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Apr 8, 2012 · If the researcher finds a statistically significant difference between the two groups, he or she rejects the null and accepts the alternate hypothesis. But if the researcher fails to find a difference between the two groups, then the only conclusion that can be made is that “all possibilities remain.” [OK. End of academic speak.
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Definition of Distinction Without A Difference. The logical fallacy of Distinction Without a Difference occurs when someone attempts to label a single situation, fact, or concept with two different terms and argues that they are different, when in reality, there is no meaningful difference. This fallacy involves making a superficial or semantic ...
Look up distinction without a difference in Wiktionary, the free dictionary. A distinction without a difference is a type of logical fallacy where an author or speaker attempts to describe a distinction between two things where no discernible difference exists. [1] It is particularly used when a word or phrase has connotations associated with ...
- What Is Discrete Data?
- What Is Continuous Data?
- Discrete vs. Continuous Data Summary
Discrete variables can only assume specific values that you cannot subdivide. Typically, you count them, and the results are integers. For example, if you work at an animal shelter, you’ll count the number of cats. Discrete data can only take on specific values. For example, you might count 20 cats at the animal shelter. These variables cannot have...
Continuous variables can assume any numeric value and can be meaningfully split into smaller parts. Consequently, they have valid fractional and decimal values. In fact, continuous data have an infinite number of potential values between any two points. Generally, you measure them using a scale. When you see decimal places for individual values, yo...
Both types of variables are essential in statistics. At the animal shelter, after counting the cats, you’ll weigh them. The counts are discrete values while their weights are continuous. Chances are you’ll need to analyze both types of variables. It’s vital to recognize discrete vs continuous data because there are different ways to graph and analy...
Nov 4, 2018 · The specifics of the hypotheses depend on the type of test you perform because you might be assessing means, proportions, or rates. Example of a two-tailed 1-sample t-test. Suppose we perform a two-sided 1-sample t-test where we compare the mean strength (4.1) of parts from a supplier to a target value (5).
Jan 28, 2020 · T-tests are used when comparing the means of precisely two groups (e.g., the average heights of men and women). ANOVA and MANOVA tests are used when comparing the means of more than two groups (e.g., the average heights of children, teenagers, and adults). Predictor variable.
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Difference between groups by some quantitative characteristic can be reasoned as the association between variables "group" and "characteristic". Eta coefficient, also called correlation ratio, is the proper association measure between a nominal variable and a scale variable, and is therefore the other side of the coin for ANOVA or t-test.
