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The alpha level is the level decided before inferential statistic tests are run at which the null hypothesis may be rejected. The null hypothesis basically states that there is no difference or that a certain claim is true. For example, somebody may say the mean of a population is 50. If we test a sample and find a sample mean different from 50, we may question if the mean of the population really is people. Based on a normal distribution curve, we find how likely it is that we got the result we did assuming the mean really was 50. The alpha level would be determined before hand. If we set the alpha level at .05 and found our result would only occur in 3% of cases if the mean were really 50, we would reject the null hypothesis (In this example the null hypothesis states that the mean is 50). Depending on how important it is to have accurate data, the alpha level may be higher or lower. If in our example the alpha level was .01, the data would not be significant and we would fail to reject the null hypothesis because 3% is greater than 1%.
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What and who determines the alpha level in statistics?
Before conducting a significance test, the statistician will choose an alpha level. Depending upon the severity of having type I or type II error, the statistician will make the alpha level higher or lower. Generally in courts, the alpha level is .05. The other common alpha levels for significance tests are .10 and .01.
How do I set alpha in statistics?
You select the alpha level based on a number of factors. One consideration is the variability of the characteristic which you are trying to measure. Another, very important criterion is the importance of the decision to be made. If the consequences of the wrong decision are dire then you want a very high alpha, otherwise you may prefer a lower alpha.
What does an INFOCON risk level of Alpha mean?
INFOCON Alpha doesn't mean anything unless it's a locally created policy. If so, please ask your local helpdesk and/or network/system administrators. INFOCON Levels vary from lvl 1 to lvl 5. Level 5 being the least strict and level 1 being the most.
What is a 0.1 for a two-tailed test?
Alpha or significance level is usually 0.1 or 0.05 for a 2-tailed test.
What is alpha in regression analysis?
Alpha is not generally used in regression analysis. Alpha in statistics is the significance level. If you use a TI 83/84 calculator, an "a" will be used for constants, but do not confuse a for alpha. Some may, in derivation formulas for regression, use alpha as a variable so that is the only item I can think of where alpha could be used in regression analysis. Added: Though not generally relevant when using regression for prediction, the significance level is important when using regression for hypothesis testing. Also, alpha is frequently and incorrectly confused with the constant "a" in the regression equation Y = a + bX where a is the intercept of the regression line and the Y axis. By convention, Greek letters in statistics are sometimes used when referring to a population rather than a sample. But unless you are explicitly referring to a population prediction, and your field of study follows this convention, "alpha" is not the correct term here.
