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lunalovehj木蟲 (小有名氣)
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[求助]
生物統(tǒng)計學問題——試驗結果不知道該選用什么檢驗方法來分析顯著性差異？？
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樓主生物統(tǒng)計學知識沒學好，只會一部分SPSS，現在要寫文章了，不知道該怎么去分析數據的顯著性，求蟲友幫忙呀！��！ 圖中YY、XZ、WX分別代表不同的地方，H代表健康的三個生物學重復，I代表發(fā)病的三個生物學重復，現在算出來了U、D、H的指標來，這種結果應該用什么方法來表示顯著性呀？已經試過two-way ANOVA和把地點分開來做的獨立樣本T檢驗，但是總覺得不能做出“平均值±標準差（顯著性標注）”的形式，有沒有什么可以把這兩個因素都考慮進去的方法呀，求大師指點了！��！ 或者說寫文章的時候可以先分析two-way ANOVA，再分析獨立樣本T么？因為不止這三個指標哈，還有一些指標，在寫成文章的時候到底該怎么去表示呢？ 360截圖20141113213805543.jpg |
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lunalovehj
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wizardfan
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【答案】應助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★
lunalovehj: 金幣+50, ★★★很有幫助, 感謝，仔細閱讀了！ 2014-11-17 09:44:46
lunalovehj: 金幣+50, ★★★很有幫助, 感謝，仔細閱讀了！ 2014-11-17 09:44:46
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wiki page Analysis of variance (ANOVA) is a collection of statistical models used to analyze the differences between group means and their associated procedures (such as "variation" among and between groups), developed by R.A. Fisher. In the ANOVA setting, the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are equal, and therefore generalizes the t-test to more than two groups. As doing multiple two-sample t-tests would result in an increased chance of committing a statistical type I error, ANOVAs are useful in comparing (testing) three or more means (groups or variables) for statistical significance. T-tests the most frequently used ways are: A one-sample location test of whether the mean of a population has a value specified in a null hypothesis. A two-sample location test of the null hypothesis that the means of two populations are equal. All such tests are usually called Student's t-tests, though strictly speaking that name should only be used if the variances of the two populations are also assumed to be equal; the form of the test used when this assumption is dropped is sometimes called Welch's t-test. These tests are often referred to as "unpaired" or "independent samples" t-tests, as they are typically applied when the statistical units underlying the two samples being compared are non-overlapping.[6] A test of the null hypothesis that the difference between two responses measured on the same statistical unit has a mean value of zero. For example, suppose we measure the size of a cancer patient's tumor before and after a treatment. If the treatment is effective, we expect the tumor size for many of the patients to be smaller following the treatment. This is often referred to as the "paired" or "repeated measures" t-test:[6][7] see paired difference test. A test of whether the slope of a regression line differs significantly from 0. So select the statistical method according to your situation see http://abacus.bates.edu/~ganders ... low_chart_v2014.pdf |
4樓2014-11-16 09:18:39
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