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An alpha error is another name in statistics for a type I error, rejecting the null hypothesis when the null hypothesis is true.
Alpha is the probability that the test statistics would assume a value as or more extreme than the observed value of the test, BY PURE CHANCE, WHEN THE NULL HYPOTHESIS IS TRUE.
Significance Level (Alpha Level): If the level is set a .05, it means the statistician is acknowledging that there is a 5% chance the results of the findings will lead them to an incorrect conclusion.
Im in statistics class and I been trying to figure out the answer too. I couldn't find it online. Luckily I had the answer to the problem I was trying answer, so to figure out what it was I worked it backwards. BASICALLY I THINK ITS ANOTHER WAY OF SAYING (confidence interval) which for most problems is either 90% 95% 99% or in decimal form is .9 .95 .99
There are two types of statistics. One is called descriptive statistics and the other is inferential statistics. Descriptive statistics is when you use numbers. Inferential statistics is when you draw conclusions or make predictions.