Intended both as a textbook for students and as a resource for researchers, this volume emphasizes the statistical concepts and assumptions necessary to describe and make inferences about real data. Throughout the text the authors encourage the reader to plot and examine their data, find confidence intervals, use power analyses to determine sample size, and calculate effect sizes. The goal is to ensure the reader understands: the underlying logic and assumptions of the analysis and what it tells them; the limitations of the analysis; and the possible consequences of violating assumptions. Using an intuitive, informal style, the authors adopt a "bottom-up" approach - a simpler, less abstract discussion of analysis of variance is presented prior to developing the more general model. A concern for alternatives to standard analyses allows for the integration of non-parametric techniques into relevant design chapters, rather than in a single, isolated chapter. This organization allows for the comparison of the pros and cons of alternative procedures within the research context to which they apply. This second edition features a greater emphasis on: graphics - two early chapters are now largely devoted to examples and discussion of displays of data and there are more graphs throughout; confidence intervals - now are usually presented before hypothesis tests to help focus on the question "What is the size of the effect?" rather than "Is there an effect?"; measures of effect size - now are introduced earlier, in the context of the t test, and then are routinely discussed in a variety of research designs and analyses; power analysis - computer programs are now used to illustrate the calculation of power; tests of contrasts - now are introduced earlier as extensions of the usual two-sample t tests in order to simplify the discussion; elementary probability - a new chapter on basic probability serves as a review and a means for using the binomial distribution to introduce hypothesis testing; correlation and regression - now introduced earlier and with an increased emphasis on the most frequent misinterpretations made when using these analyses; real data sets - a free CD contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats.
發表於2024-11-15
Research Design and Statistical Analysis 2024 pdf epub mobi 電子書 下載
純粹是初學,考試考啥我總結啥。僅為瞭紀念我第一次用R+Markdown+latex寫東西玩。 http:嗬嗬pan.baidu.com嗬s嗬11OJg5(嗬 = / ) 為什麼使用的都是最最最基本的R命令呢?因為俺們考試的時候隻允許用這些。。。比如,計算t-test的power的時候,不許用power函數;做各種test的...
評分純粹是初學,考試考啥我總結啥。僅為瞭紀念我第一次用R+Markdown+latex寫東西玩。 http:嗬嗬pan.baidu.com嗬s嗬11OJg5(嗬 = / ) 為什麼使用的都是最最最基本的R命令呢?因為俺們考試的時候隻允許用這些。。。比如,計算t-test的power的時候,不許用power函數;做各種test的...
評分純粹是初學,考試考啥我總結啥。僅為瞭紀念我第一次用R+Markdown+latex寫東西玩。 http:嗬嗬pan.baidu.com嗬s嗬11OJg5(嗬 = / ) 為什麼使用的都是最最最基本的R命令呢?因為俺們考試的時候隻允許用這些。。。比如,計算t-test的power的時候,不許用power函數;做各種test的...
評分純粹是初學,考試考啥我總結啥。僅為瞭紀念我第一次用R+Markdown+latex寫東西玩。 http:嗬嗬pan.baidu.com嗬s嗬11OJg5(嗬 = / ) 為什麼使用的都是最最最基本的R命令呢?因為俺們考試的時候隻允許用這些。。。比如,計算t-test的power的時候,不許用power函數;做各種test的...
評分純粹是初學,考試考啥我總結啥。僅為瞭紀念我第一次用R+Markdown+latex寫東西玩。 http:嗬嗬pan.baidu.com嗬s嗬11OJg5(嗬 = / ) 為什麼使用的都是最最最基本的R命令呢?因為俺們考試的時候隻允許用這些。。。比如,計算t-test的power的時候,不許用power函數;做各種test的...
圖書標籤: 教材 實驗設計與統計
這是03版的,2010年的最新版的要一韆元左右,我買不起……呃,ANOVA部分寫得很清楚。我不是裝逼,是實在找不到相應地把REPEATED MEASURE和MIXED MODEL都同時講清楚的中文版……
評分這是03版的,2010年的最新版的要一韆元左右,我買不起……呃,ANOVA部分寫得很清楚。我不是裝逼,是實在找不到相應地把REPEATED MEASURE和MIXED MODEL都同時講清楚的中文版……
評分這是03版的,2010年的最新版的要一韆元左右,我買不起……呃,ANOVA部分寫得很清楚。我不是裝逼,是實在找不到相應地把REPEATED MEASURE和MIXED MODEL都同時講清楚的中文版……
評分這是03版的,2010年的最新版的要一韆元左右,我買不起……呃,ANOVA部分寫得很清楚。我不是裝逼,是實在找不到相應地把REPEATED MEASURE和MIXED MODEL都同時講清楚的中文版……
評分這是03版的,2010年的最新版的要一韆元左右,我買不起……呃,ANOVA部分寫得很清楚。我不是裝逼,是實在找不到相應地把REPEATED MEASURE和MIXED MODEL都同時講清楚的中文版……
Research Design and Statistical Analysis 2024 pdf epub mobi 電子書 下載