Sampling and Hypothesis Testing
... We go ahead and draw the sample, and calculate a sample mean of (say) 97. If there’s a probability of .95 that our x̄ came from within 4 units of µ, we can turn that around: we’re entitled to be 95 percent confident that µ lies between 93 and 101. We draw up a 95 percent confidence interval for the ...
... We go ahead and draw the sample, and calculate a sample mean of (say) 97. If there’s a probability of .95 that our x̄ came from within 4 units of µ, we can turn that around: we’re entitled to be 95 percent confident that µ lies between 93 and 101. We draw up a 95 percent confidence interval for the ...
Chapter 6 Slides
... different samples of sufficient size and construct the confidence intervals, 95% of them would actually contain the value of the population mean . Wrong: There is a 95% chance that the true value of will fall between 98.08 and 98.32. (there is no way to calculate the probability for a population ...
... different samples of sufficient size and construct the confidence intervals, 95% of them would actually contain the value of the population mean . Wrong: There is a 95% chance that the true value of will fall between 98.08 and 98.32. (there is no way to calculate the probability for a population ...
Quantile Estimation
... used in Figure 1. The SAS and Excel estimates do have some things in common. Neither one provides an estimate that is below the observed minimum or is above the observed maximum. This is problematic in that if, for example, one additional sample point beyond seven were to be collected there is a 25 ...
... used in Figure 1. The SAS and Excel estimates do have some things in common. Neither one provides an estimate that is below the observed minimum or is above the observed maximum. This is problematic in that if, for example, one additional sample point beyond seven were to be collected there is a 25 ...
5.3 - Pages
... Imagine performing the following experiment in principle. We are conducting a socioeconomic survey of an arbitrarily large population of households, each of which owns a certain number of cars X = 0, 1, 2, or 3, as illustrated below. For simplicity, let us assume that the proportions of these four t ...
... Imagine performing the following experiment in principle. We are conducting a socioeconomic survey of an arbitrarily large population of households, each of which owns a certain number of cars X = 0, 1, 2, or 3, as illustrated below. For simplicity, let us assume that the proportions of these four t ...
2. 4. 4 Sample size estimation for a comparison of two means
... Power of the test: 1- is the power of the test, and represents the probability of correctly rejecting a false null hypothesis. It is a measure of the ability of the test to detect an alternative mean or a significant difference when it is real Note that for a given Y and s, if 2 of the 3 quantitie ...
... Power of the test: 1- is the power of the test, and represents the probability of correctly rejecting a false null hypothesis. It is a measure of the ability of the test to detect an alternative mean or a significant difference when it is real Note that for a given Y and s, if 2 of the 3 quantitie ...
Using Stata for Confidence Intervals
... Solution. I don’t know of any Stata routine that will do this by directly analyzing raw data. Further, unlike the other 2 cases, I don’t know of a standalone command for confidence intervals only. However, the ztesti command (which is installed with Stataquest) will do this when you have the summary ...
... Solution. I don’t know of any Stata routine that will do this by directly analyzing raw data. Further, unlike the other 2 cases, I don’t know of a standalone command for confidence intervals only. However, the ztesti command (which is installed with Stataquest) will do this when you have the summary ...
2012 FR - edventure-GA
... He will consider buying only those machines for which there is no other machine that has both higher quality and lower price. On the scatterplot reproduced below, circle all data points corresponding to machines that Chris will consider buying. ...
... He will consider buying only those machines for which there is no other machine that has both higher quality and lower price. On the scatterplot reproduced below, circle all data points corresponding to machines that Chris will consider buying. ...
German tank problem
In the statistical theory of estimation, the problem of estimating the maximum of a discrete uniform distribution from sampling without replacement is known in English as the German tank problem, due to its application in World War II to the estimation of the number of German tanks.The analyses illustrate the difference between frequentist inference and Bayesian inference.Estimating the population maximum based on a single sample yields divergent results, while the estimation based on multiple samples is an instructive practical estimation question whose answer is simple but not obvious.