生物实验数据的单因素方差分析

结合实例详细地叙述了生物学实验数据的单因素方差分析计算方法,介绍了根据计算结果如何分析组群间的差异显著性,具有较强的实用意义。     

SPSS方差分析在生物统计的应用

方差分析是生物统计中常采用的一种方法。如何使用统计分析软件进行方差分析来实现对研究结果的快速和科学的处理,获得正确的结论,是生物学研究中重要的一环。本文通过实例介绍了如何使用SPSS(Statistical Package for the Social Science or Statistic Products and Service Solution)数据分析工具进行方差分析的方法;实现了数据分析和处理的快捷、准确和直观;与Excel相比,SPSS的统计分析功能更为强大,既有利于提高数据处理效率,又降低了实验成本。     

生物实验数据的两因素方差分析

结合实例详细地叙述了生物实验数据的两因素方差分析计算方法,具有较强的实用意义。并介绍了如何分析计算结果。     

棉铃虫自然种群生命表及其初步分析

生命表技术起初是为社会人口统计而设计的,在资本主义国家则广泛应用于人寿保险事业,以确定保险费。五十年代以来,越来越多的昆虫学工作者利用生命表技术来研究、分析昆虫种群动态及其影响因素,确定种群的管理策略。关于昆虫生命表的组建、应用和分析方法,不少昆虫学者都已作过评论。概括说来,就是通过田间调查或一定条件下的室内试验,系统地观察、记录同时出生的某一昆虫种群在各个     

生态因素对蛾类昆虫交配与生殖的影响

对于两性生殖的昆虫而言,两性交配过程是产生后代及维持种群繁衍的必要环节。然而,昆虫的生殖行为经常受到一系列的内部生理因素和外部生态因素的影响,最终导致昆虫的生殖适合度产生差异。本文以蛾类昆虫为例,通过检索国内外文献,分析比较了气候因素(温度、湿度和光照)、生物因素(寄主植物、天敌和共生菌)和农事活动等生态因素对这类昆虫交配行为和生殖适合度的影响。结果表明,这些因子不但影响该类昆虫的交配行为(包括求偶与交配高峰、交配成功率、交配次数和交配持续时间等),还影响其生殖适合度(如产卵前期、产卵期、产卵量、孵化率和寿命等)。这些研究为深入开展蛾类昆虫的生殖行为生态学研究提供理论基础,同时为揭示蛾类昆虫的种群暴发机制以及该类害虫的科学防控提供线索。     

土壤中微生物含量影响因素的统计方法分析

【目的】采用多元方差分析、多元线性回归分析、通径分析等统计方法,并利用多元统计方法对土壤中微生物含量进行分析。【方法】通过研究这3种常用统计方法的原理、应用条件、适用于解决的问题等,用不同的方法分析影响土壤中微生物含量的各种因素,利用SPSS软件求解。【结果】得出不同降雨量下土壤中的微生物含量存在差异性;铵态氮含量和海拔高度与变形菌门含量呈显著的线性关系,土壤中变形菌门含量随着铵态氮含量增多而增多,且铵态氮含量对变形菌门含量所起的直接作用最大;土壤中铵态氮含量、总氮量和海拔高度与放线菌门含量呈显著的线性关系,且均为负相关;其中总氮量对土壤中放线菌门含量的变化所起的负面作用最大,但铵态氮含量对放线菌门含量所起的直接作用最大。对比描述性统计方法与多元方差分析方法可知,应用描述性统计方法只能得出降雨量是影响土壤中不同细菌群落相对含量的因素之一,而不知降雨量对微生物含量变化的影响程度,6个梯度降雨量引起地显著差异究竟是由哪种微生物引起的,方差分析方法可以解决以上的问题。对比多元线性回归分析方法与通径分析方法可知,多元线性回归分析得出的相关系数只能表示铵态氮含量、总氮量和海拔与变形菌门含量(放线菌门含量)之间关系的密切程度,但无法解释和分析这种关系的构成和来源,通径分析方法可以解决这个问题。【结论】通径分析方法在分析相关问题时要优于多元线性回归分析方法,通径分析比多元线性回归分析方法更能体现因素对变形菌门含量(放线菌门含量)的直接影响和间接影响,分析结论更直观、更能说明问题。     

