標(biāo)題: Titlebook: Beginning R; An Introduction to S Larry Pace Book 2012 Larry Pace 2012 [打印本頁(yè)] 作者: Amalgam 時(shí)間: 2025-3-21 19:48
書(shū)目名稱Beginning R影響因子(影響力)
作者: 奇怪 時(shí)間: 2025-3-22 00:07
http://image.papertrans.cn/b/image/182494.jpg作者: 小故事 時(shí)間: 2025-3-22 00:41 作者: CREEK 時(shí)間: 2025-3-22 08:21
Spezifische Sicherheitskonzepte,er. We will discuss the basics of programming in general, and the specifics of programming in R, including program flow, looping, and the use of logic. In Chapter 3, you will learn how to create your own useful R functions to keep from typing the same code repetitively. When you create functions, th作者: Junction 時(shí)間: 2025-3-22 08:45
Spezifische Sicherheitskonzepte,unctions and thousands more contributed by the R community. Before you consider writing your own function for a particular problem, check the R documentation and discussions to see if someone else has already done the work for you. One of the best things about the R community is that new packages ap作者: 流動(dòng)性 時(shí)間: 2025-3-22 15:28
,Kurzfassung und überblick für Eilige,and, more important, reports the statistical results. We cover the standard descriptive statistics from a business statistics class. If you have not taken statistics or are a little rusty, I recommend David Moore’s business statistics books. Although it is a toss-up whether to cover graphs or numeri作者: 闡明 時(shí)間: 2025-3-22 18:51 作者: Soliloquy 時(shí)間: 2025-3-22 21:14 作者: 兵團(tuán) 時(shí)間: 2025-3-23 02:40 作者: 匍匐前進(jìn) 時(shí)間: 2025-3-23 07:49 作者: lipoatrophy 時(shí)間: 2025-3-23 10:50 作者: 無(wú)底 時(shí)間: 2025-3-23 16:29
,Kurzfassung und überblick für Eilige,tween the observed and predicted variables. You also learn, as promised earlier, that the general linear model underlying multiple regression also underlies ANOVA and . tests, and you can use regression instead of those procedures to obtain the same (or more informative) results. You discover R’s fu作者: 別炫耀 時(shí)間: 2025-3-23 20:16 作者: Spirometry 時(shí)間: 2025-3-24 01:04 作者: harrow 時(shí)間: 2025-3-24 03:41 作者: 分貝 時(shí)間: 2025-3-24 08:42
Neue Anforderungen an den Datenschutz,s and work only with sample data. We will still be simulating, however, because we will use resampling and bootstrapping to generate multiple samples with replacement from our original data. In essence these are . techniques, because we are not making assumptions about populations when we analyze th作者: 永久 時(shí)間: 2025-3-24 12:27 作者: 神圣不可 時(shí)間: 2025-3-24 18:36 作者: Externalize 時(shí)間: 2025-3-24 19:28
,The “New” Statistics: Resampling and Bootstrapping,s and work only with sample data. We will still be simulating, however, because we will use resampling and bootstrapping to generate multiple samples with replacement from our original data. In essence these are . techniques, because we are not making assumptions about populations when we analyze the sample data.作者: 下級(jí) 時(shí)間: 2025-3-25 01:39
Zehn Schritte zum Sicherheitsmanagement,In Chapter 6, you learn how to use R for the binomial distribution and the Poisson distribution. We quickly review the characteristics of a discrete probability distribution, and then you learn the various functions in R that make it easy to work with both discrete and continuous distributions.作者: 慟哭 時(shí)間: 2025-3-25 07:16
Sicherheitsziele / Sicherheitsanforderungen,We have already discussed using the standard normal and . distributions for confidence intervals for means. We can construct confidence intervals for other statistics as well. Confidence intervals avoid some of the logical problems of null hypothesis testing and therefore is recommended as an alternative in many cases.作者: 復(fù)習(xí) 時(shí)間: 2025-3-25 10:56 作者: 效果 時(shí)間: 2025-3-25 14:47 作者: pus840 時(shí)間: 2025-3-25 18:26 作者: WAG 時(shí)間: 2025-3-25 22:14
Discrete Probability Distributions,In Chapter 6, you learn how to use R for the binomial distribution and the Poisson distribution. We quickly review the characteristics of a discrete probability distribution, and then you learn the various functions in R that make it easy to work with both discrete and continuous distributions.作者: Libido 時(shí)間: 2025-3-26 00:10 作者: Phonophobia 時(shí)間: 2025-3-26 05:24 作者: 有毒 時(shí)間: 2025-3-26 09:19
Using R for Simulation,R shines as a tool for simulations of all kinds. Simulations have been around for a very long time. I remember doing Monte Carlo simulations as a graduate student with FORTRAN-IV programs I wrote. That was fun, but R is far more versatile, and as a result, more fun.作者: 誘拐 時(shí)間: 2025-3-26 15:41 作者: Foolproof 時(shí)間: 2025-3-26 20:21 作者: 無(wú)可爭(zhēng)辯 時(shí)間: 2025-3-26 22:08
Martin Darms,Stefan Ha?feld,Stephen Fedtketribution of Karl Pearson, the chi-square distribution has proven to be quite versatile. We use chi-square tests for determining goodness of fit and for determining the association or lack thereof for cross-tabulated categorical variables.作者: AV-node 時(shí)間: 2025-3-27 03:22 作者: grounded 時(shí)間: 2025-3-27 09:13 作者: 豪華 時(shí)間: 2025-3-27 11:41 作者: Fester 時(shí)間: 2025-3-27 16:48
One-Way Analysis of Variance, two variances follows the . (named after R. A. Fisher) distribution. Some readers may have difficulty understanding why the analysis of variance components can be used to test hypotheses about means, but on reflection, one should realize that the variances themselves are based on squared deviations from means.作者: MOCK 時(shí)間: 2025-3-27 20:30 作者: 元音 時(shí)間: 2025-3-27 23:19
