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# Tag Archives: statistics

## A Typology of Data Relationships

Nine patterns of three types of relationships that aren’t spurious. When analysts see a large correlation coefficient, they begin speculating about possible reasons. They’ll naturally gravitate toward their initial hypothesis (or preconceived notion) which set them to investigate the data relationship … Continue reading

Posted in Uncategorized
Tagged causality, causation, correlation, data relationships, statistics
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## The Evolution of Data Science … As I Remember It

Those who cannot remember the past are condemned to repeat it. George Santayana History isn’t always clear-cut. It’s written by anyone with the will to write it down and the forum to distribute it. It’s valuable to understand different perspectives … Continue reading

Posted in Uncategorized
Tagged articicial intelligence, big data, data analysis, data processing, data science, data wrangling, eniac, excel, gallup, history, mainframe, number crunching, python, SAS, SPSS, statistics, stats with cats
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## Anecdotes and Big Data

An anecdote is a kitten gently licking your face with a warm, wet,

raspy tongue. Big data is a three-inch, high-pressure, firehose held an arm’s length away. They have to be treated quite differently.

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## WHAT ARE THE ODDS?

Probability is the core of statistics. You hear the phrase “what’s the probability of …” all the time in statistics. You also hear that phrase in everyday life, too. What’s the probability of rain tomorrow? What’s the probability of winning … Continue reading

## PROBABILITY IS SIMPLE … KINDA

Language isn’t very precise in dealing with uncertainty. Probably is more certain than possibly, but who knows where dollars-to-doughnuts falls on the spectrum. Statistics needs to deal with uncertainty more quantitatively. That’s where probability comes in. For the most part, … Continue reading

## What To Look For In Data

Sometimes you have to do things when you have no idea where to start. It can be a stressful experience. If you’ve ever had to analyze a data set, you know the anxiety. Deciding how and where to start exploring … Continue reading

## What to Look for in Data – Part 2

What to Look for in Data – Part 1 discusses how to explore data snapshots, population characteristics, and changes. Part 2 looks at how to explore patterns, trends, and anomalies. There are many different types of patterns, trends, and anomalies, … Continue reading

Posted in Uncategorized
Tagged cats, censored data, curvilinear, cycles, data relationships, graphs, heteroskedasticity, homoskedasticity, interpolation, linear, outliers, shifts, shocks, simpson's paradox, statistics, stats wit cats, steps, time series, transformations, what to look for
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## DARE TO COMPARE – PART 4

Part 3 of Dare to Compare shows how one-population statistical tests are conducted. Part 4 extends these concepts to two-population tests. To review, this flowchart summarizes the the process of statistical testing. First, you PLAN the comparison by understanding the … Continue reading

Posted in Uncategorized
Tagged ANOVA, blogs, cats, populations, statistical comparisons, statistical tests, statistics, statswithcats, t-test
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## You Need Statistics to Make Wine

The American Statistical Association has identified 146 college majors that require statistics to complete a degree. You probably wouldn’t be surprised that statistics is required for degrees in mathematics, engineering, physics, astronomy, chemistry, meteorology, and even biology and geology. Most … Continue reading

Posted in Uncategorized
Tagged college degrees, college majors, statistics, stats with cats
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