By Gary L. Tietjen
Statistics is the accredited physique of tools for summarizing or describing info and drawing conclusions from the precis measures. every person who has information to summarize hence wishes a few wisdom of information. step one in gaining that wisdom is to grasp the pro jargon. This dictionary is geared to supply greater than the standard string of remoted and self sufficient definitions: it presents additionally the context, purposes, and comparable terminology. The meant viewers falls into 5 teams with fairly diverse wishes: (1) expert statisticians who have to keep in mind a definition, (2) scientists in disciplines except statistics who want to know the suitable equipment of summarizing information, (3) scholars of records who have to increase their knowl fringe of their subject material and make consistent connection with it, (4) managers who should be interpreting statistical stories written by way of their staff, and (5) newshounds who have to interpret executive or clinical experiences and transmit the data to the public.
Read or Download A Topical Dictionary of Statistics PDF
Similar statistics books
Impending computational statistics via its theoretical facets should be daunting. usually intimidated or distracted by way of the speculation, researchers and scholars can lose sight of the particular pursuits and purposes of the topic. What they want are its key ideas, an realizing of its equipment, adventure with its implementation, and perform with computational software program.
This e-book used to be written to supply source fabrics for academics to exploit of their introductory or intermediate information category. The bankruptcy content material is ordered alongside the traces of many well known facts books so it may be effortless to complement the content material and routines with category lecture fabrics. The ebook includes R script courses to illustrate vital themes and ideas coated in a information path, together with chance, random sampling, inhabitants distribution varieties, position of the important restrict Theorem, production of sampling distributions for statistics, and extra.
Compliment for the 1st version" . . . a very good addition to an upper-level undergraduate direction on environmental facts, and . . . a 'must-have' table reference for environmental practitioners facing censored datasets. " —Vadose sector JournalStatistical tools for Censored Environmental info utilizing Minitab® and R, moment version introduces and explains equipment for studying and examining censored facts within the environmental sciences.
Enterprise information in perform, 7th variation offers a latest, functional and designated framework for educating an introductory direction in enterprise facts. The textbook employs reasonable examples, carrying on with case reviews and a enterprise development topic to coach the cloth. The 7th version positive factors extra concise and lucid factors, a higher subject stream and a smart use of the easiest and such a lot compelling examples.
- Handbook of Fitting Statistical Distributions with R
- Spatial Statistics and Computational Methods
- Dynamic Linear Models with R (Use R!)
- Getting Started with Julia
- Essentials of Statistics for the Behavioral Sciences (8th Edition)
- Compstat 1984: Proceedings in Computational Statistics
Additional info for A Topical Dictionary of Statistics
05 for. a discrete distribution. We reject the null hypothesis if the observed number of successes in n trials is less than tl or greater than t2 • The sign test is a binomial test with p = 112. We can use it to test whether the p-th quantile is equal to a specified value. It is then called the quantile test. d. A possible form of non independence is correlation between consecutive observations, called serial correlation or autocorrelation, meaning that observations a distance of k units apart are correlated.
For the same reason, (T2 is a scale parameter. In the gamma distribution the parameter r is a shape parameter. :; a+'A) for all 'A> and all a. An estimator is most concentrated if it is more concentrated than any other estimator. Most concentrated estimators do not generally exist. The estimator T' is Pitnuin closer than T if p(lT' - al < IT - al) ;:,: 1/2 for all S. An estimator is Pitman closest if it is Pitman closer than any other estimator of S. We now classify several types of estimators according to the method used in finding them.
F(x» , and n+l n+l p is the cdf. In small samples the optimal weights are derived from the expected values and covariances of the order statistics. An R-estimator (for ranks) is a solution of 'i, sgn(Xj - A) r [R(IX j - AI)/ (n+ 1)] = 0, where r(u) = 1(112 + ul2), R(u) is the rank of u, and sgn is the signum function. The most efficient score function is leu) = (-f (x)! f(x)(P-\u». We now proceed to interval estimation, which consists of obtaining a pair of estimators to serve as the endpoints of a random interval in which the parameter will lie with some stated probability.