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Chi-squared distribution: It is the probability distribution, f (x), of the random variable de?ned as the sum of squares of the number (v) of independent standard normal variables and given as follows
The shape parameter, v, is generally known as the degrees of freedom of the distribution. This distribution occurs in number of areas of the statistics, for instance, assessing the goodness-of-?t of models, specifically those ?tted to contingency tables. The mean of distribution is v and its variance is 2v.
A standard IQ test has a mean of 98 and a standard deviation of 16. We want to be 99% certain that we are within 8 IQ points of the true mean. Determine the sample size
The number of employees absent from work at a large electronics manufacturing plant over aperiod of 106 days is given in the table below. 146 141 139 140 145 141 142 131 142 140
Described by the leading proponent as 'the conscientious, explicit, and judicious uses of present best evidence in making the decisions about the care of individual patients, and
Difference b/w historigram and histogram
O. J. Simpson paradox is a term coming from the claim made by the defence lawyer in murder trial of O. J. Simpson. The lawyer acknowledged that the statistics demonstrate that onl
Thomas Economic Forecasting, Inc. and Harmon Econometrics have the same mean error in forecasting the stock market over the last ten years. However, the standard deviation for Thom
Unequal probability sampling is the sampling design in which the different sampling units in the population have different probabilities of being included in sample. The differing
1. define statistical algorithms 2. write the flow charts for statistical algorithms for sums, squares and products. 3. write flow charts for statistical algorithms to generates ra
An oil company is considering whether or not to bid for an offshore drilling contract. If they bid, the value would be $600m with a 65% chance of gaining the contract. The company
The measure of the degree to which the particular model differs from the saturated model for the data set. Explicitly in terms of the likelihoods of the two models can be defined a
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