le, and freely-available programming language and statistica.Beginning R: An Introduction to Statistical Programming. is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-sou作者: 郊外 時(shí)間: 2025-3-28 02:41 作者: Laconic 時(shí)間: 2025-3-28 06:27 作者: Adrenal-Glands 時(shí)間: 2025-3-28 13:39 作者: 追逐 時(shí)間: 2025-3-28 15:38 作者: 腐爛 時(shí)間: 2025-3-28 22:44
Martin Darms,Stefan Ha?feld,Stephen Fedtke, such as employee rankings, while in other cases we convert interval or ratio data to ranks because the data violate distributional assumptions such as linearity, normality, or equality of variance. As a rule of thumb, nonparametric tests are generally less powerful than parametric tests, but that is not always the case.作者: 壯麗的去 時(shí)間: 2025-3-29 00:32
Writing Reusable Functions,ntation and discussions to see if someone else has already done the work for you. One of the best things about the R community is that new packages appear regularly, and it is quite likely someone else has already faced and solved the same programming problem. If they haven’t, it is easy enough to create your own functions.作者: 自愛(ài) 時(shí)間: 2025-3-29 03:39
Computing Normal Probabilities,normal distribution and distributions theoretically related to it, such as ., and ?., for testing hypotheses about means and functions of means (such as the differences between two or more means, or variances, which are derived from means).作者: Wernickes-area 時(shí)間: 2025-3-29 09:30 作者: 桉樹(shù) 時(shí)間: 2025-3-29 11:38 作者: 怎樣才咆哮 時(shí)間: 2025-3-29 17:14
Nonparametric Tests,, such as employee rankings, while in other cases we convert interval or ratio data to ranks because the data violate distributional assumptions such as linearity, normality, or equality of variance. As a rule of thumb, nonparametric tests are generally less powerful than parametric tests, but that is not always the case.作者: leniency 時(shí)間: 2025-3-29 22:35 作者: 類似思想 時(shí)間: 2025-3-30 02:52
,Kurzfassung und überblick für Eilige,cal summaries first, we will start with numerical summaries. We will cover measures of central tendency and spread, and the shape of a distribution. For this chapter, and for others, we will use common examples, and the same data will be used several different times.作者: myelography 時(shí)間: 2025-3-30 06:38
Zehn Schritte zum Sicherheitsmanagement, two variances follows the . (named after R. A. Fisher) distribution. Some readers may have difficulty understanding why the analysis of variance components can be used to test hypotheses about means, but on reflection, one should realize that the variances themselves are based on squared deviations from means.作者: 玷污 時(shí)間: 2025-3-30 09:55
Spezifische Sicherheitskonzepte,or problem with discriminant analysis, namely that it can take advantage only of continuous predictors. A more modern technique to the prediction (and classification as desired) of group membership in two groups represented by 0s and 1s is known as logistic regression. Logistic regression allows the use of both continuous and binary predictors.作者: FAZE 時(shí)間: 2025-3-30 15:49 作者: Mortal 時(shí)間: 2025-3-30 18:08 作者: LUT 時(shí)間: 2025-3-31 00:43
Programming in R, function call should perform a well-defined computation relying on the arguments passed to the function (or to default values for arguments). Everything in R is an object, including a function, and in this sense, R is an . programming language.作者: cortex 時(shí)間: 2025-3-31 01:01
Multiple Regression,As a bonus, I show you how to use matrix algebra to solve a regression model. This will enhance both your R skills and your statistical understanding, and will help you with more advanced topics such as multivariate analyses (which are beyond the scope of this beginning text).作者: separate 時(shí)間: 2025-3-31 08:46 作者: HEAVY 時(shí)間: 2025-3-31 12:44 作者: Fortify 時(shí)間: 2025-3-31 13:56 作者: 定點(diǎn) 時(shí)間: 2025-3-31 21:10
Writing Reusable Functions,unctions and thousands more contributed by the R community. Before you consider writing your own function for a particular problem, check the R documentation and discussions to see if someone else has already done the work for you. One of the best things about the R community is that new packages ap作者: Morbid 時(shí)間: 2025-4-1 00:16
Summary Statistics,and, more important, reports the statistical results. We cover the standard descriptive statistics from a business statistics class. If you have not taken statistics or are a little rusty, I recommend David Moore’s business statistics books. Although it is a toss-up whether to cover graphs or numeri作者: nuclear-tests 時(shí)間: 2025-4-1 03:09
Creating Tables and Graphs,y tables and for various graphical representations of data. As with many of the other functions of R, you will learn that the methods R provides often produce quite different results depending on the input.作者: 偽造 時(shí)間: 2025-4-1 06:38 作者: 褲子 時(shí)間: 2025-4-1 10:29 作者: atopic 時(shí)間: 2025-4-1 18:21
Advanced Analysis of Variance,s of ANOVA allow us to evaluate the combined effect of two or more factors or to examine multiple measurements on the dependent variable. In Chapter 13, where we discuss multiple regression, we will illustrate how the same linear model underlies both regression and ANOVA models and how we can use re
