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BiostatIntro2008 Biostatistics for Genetics and Genomics Birmingham AL July 2008
BiostatIntro2008 Biostatistics for Genetics and Genomics Birmingham AL July 2008

... As an example, when a thumbtack is thrown in the air, it will land either “point up” or “point down”. Because of the physical nature of a thumbtack, the probability that it will land “point up” is unknown to us. Thus this probability is a parameter. We follow standard statistical notation and denote ...
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... Statistics for a data set o Find the mean, mean absolute deviation, variance, and standard deviation. o Prove and use this alternate formula for variance: x 2  (x ) 2 . o Prove and use that means and variances are additive. Repeated experiments o Given the statistics (mean, variance, and/or standar ...
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... find the theoretical probability distribution for the number of correct answers obtained by guessing on all five questions of a multiple-choice test where each question has four choices, and find the expected grade under various grading schemes. 4-1 6. Develop a probability distribution for a rando ...
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... the mean (average), median, standard deviation and standard error are often included on tables for analysis purposes. For example, it might be helpful to show the mean of a rating scale question and other numeric fields (i.e., age or income values). These measures summarize the key results in a few ...
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... Suppose only one background type b; overall fractions of signal and background events are ps and pb (prior probabilities). Suppose we select events with t < tcut. What is the ‘purity’ of our selected sample? Here purity means the probability to be signal given that the event was accepted. Using Baye ...
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... between –2.101 and 2.101 is consistent with equality of means It is possible for the means to be equal and t0 to exceed either 2.101 or –2.101, but it would be a “rare event” … leads to the conclusion that the means are different Could also use the P-value approach ...
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... Calculate arithmetical average for each casino. X the random variable, is defined as wins greater than $50,000 in the table shown above. Which casino should we choose? What happens if random variable X is defined as wins greater than $200,000? ...
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Just My Cup of t (test)

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Foundations of statistics

Foundations of statistics is the usual name for the epistemological debate in statistics over how one should conduct inductive inference from data. Among the issues considered in statistical inference are the question of Bayesian inference versus frequentist inference, the distinction between Fisher's ""significance testing"" and Neyman-Pearson ""hypothesis testing"", and whether the likelihood principle should be followed. Some of these issues have been debated for up to 200 years without resolution.Bandyopadhyay & Forster describe four statistical paradigms: ""(1) classical statistics or error statistics, (ii) Bayesian statistics, (iii) likelihood-based statistics, and (iv) the Akaikean-Information Criterion-based statistics"".Savage's text Foundations of Statistics has been cited over 10000 times on Google Scholar. It tells the following.It is unanimously agreed that statistics depends somehow on probability. But, as to what probability is and how it is connected with statistics, there has seldom been such complete disagreement and breakdown of communication since the Tower of Babel. Doubtless, much of the disagreement is merely terminological and would disappear under sufficiently sharp analysis.
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