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What is a Sigma in math?

Updated: 4/28/2022
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14y ago

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summation it means the sum of all entities specified. like if is say 1i=10, i2=20, i3=30 then sigma i = 60 i.e.(10+20+30)

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Q: What is a Sigma in math?
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In a normal distribution with mu equals 25 and sigma equals 3m what number corresponds to z equals -3?

z = (x-mu)/sigma So x = sigma*z + mu = 3m*(-3) + 25 = -9m + 25


How do you compute one sigma deviation?

Let x denote the values of the variable in question. Suppose there are n observations. Let Sx = the sum of all the values. then the mean of x, Mx = Sx/n Let Sxx = the sum of all the squares of the values. The Vx (= the variance of x) is Sxx - (Mx)^2 and sigma(x) = sqrt(Vx). Therefore one sigma deviation, relative to the mean, = Mx - sigma(x), Mx + sigma(x).


What is the symbol for population standard deviation?

Sigma


What is plus or minus two sigma?

In statistics, sigma is a measure of the standard error of a variable. That is a measure of the spread of the variable around its mean value. Many variables are distributed approximately according to the Gaussian (Normal) distribution. Even when they are not, the means of repeated samples are (Central Limit Theorem). For the Gaussian distribution, 95% of the observations lie within 1.96*sigma from the mean. This is sometimes rounded to two sigma. While for an exact Gaussian distribution 2 sigma would imply 95.45%, for approximate Gaussian, it is still "around" 95%. Thus, for example, average IQ (whatever it measures, which certainly is not intelligence!) is 100 and sigma = 15. So 95% of the population will have IQs between 100-2*sigma and 100+2*sigma, which is 70 and 130. By the way, if you think my comment about what IQs measure is sour grapes, I assure you that is nowhere near the truth!


What is the formula for standard error of a contrast?

Denote: ai = contrast and ni = sample size for each level Estimate of contrast: sum( ai ybari ) note: sum is written as Sigma Standard Error of contrast: sqrt( sum( sigma2 ai2 / ni ) ) note: sum is written as Sigma, and lowercase sigma is usually estimated with MSE Sums of Squares of contrast: ( sum( ai ybari ) )2 / ( sum( ai2 / ni ) ) note: sum is written as Sigma Usually when one uses estimate divided by SE, the test statistic follows a t-distribution (unless he/she didn't estimate lowercase sigma). When one uses SS(contrast) divided by MSE, the test statistic follows a F-distribution. The formulas are similar because there's a strong relationship between the t-distribution and the F-distribution. Hopes this helps and sorry I don't know how to write math equations here.