Average Annual Percent Change (AAPC) — Joinpoint Help System 184.108.40.206 While Joinpoint computes the trend in segments whose start and end are determined to best fit the data, sometimes it is useful to summarize the trend over a fixed predetermined interval. The AAPC is a method which uses the underlying Joinpoint model to compute a summary measure over a fixed pre-specified interval. Annual Percent Change (APC) is one way to characterize trends in cancer rates over time. With this approach, the cancer rates are assumed to change at a constant percentage of the rate of the previous year. For example, if the APC is 1%, and the rate is 50 per 100,000 in 1990, the rate is 50 x 1.01 = 50.5 in 1991 and 50.5 x 1.01 = 51.005 in 1992. Rates that change at a constant percentage every year change linearly on a log scale. One advantage of characterizing trends this way is that it is a measure that is comparable across scales, for both rare and common cancers. Average Annual Percent Change (AAPC) is a summary measure of the trend over a pre-specified fixed interval.
Statistique décisionnelle, Data Mining, Scoring et CRM Welcome to STAT 505! | STAT 505 - Applied Multivariate Statistical Analysis Printer-friendly version This is the STAT 505 online course materials website. All of the examples, notes, i.e., the lecture materials will all be found on this website. You may want to make a bookmark for this site. ANGEL is the other course website that will support our work in this course. Use the ANGEL discussion forums to pose questions and collaborate with others in this course to find answers. ANGEL is where you will find the course schedule, any annoucements, weekly work assignments, exams and the dropboxes for these assignments as well. Welcome to STAT 505!
Geometric standard deviation From Wikipedia, the free encyclopedia In probability theory and statistics, the geometric standard deviation (GSD) describes how spread out are a set of numbers whose preferred average is the geometric mean. For such data, it may be preferred to the more usual standard deviation. Note that unlike the usual arithmetic standard deviation, the geometric standard deviation is a multiplicative factor, and thus is dimensionless, rather than having the same dimension as the input values. Thus, the geometric standard deviation may be more appropriately called geometric SD factor. When using geometric SD factor in conjunction with geometric mean, it should be described as "the range from (the geometric mean divided by the geometric SD factor) to (the geometric mean multiplied by the geometric SD factor), and one cannot add/subtract "geometric SD factor" to/from geometric mean. Definition Derivation If the geometric mean is is positive for all ), so It can now be seen that
Factorial Analysis of Variance Factorial Analysis of Variance (ANOVA) One-way ANOVAs only allow us to examine one source of variance (one factor). There are situations (lots of situation) where we are interested in examine more than one source of variance. We will now examine 2 or more independent variables (or factors) on a single dependent variable. One-way ANOVA = 1 IV Two-way ANOVA = 2 IV (factorial ANOVA) Three-way ANOVA = 3 IV (factorial ANOVA) etc. When we covered research designs, we usually used X (treatment) and O (measure) to illustrate the design. What do the numbers (e.g., 3 X 2) mean? Factors can be assigned or active. Activity Design three research questions that would require a two-way ANOVA to analyze the data. Why not run 2 one-way ANOVAs? Ordinal Interaction (lines are not parallel) Disordinal Interaction (lines cross) but lines do not have to cross to be considered an interaction. The following graphic illustration are from Dr. Effects may be depicted graphically. Null Hypotheses 1. [data] Profile Plots
Center For Statistics And The Social Sciences Manuali di Statistica Lamberto Soliani con la collaborazione di Franco Sartore e Enzo Siri Email: firstname.lastname@example.org Tel.0521/905662 Fax 0521/905402 Le dispense (quasi 2500 pagine in 24 capitoli, più allegati) possono essere utilizzate gratuitamente. E' sufficiente cliccare il titolo del capitolo. A coloro che le utilizzano, l’autore chiede un favore - senza alcun impegno, ma solo per facilitare la raccolta di informazioni sul tipo di utenti e quindi adattare la scelta degli argomenti per edizioni future, è gradito l’invio di una e-mail, all’indirizzo: email@example.com Chi desidera seguire eventuali corsi e chi non trova l’argomento desiderato può inviare la sua richiesta, con un minimo di dettagli. Più che creare, trasmetto. Even more important than learning about statistical techniques is the development of what might be called a capability for statistical thinking. (Dal Preface di G. Da quanto in rete è stata tratta una versione abbreviata e una versione per la sola statistica non parametrica. 2. 6.
Venn Diagram Plotter | Pan-Omics Research Acknowledgment All publications that utilize this software should provide appropriate acknowledgement to PNNL and the OMICS.PNL.GOV website. However, if the software is extended or modified, then any subsequent publications should include a more extensive statement, as shown in the Readme file for the given application or on the website that more fully describes the application. Disclaimer These programs are primarily designed to run on Windows machines. Please use them at your own risk. Portions of this research were supported by the NIH National Center for Research Resources (Grant RR018522), the W.R. We would like your feedback about the usefulness of the tools and information provided by the Resource.
All your Bayes are belong to us! This week's post contains solutions to My Favorite Bayes's Theorem Problems, and one new problem. If you missed last week's post, go back and read the problems before you read the solutions! If you don't understand the title of this post, brush up on your memes. 1) The first one is a warm-up problem. Suppose there are two full bowls of cookies. First the hypotheses: A: the cookie came from Bowl #1 B: the cookie came from Bowl #2 And the priors: P(A) = P(B) = 1/2 The evidence: E: the cookie is plain And the likelihoods: P(E|A) = prob of a plain cookie from Bowl #1 = 3/4 P(E|B) = prob of a plain cookie from Bowl #2 = 1/2 Plug in Bayes's theorem and get P(A|E) = 3/5 You might notice that when the priors are equal they drop out of the BT equation, so you can often skip a step. 2) This one is also an urn problem, but a little trickier. The blue M&M was introduced in 1995. A friend of mine has two bags of M&Ms, and he tells me that one is from 1994 and one from 1996. Again, P(A) = P(B) = 1/2.
Plot Digitizer Big Data, Data Mining, Predictive Analytics, Statistics, StatSoft Electronic Textbook This free ebook has been provided as a public service since 1995. Statistics: Methods and Applications textbook offers training in the understanding and application of statistics and data mining. It covers a wide variety of applications, including laboratory research (biomedical, agricultural, etc.), business statistics, credit scoring, forecasting, social science statistics and survey research, data mining, engineering and quality control applications, and many others. The Textbook begins with an overview of the relevant elementary (pivotal) concepts and continues with a more in depth exploration of specific areas of statistics, organized by "modules", representing classes of analytic techniques. You have filtered out all documents.