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What is one factor which will increase the required sample size of a study?
In general, three or four factors must be known or estimated to calculate sample size: (1) the effect size (usually the difference between 2 groups); (2) the population standard deviation (for continuous data); (3) the desired power of the experiment to detect the postulated effect; and (4) the significance level.
What effect does increasing the sample size have on the probability?
Since the increase in sample size leads to a decrease in the variability of the sample mean the probability will increase as we will be able to comment about the characteristics of the sample in a much more accurate manner.
Can a new predictor variable change the sample size?
Usually no change. That is, the inclusion of a new predictor variable will only change the sample size of the model if the new predictor variable has missing values. Any cases with missing values on any predictor variable are dropped automatically Yes. For the R-square, any new nonzero terms must improve the fit.
How is the sample size of an experiment influenced?
Unfortunately, there is no correct answer without additional information (or assumptions). The sample size required for an experiment designed to investigate the behavior of an unknown population mean will be influenced by the following: value selected for \\(\\alpha\\), the risk of rejecting a true hypothesis,
What happens when you change unit of measurement in simple regression model?
Consider the simple regression model y = β 0 + β 1 x + u where u ∼ N ( 0, 1) is iid. β 1 will change if you change the units of x only.
How are sample sizes calculated when standard deviation is not known?
The procedures for computing sample sizes when the standard deviation is not known are similar to, but more complex, than when the standard deviation is known.