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What is the variance of intercept in a simple regression model when all observations on x axis are identical?
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What do both variance and the standard deviaton tell you about distribution?
How widely spread out, or tightly concentrated about the mean the observations are.
What are the advantages of weighted average?
More importance can be attached to observations which are either of greater importance, accuracy (lesser variance).
What does n-1 indicate in a calculation for variance?
The n-1 indicates that the calculation is being expanded from a sample of a population to the entire population. Bessel's correction(the use of n − 1 instead of n in the formula) is where n is the number of observations in a sample: it corrects the bias in the estimation of the population variance, and some (but not all) of the bias in the estimation of the population standard deviation. That is, when estimating the population variance and standard deviation from a sample when the population mean is unknown, the sample variance is a biased estimator of the population variance, and systematically underestimates it.
What difference between a favorable variance and an unfavorable variance?
Favourable variance is that variance which is good for business while unfavourable variance is bad for business
Why is it important to look at a scatter plot prior to starting a simple linear regression?
To see if there is a linear relationship between the dependent and independent variables. The relationship may not be linear but of a higher degree polynomial, exponential, logarithmic etc. In that case the variable(s) may need to be transformed before carrying out a regression. It is also important to check that the data are homoscedastic, that is to say, the error (variance) remains the same across the values that the independent variable takes. If not, a transformation may be appropriate before starting a simple linear regression.
What is the meaning of analysis of covariance?
A mix of linear regression and analysis of variance. analysis of covariance is responsible for intergroup variance when analysis of variance is performed.
What is heteroscadacity?
In regression analysis , heteroscedasticity means a situation in which the variance of the dependent variable varies across the data. Heteroscedasticity complicates analysis because many methods in regression analysis are based on an assumption of equal variance.
What is varience?
In statistics, variance measures how far apart a set of numbers is spread out. If the numbers are identical, the variance is zero. Variance can never be negative.
What is the smallest value a variance can be?
0. When all the observations have the same value.
Basic assumption in analysis of variance?
1- observations are from normally distributed populations. 2- observations are from populations with equal variances.
What is the F stat in regression analysis?
The F stat tests the equality of variances. It uses statistical tables for reference and is calculated with F = Variance 1 (max)/variance 2(min).
What has the author Stanton A Glantz written?
Stanton A. Glantz has written: 'Clinician's Pocket Drug Reference 2002' 'Book and Windows Software' 'Primer Biostatistics' 'Primer of Applied Regression & Analysis of Variance' -- subject(s): Analysis of variance, Biometry, Regression analysis 'Primer of Biostatistics, IBM' 'Tobacco War'
The standard deviation of a sample of 10000 observations equals 121 The variance of the sample equals?
It equals 14641.
What do both variance and the standard deviaton tell you about distribution?
How widely spread out, or tightly concentrated about the mean the observations are.
What are the advantages of weighted average?
More importance can be attached to observations which are either of greater importance, accuracy (lesser variance).
What has the author David J Saville written?
David J. Saville has written: 'Statistical methods' -- subject(s): Regression analysis, Geometry, Analysis of variance
What are 5 number data that have mean of 20 value of variance 0?
Variance = 0 means they are all the same. So the question is simplified to: what 5 identical values have a mean of 20. Since they are identical, their mean value is the same as themselves. So the answer, trivially, is [20, 20, 20, 20, 20].
