numerous factors influence property prices. The economy, market demand, location, and even the year a property is sold can play significant roles. The years 2007 to 2009 marked a tumultuous time for the US housing market. This period, often referred to as the Great Recession, saw a drastic decline […]
In the realm of inferential statistics, you often want to test specific hypotheses about our data. Using the Ames Housing dataset, you’ll delve deep into the concept of hypothesis testing and explore if the presence of an air conditioner affects the sale price of a house. Let’s get started. Overview This post unfolds through the […]
