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hawthorne effect
It is the hypothesis that is presumed true until statistical evidence in the form of a hypothesis test proves it is not true.
Rejection of the null hypothesis occurs in statistical hypothesis testing when the evidence collected from a sample is strong enough to conclude that the null hypothesis is unlikely to be true. This typically involves comparing a test statistic to a critical value or assessing a p-value against a predetermined significance level (e.g., 0.05). If the evidence suggests that the observed effect is statistically significant, researchers reject the null hypothesis in favor of the alternative hypothesis. This decision implies that there is sufficient evidence to support a relationship or effect that the null hypothesis posits does not exist.
A base rate fallacy is a common error in logical reasoning where an effect is attributed to an incorrect cause due to incorrect statistical data based on statistical ratios not being taken into account.
Statistical evidence refers to data or information that has been gathered or analyzed using statistical methods. This evidence provides support for or against a particular hypothesis, theory, or claim through the use of statistical measures and tests to assess the likelihood of the observed results occurring by chance.
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Statistical evidence refers to data or information that has been analyzed and interpreted using statistical methods to support or challenge a hypothesis or claim. It helps quantify uncertainty and provides insights into the likelihood of an event occurring, making it a valuable tool in decision-making and research.
hawthorne effect
The Hawthorne effect
No statistical evidence to support a detrimental statement
There Is not currently statistical evidence available to support this
Yes, there is some statistical evidence that suggests a correlation between marijuana use and the likelihood of trying other drugs, but the concept of marijuana being a "gateway drug" is a complex and debated issue among researchers.
It is the hypothesis that is presumed true until statistical evidence in the form of a hypothesis test proves it is not true.
It is the hypothesis that is presumed true until statistical evidence in the form of a hypothesis test proves it is not true.
David C. Baldus has written: 'Statistical proof of discrimination' -- subject(s): Actions and defenses, Discrimination in employment, Evidence (Law), Law and legislation, Statistical methods
Coriolis effect.