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Let’s assume the two middle groups have the means of grand mean, say g. Then we have (550 + g + g + 610) / 4 = g. This gives us g = (550 + 610)/2 = 580. Let’s now redo our sample size calculation with this set of means. So we see that at a power of .8, we have a sample size of 160, or 40 for each group. What about a small effect size; say, .25?
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Here we have one factor, music, with 2 levels. This factor is going to affect our two dependent variables, i.e., the test scores of maths and history. Denoting this information in terms of variables, we can say that we have L = 2 (2 different music treatment groups) and P = 2 (maths and history scores).
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Analysis of Variance (ANOVA) is a parametric statistical technique used to compare the data sets. This technique was invented by R.A. Fisher, hence it is also referred as Fisher’s ANOVA. It is similar techniques such as t-test and z-test , to compare means and …
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A one-way ANOVA compares the effects of an independent variable (a factor that influences other things) on multiple dependent variables. Two-way ANOVA does the same thing, but with more than one independent variable, while a factorial ANOVA extends the number of independent variables even further.
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Balanced designs (i.e., same number of subjects in each group) are ideal; ... The following steps reflect SPSS’s dedicated One-Way ANOVA procedure. However, since the One-Way ANOVA is also part of the General Linear Model (GLM) family of statistical tests, it can also be conducted via the Univariate GLM procedure (“univariate” refers to ...
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Balanced ANOVA: A statistical test used to determine whether or not different groups have different means. An ANOVA analysis is typically applied to a set of data in which sample sizes are kept ...
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An introduction to the one-way ANOVA. Published on March 6, 2020 by Rebecca Bevans. Revised on January 7, 2021. ANOVA, which stands for Analysis of Variance, is a statistical test used to analyze the difference between the means of more than two groups.. A one-way ANOVA uses one independent variable, while a two-way ANOVA uses two …
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(j) Number of entry-arm errors before finding platform. All data are shown as the mean ± s.e.m. * P < 0.05, t test ( b , c , g ), ANOVA with Dunnett's post-hoc test ( i …
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This is a case for ANOVA, which utilizes the F-distribution. Anytime you are comparing more than two groups, you will need the F-distribution for the F-test. The F-distribution is used for (surprise, surprise) the F-test.