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IntroBiostatCourseHW1
(30 Oct 2006,
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---+++ Homework 1 (due on Monday, January 23) *Please note*: * Problems will be added until the last class before the due date. * No electronic submission unless explicitly allowed. * Use your own words when answering questions. Copying from other sources (including textbooks, handouts, my blog) is strongly discouraged, because it often indicates you don't understand your answer. 1 List 8 or more major problems associated with the [[%PUBURL%/Main/IntroBiostatCourse2006/Spreadsheetfromhell.xls][spreadsheet from hell]]. 1 Describe the difference between a continuous variable and a categorical variable, the advantages and/or disadvantages of categorizing a continuous variable. 1 Describe what sensitivity analysis is and what scenarios a sensitivity analysis can lead to. 1 Describe Simpson's paradox. A helpful reading is [[http://www.math.grinnell.edu/~mooret/reports/SimpsonExamples.pdf][here]]. 1 Nashville's December 2005 daily mean temperatures had mean 37.7 degrees (Fahrenheit) and standard deviation 7.0 degrees. The formula between Fahrenheit and Celcius is F = C * 9/5 + 32. Now, do you have enough information to get the mean and SD in Celcius? If yes, what are these? If no, what else do you need? 1 A binary outcome can only take two possible values. Examples include coin flipping, sex of newborn babies, having a type of cancer or not, etc. We always can denote one outcome as "1" and the other as "0". Let the probability of having "1" be _p_. Then 0 < _p_ < 1 and _q_ = 1 - _p_ is the probability of having "0". Suppose there are _n_ outcomes. The number _x_ of outcome "1" can vary from 0 to _n_, with varying probabilities. These possible outcomes together with their associated probabilities are called a binomial distribution. The parameter _p_ can be estimated by _x/n_. The coefficient of variation of this estimator is √[(1 - _p_)/(_np_)] x 100%. * Calculate the CV for _n_ = 10, 100, 1000 and _p_ = .01, .05, .1, .3, .5. * Comment on how CV changes as _n_ increases with _p_ fixed and as _p_ changes with _n_ fixed. * Suppose you want to estimate a cancer rate with accuracy measured as CV < 10%. What sample size do you need if the real rate is about 10%? What sample size do you need if the real rate is about 1%?
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Topic revision: r12 - 30 Oct 2006,
ChunLi
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