Sse = ssr / ( n - k)
It depends entirely on the variance (or standard error).
no
Each treatment is applied more than once per block. This makes it possible to enhance the error variance estimate by extracting some sampling variance from it. See the link for a visual example.
Favourable variance is that variance which is good for business while unfavourable variance is bad for business
The error in which a particular numbers are set apart is called error variance.
The unaccounted for variance aka Error Variance, is the amount of variance of the dependent variable (DV) that is not accounted for by the main effects/independent variables (IV) and their interactions.
Sse = ssr / ( n - k)
true
It depends entirely on the variance (or standard error).
The error, which can be measured in a number of different ways. Error, percentage error, mean absolute deviation, standardised error, standard deviation, variance are some measures that can be used.
no
3.92
A sequence of variables in which each variable has a different variance. Heteroscedastics may be used to measure the margin of the error between predicted and actual data.
Each treatment is applied more than once per block. This makes it possible to enhance the error variance estimate by extracting some sampling variance from it. See the link for a visual example.
A small sample size and a large sample variance.
The sample variance is obtained by dividing SS by the degrees of freedom (n-1). In this case, the sample variance is SS/(n-1) = 300/(4-1) = 300/3 = 100 In order to get the standard error, you can do one of two things: a) divide the variance by n and get the square root of the result: square.root (100/4) = square.root(25) = 5, or b) get the standard deviation and divide it by the square root of n. 10/square.root(4) = 10/2 = 5