Independent samples—more hypotheses testing

B. Knežević, Berislav Žmuk
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Abstract

Two-way analysis of variance (ANOVA) without replication is called a factorial ANOVA with two factors. It is used to test if there is a significant difference between means of several sets of data (groups) dependable on two independent factors. It is applied when we have one measurement variable and two nominal variables (usually called ‘factors’ or ‘main effects’). In this chapter hypotheses and assumptions of the method are given. Then the example of the procedure of two-way analysis of variance (ANOVA) without replication is described in details. The two-way analysis of variance (ANOVA) with replication is utilized to simultaneously test the effects of varying two variables for a sample which consists of more than one respondent per a certain combination of variables. The example of the procedure of two-way analysis of variance (ANOVA) with replication is described in details in this chapter. For both procedures the easy to follow examples shows the procedure stepby-step. The practical part includes the guidance for SPSS and for Excel.
独立样本——更多的假设检验
没有复制的双向方差分析(ANOVA)被称为具有两个因素的因子方差分析(factorial ANOVA)。它用于检验依赖于两个独立因素的几组数据(组)的平均值之间是否存在显著差异。当我们有一个测量变量和两个名义变量(通常称为“因素”或“主效应”)时,它被应用。在本章中,给出了方法的假设和假设。然后详细介绍了无重复的双向方差分析(ANOVA)过程的实例。具有复制的双向方差分析(ANOVA)用于同时测试变化两个变量对样本的影响,该样本由一个以上的受访者组成,每个特定的变量组合。本章详细描述了具有复制的双向方差分析(ANOVA)过程的示例。对于这两个过程,简单易懂的示例一步一步地展示了过程。实践部分包括SPSS和Excel的指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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