昆虫抗冻耐寒能力的测定与分析方法

昆虫抗冻耐寒能力因其理论意义和实践价值成为当前生物学和生态学的重要研究内容。尤其昆虫抗冻耐寒能力的测定与分析是昆虫低温生物学的热点问题。本文从昆虫生态,及生理生化层面阐述了昆虫抗冻策略和耐寒机制类型。进一步介绍了昆虫抗冻耐寒能力的测定与分析方法:一方面,以昆虫种群为对象,分析低温对种群存活的胁迫作用,如低温实验中种群的存活率,致死中温度或致死中时间,冷伤害上限温度,冷害低温总和,以及低温冷伤害的死亡速率等。另一方面,以昆虫个体为对象,测定个体为适应低温环境而采取响应机制,如昆虫个体过冷却点、含水量、能量物质、抗冻小分子物质和抗冻蛋白含量等。在未来,从微观上看随着低温生物学拓展到基因组、转录组、蛋白质组及代谢组层次的研究,从宏观上看随着越冬代昆虫种群数量动态及其迁飞转移行为规律与栖息地微环境气候和区域性景观格局特征等的关系研究,有利于更全面地和深入地了解昆虫类群的抗冻策略或耐寒机制,从而为更系统地建立昆虫抗冻耐寒能力的测定与分析方法体系提供可靠指标。     

内蒙古锡林郭勒高原大针茅种群分株构件数量性状的地理变异研究

采用单因素方差分析、变异组分分析和分形几何学的原理和方法,对内蒙古锡林郭勒盟不同气候条件下的3个大针茅种群分株构件数量性状进行了研究,并结合它们所在生境特点对所得结果进行了分析。结果显示：（1）整个生长季内,不同种群大针茅营养枝高度的生长模式不同;营养枝高度和生殖枝高度在种群间差异显著,且多数变异存在于种群之间;（2）在不同生长期内,大针茅种群地上部干重与植株高度之间存在显著的分形关系;在无强度干扰的情况下,大针茅种群营养枝分形维数的大小与大针茅营养枝地上部干重的累积程度是一致的;但在长期严重干旱条件下,分形维数值表现为快速增加;（3）整个生长季内,同一生境条件下大针茅种群营养枝地上部干重与植株高度之间也存在显著的分形关系,且不同样地间分形维数值差异显著。不同生境条件下大针茅种群分株构件数量性状的差异是对所在生境长期适应、自然选择的结果。     

生物实验数据的单因素方差分析

结合实例详细地叙述了生物学实验数据的单因素方差分析计算方法,介绍了根据计算结果如何分析组群间的差异显著性,具有较强的实用意义.     

昆虫体内微生物多样性的影响因素研究进展

昆虫体内的微生物种类繁多,在长期的协同进化中与其宿主昆虫形成了密切的共生关系。近年来,随着分子生物学技术的快速发展与应用,昆虫体内微生物多样性得到广泛的研究。本文综述了影响昆虫体内微生物多样性的各种因素。体内微生物多样性除与昆虫种类相关外,还与昆虫自身因素(性别、发育龄期和种群)、生态因子(食物、温度、CO_2浓度和辐照)以及技术本身的局限性等方面密切相关。     

Prevalidation statistical design to assess analytical methods example of a quick liquid chromatographic assay of itraconazole in serum

(A) An analysis-of-varience spreadsheet program is presented which allows to readily test and/or quantitate in a single run analytical linearity, matrix effect on recovery, repeatability of measurement and of extraction and the ruggedness of these features for up to three sessions. Owing to napierian logarithmic transformation, ANOVA mean squares directly read as relative standard deviations and checking linearity is straightforward. (B) A quick assay for therapeutic drug monitoring of itraconazole and its main metabolite was devised with the help of the program, and subsequently validated according to current quality control recommendations. The assay involves acetonitrile demixing extraction, reversed-phase HPLC and UV detection and shows acceptable performance from 0.06 to 5.0 mg/l (limit of detection about 0.03 mg/l). The prevalidation design fairly predicted precision and accuracy, was more informative about matrix effect and was even more demanding about analytical linearity.     

A Procedure for Clustering Means of Unequal-Sized Samples in ANOVA

The proposed procedure “SECOLICO” is based on the sequential construction of linear contrasts. After an analysis of variance the procedure is able to classify the treatments represented by mean values of unequal-sized samples made at random into distinguishable groups. For the purpose of illustrating the procedure “SECOLICO” a simplified example is given.     

Statistical Methods for Using Nonlinear Models to Compare Silage Treatments

Statistical methods are described which can be used to compare treatments where the response is described by a nonlinear model. The nonlinear analysis of covariance is described for a one-way treatment structure and a two-way treatment structure. Methods for constructing confidence bands about a model and about the difference of two models are described. Examples involving the dynamics of silage fermentation are used to demonstrate the methods.     

