In univariate data analysis, the median is often used as an alternative to the mean because the mean is sensitive to outliers in the data, whereas the median is a robust statistic. For higher-dimensional data, the mean and the centroid are both used to represent the "center" of a cloud
Many data analysts are familiar with logistic regression, where the response variable, Y, has two observed values, often represented as Y=0 and Y=1. The case Y=0 encodes that an event did not happen. For example, a patient did not experience some disease or did not die. The opposite case (Y=1)
A previous article discusses various ways to overlay a density curve on a histogram in SAS. SAS provides several procedures that handle this task for common univariate probability distributions such as normal, lognormal, and gamma. If you define and use a less common distribution, you can write a GTL template
SAS has several procedures that can fit a probability distribution to data, plot a histogram, and overlay one or more density estimates: PROC UNIVARIATE in Base SAS enables you to overlay parametric density curves from about 20 common continuous probability distributions, such as normal, lognormal, and gamma. It also enables
SAS supports more than 25 common probability distributions for the PDF, CDF, QUANTILE, and RAND functions. If you need a less-common distribution, you can implement new distributions by using Base SAS (specifically, PROC FCMP) or the SAS/IML language. On the SAS Support Communities, a SAS programmer asked how to implement
A previous article discusses Cohen's d statistic and how to compute it in SAS. For a two-sample independent design, Cohen's d estimates the standardized mean difference (SMD). Because Cohen's d is a biased statistic, the previous article also computes Hedges' g, which is an unbiased estimate of the SMD. Lastly,
What is Cohen's d statistic and how is it used? How can you compute it in SAS? This article gives some history behind Cohen's d statistic. It shows how to compute the statistic in SAS for the difference in means between two independent samples. It shows how to estimate a
SAS provides procedures to fit common probability distributions to sample data. You can use PROC UNIVARIATE in Base SAS or PROC SEVERITY in SAS/ETS software to estimate the distribution parameters for approximately 20 common distributions, including normal, lognormal, beta, gamma, and Weibull. Since there are infinitely many distributions, you may
Dating can be a challenge. No, I'm not talking about the process of finding a soulmate. I'm talking about managing days, weeks, months, and years in statistical analyses and reports! One challenge is how to number the weeks of the year. Because there are seven days in a week, 52
While researching a topic on effect sizes, I learned about a SAS function that is related to noncentrality parameters. I previously wrote an article about the noncentral t distribution, which is one of several well-known distributions that contains an optional noncentrality parameter. I mentioned that the PDF, CDF, and QUANTILE
