Hypothesis testing can be an overwhelming topic to grasp if you're new to the subject. As well as dealing with all of the different terminology, you have to perform several steps to run a test. Even if you use software, you have decisions to make at each step, such as what you're testing in the first place and what kind of wiggle room for error you're…Continue
Added by Stephanie Glen on April 6, 2020 at 12:58pm — No Comments
In a previous blog post, I created a flow chart showing how to choose a statistical test from a dozen different tests. While researching the article, I came across a short and sweet version which only includes four of the more basic tests:…Continue
At first glance, the Lognormal, Weibull, and Gamma distributions distributions look quite similar to each other. Selecting between the three models is "quite difficult" (Siswadi & Quesenberry) and the problem of testing which distribution is the best fit for data has been studied by a multitude of researchers.
If all the models fit the data fairly…Continue
Added by Stephanie Glen on March 27, 2020 at 7:30am — No Comments
If you've been keeping up on the statistics for Covid-19 in the last week (and who hasn't?), you've probably noticed a wide variety of projections for deaths in the United States, ranging from the "best-case" scenario (327 people) to the "doomsday" figure (2.2 million). Recent statistics published include:
My original intent with this article was to write about how to understand statistics in general. However, with the global pandemic on everyone's minds right now, it seems blithe to write an article on understanding statistics without a nod to current events. If you're uncomfortable or unfamiliar with statistics, you might find the facts and figures surrounding Covid-19 hard to decipher. Let's break down the key statistics into plain English and shed a little light on a few…Continue
Data science uses many different probability distributions, but some are used more than others. This one picture shows an overview of five probability distributions data scientists will find the most useful. See below the image for more information about the distributions.
Added by Stephanie Glen on February 29, 2020 at 3:00pm — No Comments
I live in Jacksonville, Florida, where the odds of a hurricane on any given day are "improbable". But does that mean I shouldn't stock up on hurricane supplies and have an emergency preparedness plan? Far from it. Hurricane Irma blew through my city in 2017, causing around $85 million in damage and the worst…Continue
Added by Stephanie Glen on February 21, 2020 at 12:00pm — No Comments
Machine learning algorithms learn in three ways: unsupervised, supervised, and semi supervised. This picture illustrates the differences between the three types.
Added by Stephanie Glen on February 14, 2020 at 12:30pm — No Comments
You don't have to take college classes to learn statistics. If you just want some basic information about a particular statistical topic, then StatisticsHowTo.com is a great way to start. But if you're looking for more structured training and perhaps a certification, you've got a lot of good options.
If you have zero to little statistics or programming knowledge, these…Continue
Added by Stephanie Glen on February 7, 2020 at 3:00pm — No Comments
Fifty years, ago, the lines between "data analysis" and "statistical analysis" were pretty clear. But as data analysis evolved, those lines became blurred. The differences between the two terms are now very much a grey area, but there are still a few notable differences.
Data scientists and statisticians typically define "data analysis" in different ways.
Added by Stephanie Glen on January 31, 2020 at 3:30am — No Comments
Hundreds of programming languages dominate the data science and statistics market: Python, R, SAS and SQL are standouts. If you're looking to branch out and add a new programming language to your skill set, which one should you learn? This one picture breaks down the differences between the four languages.
Below are more…Continue
In my previous post, I discussed the differences between Business Intelligence and Business Analytics. Two other terms that are often confused are Business Analytics and Data Analytics, but they are actually quite separate entities. This one picture highlights the differences between the two…Continue
Added by Stephanie Glen on January 18, 2020 at 7:12am — No Comments
Business Intelligence (BI) and Business Analytics (BA) are both used to interpret business information and create data-based action plans. The two terms are frequently used interchangeably, and many people consider one to be a subset of the other (there's some disagreement about whether BI is a subset of BA, or BA is a subset of BI). However, it might be more accurate to describe them as two arms of successful business planning: BI tells you the…Continue
Business intelligence is an umbrella term covering a variety of ways to collect, store and analyze business operations and activities data. This one picture shows you the different processes and methods that make up the business intelligence sphere.
Added by Stephanie Glen on December 27, 2019 at 9:58am — No Comments
Predictive analytics, prescriptive analytics and the fairly recent offshoot-- discovery analytics-- can all support business decision making. Although the three tools are very similar in that they build off the same analytic foundation, the types of decisions they support are quite different. This one picture explains the differences between the three methods.…Continue
Predictive analytics is a wide field of techniques that share a common goal of predicting future behavior. Choosing the right prediction modeling method is perhaps the most important step in the process, because predictive models are the driving force behind predictive analytics. This picture summarizes six of the most popular methods:…Continue
Added by Stephanie Glen on December 21, 2019 at 3:30pm — No Comments
If you ask the question "What's the best degree for Data Science?" you'll get dozens of different answers. The sheer amount of different opinions might leave you wondering which degree is the "best", and there isn't a simple answer. One person's "best" degree is another person's "worst."
Trying to make sense of all those differing opinions? I've done the hard work for you. This is where statistics is actually very useful (and it's one of the popular choices for…Continue
In my last blog post, I covered the statistics you need to know for data science. But of course, stats isn't the only math related knowledge you need. Rather than offer my own biased opinion about the importance of this subject vs. that one, I performed a meta analysis of popular opinion to see what data scientists and educators are saying (see…Continue
Added by Stephanie Glen on December 14, 2019 at 7:00am — No Comments
Added by Stephanie Glen on December 9, 2019 at 7:30am — No Comments
At the time of writing, I'm a 52 year-old working in the fields of mathematics and data science. In mathematics, that makes me well-seasoned (and probably well-tenured, if I had chosen to continue in academia). In data science, some would consider me a dinosaur. In fact, many older people considering a career in data science might be put off by the thought that data science is tough to break into at a later age. But is that statement true? Should the over 50 crowd put down their textbooks…Continue