Nonparametric Evaluation of ANOVA Designs by Local,Regional, and Global Contingency Testing

Nonparametric analysis of ANOVA designs is proposed to be done by simultaneous contingency testing of discretised response variables. Selected treatment-response patterns are evaluated by predictive configural frequency analysis (local contingency). Treatment response associations are defined by regional contingencies. Total treatment-response relation is defined by global contingency. All methods are illustrated numerically by biometrical examples.     

Convergence and historical effects in harvester ant assemblages of Australia, North America, and South America

In this paper I examine the extent to which contemporary ecological patterns in 42 harvester ant assemblages of three continents can be explained as a result of present-day environments or from differences in the history of each ant biota. The contribution of each factor to the overall variability of six community characters was evaluated by the ANOVA procedure. The mediod revealed absence of convergence in three-continent and pairwise-continent analyses in almost every community attribute that was measured. Significant convergence was detected only in die foraging score for the North America-South America comparison. This implies mat the foraging mode used by ants for searching seeds is more similar within similar environments in the two continents than between different environments in the same continent. Significant historical effects were much more prevalent than convergence both in three-continent and pairwise-continent comparisons. Abundance at baits, body size, and foraging distance were more variable within similar environments in different continents than between different environments in the same continent. The overall absence of convergence documented in this study suggests that constraints related to the evolutionary history of each species assemblage have inhibited convergent evolution in response to local selective pressures.     

Fertility Adjustments in Rectangular Field Trials

Based on Mandel's additive plus multipicative model for ANOVA, this paper presents a procedure to represent fertility differences in field trials arranged in rectangular plans. After fitting any block and treatment effects, the residuals are assigned to their positions in the rectangular planting plan, and then decomposed into orthogonal components, of which the largest ist attributed to fertility. If the variance associated with this component is significantly larger than those remaining, the observed data are then adjusted for it; the process is repeated until there is no significant component. The procedure is illustrated by data from a variety trial.     

Distance-based analysis of variance for brain connectivity

The field of neuroimaging dedicated to mapping connections in the brain is increasingly being recognized as key for understanding neurodevelopment and pathology. Networks of these connections are quantitatively represented using complex structures, including matrices, functions, and graphs, which require specialized statistical techniques for estimation and inference about developmental and disorder-related changes. Unfortunately, classical statistical testing procedures are not well suited to high-dimensional testing problems. In the context of global or regional tests for differences in neuroimaging data, traditional analysis of variance (ANOVA) is not directly applicable without first summarizing the data into univariate or low-dimensional features, a process that might mask the salient features of high-dimensional distributions. In this work, we consider a general framework for two-sample testing of complex structures by studying generalized within-group and between-group variances based on distances between complex and potentially high-dimensional observations. We derive an asymptotic approximation to the null distribution of the ANOVA test statistic, and conduct simulation studies with scalar and graph outcomes to study finite sample properties of the test. Finally, we apply our test to our motivating study of structural connectivity in autism spectrum disorder.     

Statistical Analysis of Factorial Diallel Design over Environments

Starting from the experimental situation that in each of a environments all mp combinations between m maternal and p paternal genotypes are raised in b replications (blocks), a linear model is formulated for a quantitative character. On the basis of this model formulae for the analysis of variance are given. The expectations of mean squares as well as the estimations of effects (general and specific combining ability and their interaction terms with environments) and their variances are given for different combinations of fixed and random factors.     

What is hierarchical selection?

It has been proposed that natural selection occurs on a hierarchy of levels, of which the organismic level is neither the top nor the bottom. This hypothesis leads to the following practical problem: in general, how does one tell if a given phenomenon is a result of selection on level X or level Y. How does one tell what the units of selection actually are? It is convenient to assume that a unit of selection may be defined as a type of entity for which there exists, among all entities on the same “level” as that entity, an additive component of variance for some specific component F of fitness which does not appear as an additive component of variance in any decomposition of this F among entities at any lower level. But such a definition implicitly assumes that if f(x, y) depends nonadditively on its arguments, there must be interaction between the quantities which x and y represent. This assumption is incorrect. And one cannot avoid this error by speaking of “transformability to additivity” instead of merely “additivity”. A general mathematical formulation of the concepts of interaction and non-interaction is proposed, followed by a correspondingly modified approach to the definition of a unit of selection. The practical difficulty of verifying the presence of hierarchical selection is discussed.