It can be hard to find the perfect sample size for statistically sound results. Here we reveal methods and tools for effective sample size determination.
effect sizes and CIs in a normalizing metric, such as the log metric. The default tolerance to determine the CI asymmetry is 1e-6. Effect sizes and their CIs are often reported with limited precision that, after the normalizing transformation, may lead to asymmetric CIs. In that case, the...
For example, items sorting into different dimensions may reflect an insufficient sample size or hint that the item is multidimensional—that is, highly connected to two or more dimensions. From this sampling distribution several statistics can be obtained. These include descriptive statistics, like the...
Click on the file name of the date you wish to analyze; for example, "Jury.sav." ANOVA Step 1 Click on "Statistics" at the top of the SPSS screen. Then select "General Linear Model" from the dialog box and "Simple Factorial" from the drop-down box. Step 2 Highlight your dependent...
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g andCohen’s dare extremely similar. Both have an upwardsbias(an inflation) in results of up to about 4%. The two statistics are very similar except whensample sizesare below 20, when Hedges’ g outperforms Cohen’s d. Hedges’ g is therefore sometimes called thecorrected effect size. ...
Test different paragraph lengths and different levels of persuasion. Does your audience prefer the hard sell or a softer approach? Will you win over prospects with statistics or anecdotal copy? 2. CTAs Your call to action tells readers what you want them to do now. It should entice the reade...
We discuss how to perform each of these tests in the next section. But before you learn how to do them, it is imperative that you learn under what circumstances you should be using which test. The easiest way to determine which t-test is suitable for any scenario is by using the flowch...
How do you know when to reject the null hypothesis? Figure showing two possible decisions: reject or keep the null hypothesis. To determine whether or not to reject the null hypothesis, two common criteria are typically considered: Significance (alpha) level:Thesignificance levelrepresen...
In statistics, a spurious correlation, or spuriousness, refers to a connection between two variables that appears causal but is not. Learn why it matters.