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Will the variance of the difference of two independent normally distributed random variables be equal to the SUM of the variances of the two distributions?
Wiki User
∙ 14y ago
Yes it is. That is actually true for all random vars, assuming the covariance of the two random vars is zero (they are uncorrelated).
Wiki User
∙ 14y ago
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The usual sampling distributionof the difference between means is a what?
There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.
How do you explain F-statistic?
If X and Y have Gaussian (Normal) distributions, then the ratio ofthe mean of m variables distributed as X2 andthe mean of n variables distributed as Y2 hasan F distribution with m and n degrees of freedom.
Where do we use Gaussian distribution?
It is used when there are a large number of independent, identically distributed variables.
The difference between the independent and dependent variables?
Independent variables are variables that can be changed in an experiment, while dependent variables are variables that change as a result of an experiment. In other words, independent variables are what you change, and dependent variables are the results of the experiment.
What is the differecnce between independent variables and dependent variables?
Every time the independent variables change, the dependent variables change.Dependent variables cannot change if the independent variables didn't change.
The usual sampling distributionof the difference between means is a what?
There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.There is no such thing as "the usual sampling distribution". Different distributions of the original random variables will give different distributions for the difference between their means.
Will the sum of two normally distributed random variables be normally distributed if the random variables are independent?
Yes, and the new distribution has a mean equal to the sum of the means of the two distribution and a variance equal to the sum of the variances of the two distributions. The proof of this is found in Probability and Statistics by DeGroot, Third Edition, page 275.
How are difference from independent variables?
Constants stays the same independent variables is the variable that is being manipulated
How do you explain F-statistic?
If X and Y have Gaussian (Normal) distributions, then the ratio ofthe mean of m variables distributed as X2 andthe mean of n variables distributed as Y2 hasan F distribution with m and n degrees of freedom.
Where do we use Gaussian distribution?
It is used when there are a large number of independent, identically distributed variables.
What do you want your residuals to be in statistics?
For the purpose of analyses, they should be independent, identically distributed random variables. But the ideal is that they are all 0.
The difference between the independent and dependent variables?
Independent variables are variables that can be changed in an experiment, while dependent variables are variables that change as a result of an experiment. In other words, independent variables are what you change, and dependent variables are the results of the experiment.
What is the differecnce between independent variables and dependent variables?
Every time the independent variables change, the dependent variables change.Dependent variables cannot change if the independent variables didn't change.
What is F-ratio?
The F-ratio is a statistical ratio which arises as the ratio of two chi-square distributions.If X and Y are two random variables which are independent and approximately normally distributed, then their variances have chi-squared distributions. The ration of these chi-square distributions, appropriately scaled, is called the F-ratio.The F-ratio is used extensively in analysis of variance to determine what proportion of the variation in the dependent variable is explained by an explanatory variable (and the model being tested).
Independent and dependent are types of what?
Independent and dependent are types of variables. These variables are used mostly in science and math. When using independent variables you can control them dependent variables you cannot.
What is the difference between a manipulated and responding variable?
Manipulated variables are also known as independent variables. These are the variable which you change in an investigation. Plotted on the x axis.
What is the role of the stochastic error term in regression analysis?
Regression analysis is based on the assumption that the dependent variable is distributed according some function of the independent variables together with independent identically distributed random errors. If the error terms were not stochastic then some of the properties of the regression analysis are not valid.
