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CHAPTER 2: SOME TRULY USEFUL BASIC TESTS FOR
CHAPTER 2: SOME TRULY USEFUL BASIC TESTS FOR

Autocorrelation
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... Autocorrelation Autocorrelation (sometimes called serial correlation) occurs when one of the GaussMarkov assumptions fails and the error terms are correlated. i.e. cov(ut , ut 1 )  0 . This can be due to a variety of problems, but the main cause is when an important variable has been omitted from ...
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... • B) What would be a reasonable value for T? ...
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... 1. An interval calculated from the data, usually of the form: estimate  margin of error ...
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... distorted by limitations of the statistical procedures used to obtain it • E.g., the mean is influenced by outliers • The larger the sample, the greater the opportunity for an outlier to be neutralized in such a way as to not distort a sample mean • A small sample is especially vulnerable to outlier ...
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Math 116 – Chapter 11 – Take Home

... 4) We wish to estimate the mean price, , of all hotel rooms in Las Vegas. The Convention Bureau of Las Vegas did this in 1999 and used a sample of n = 112 rooms. In order to get a better estimate of  than the 1999 survey, we should a) Take a larger sample because the sample mean will be closer to ...
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...  The z-distribution is used when we know the population’s standard deviation—which, however, we virtually never know.  Almost always, then, we use the tdistribution, because we are estimating a statistic from sample data. ...
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Sampling Distributions - Associate Professor Leigh Blizzard

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... The problem required students to transform the given regression model into one in the actuarial tables and thereafter use the results given to derive the least square estimates of the parameters. But, full credit is also available for students who solve this problem correctly from first principles u ...
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... • Generally, most of the scores in a normal distribution cluster fairly close to the mean, • There are fewer and fewer scores as you move away from the mean in either direction. • In a normal distribution, 68.26% of the scores fall within one standard deviation of the mean, • 95.44% fall within two ...
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Resampling (statistics)

In statistics, resampling is any of a variety of methods for doing one of the following: Estimating the precision of sample statistics (medians, variances, percentiles) by using subsets of available data (jackknifing) or drawing randomly with replacement from a set of data points (bootstrapping) Exchanging labels on data points when performing significance tests (permutation tests, also called exact tests, randomization tests, or re-randomization tests) Validating models by using random subsets (bootstrapping, cross validation)Common resampling techniques include bootstrapping, jackknifing and permutation tests.
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