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Analytics | Learn SAS

Rick WicklinOctober 14, 2019 2

Compute the geometric mean for many variables in SAS

I recently wrote about how to use PROC TTEST in SAS/STAT software to compute the geometric mean and related statistics. This prompted a SAS programmer to ask a related question. Suppose you have dozens (or hundreds) of variables and you want to compute the geometric mean of each. What is

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Analytics | Data Visualization

Rick WicklinOctober 9, 2019 9

What statistic should you use to display error bars for a mean?

In a previous article, I mentioned that the VLINE statement in PROC SGPLOT is an easy way to graph the mean response at a set of discrete time points. I mentioned that you can choose three options for the length of the "error bars": the standard deviation of the data,

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Analytics | Programming Tips

Rick WicklinOctober 2, 2019 25

Compute the geometric mean, geometric standard deviation, and geometric CV in SAS

I frequently see questions on SAS discussion forums about how to compute the geometric mean and related quantities in SAS. Unfortunately, the answers to these questions are sometimes confusing or even wrong. In addition, some published papers and web sites that claim to show how to calculate the geometric mean

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Analytics | Programming Tips

Rick WicklinSeptember 25, 2019 2

Solve many optimization problems

One of the strengths of the SAS/IML language is its flexibility. Recently, a SAS programmer asked how to generalize a program in a previous article. The original program solved one optimization problem. The reader said that she wants to solve this type of problem 300 times, each time using a

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Analytics | Data Visualization | Programming Tips

Rick WicklinSeptember 16, 2019 0

The Hull moving average: Implement a custom time series smoother in SAS

A moving average is a statistical technique that is used to smooth a time series. My colleague, Cindy Wang, wrote an article about the Hull moving average (HMA), which is a time series smoother that is sometimes used as a technical indicator by stock market traders. Cindy showed how to

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Analytics | Data Visualization | Programming Tips

Rick WicklinSeptember 5, 2019 4

Use cosine similarity to make recommendations

When you order an item online, the website often recommends other items based on your purchase. In fact, these kinds of "recommendation engines" contributed to the early success of companies like Amazon and Netflix. SAS uses a recommender engine to suggest articles on the SAS Support Communities. Although recommender engines

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Analytics | Data Visualization | Programming Tips

Rick WicklinSeptember 3, 2019 8

Cosine similarity of vectors

An important application of the dot product (inner product) of two vectors is to determine the angle between the vectors. If u and v are two vectors, then cos(θ) = (u ⋅ v) / (|u| |v|) You could apply the inverse cosine function if you wanted to find θ in

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Analytics

Rick WicklinAugust 12, 2019 5

The math you learned in school: Yes, it’s useful!

What is this math good for, anyway? –Every student, everywhere I am a professional applied mathematician, yet many of the mathematical and statistical techniques that I use every day are not from advanced university courses but are based on simple ideas taught in high school or even in grade school.

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Analytics

Rick WicklinJuly 22, 2019 9

Extreme values: What is an extreme value for normally distributed data?

Is 4 an extreme value for the standard normal distribution? In high school, students learn the famous 68-95-99.7 rule, which is a way to remember that 99.7 percent of random observation from a normal distribution are within three standard deviations from the mean. For the standard normal distribution, the probability

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Analytics | Learn SAS | Programming Tips

Rick WicklinJune 26, 2019 1

Jump-start PROC LOGISTIC by using parameter estimates from PROC HPLOGISTIC

SAS/STAT software contains a number of so-called HP procedures for training and evaluating predictive models. ("HP" stands for "high performance.") A popular HP procedure is HPLOGISTIC, which enables you to fit logistic models on Big Data. A goal of the HP procedures is to fit models quickly. Inferential statistics such

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