Frequency distribution table shows how many times "n_i" would you expect appearing of some value "x_i" of discrete random variable "X" through the "N" experiments. If you divide frequency of "x_i" by total number of measurements "N", you will obtain normed frequency distribution that is an approximation to probability density function (PDF). When "N \\rightarrow \\infty" normed frequency distribution becomes PDF. Frequency distribution table has two arrays: "x_i ; n_i" .
To find expectation (or mean) you need to calculate "\\bar{x}=\\frac{\\sum x_i n_i}{N} = \\mu" .
Standard deviation: "\\sigma =\\sqrt{\\frac{\\sum n_i(x_i-\\bar{x})^2}{N}}".
Coefficient of variation: "c_V = \\frac{\\sigma}{\\mu}".
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A rare disease exists in which only 1 in 500 are affected. A test for the disease exists but of course it is not infallible. A correct positive result (positive test for a patient actually having the disease) occurs 95% of the time while a false positive result (positive test for a patient not having the disease) occurs 1% of the time. d- If a randomly selected individual is tested and the result is positive, what is the probability that the individual does not have the disease?
A rare disease exists in which only 1 in 500 are affected. A test for the disease exists but of course it is not infallible. A correct positive result (positive test for a patient actually having the disease) occurs 95% of the time while a false positive result (positive test for a patient not having the disease) occurs 1% of the time. a- Find the prevalence of the disease. b- Find the sensitivity and specificity of the test.
A rare disease exists in which only 1 in 500 are affected. A test for the disease exists but of course it is not infallible. A correct positive result (positive test for a patient actually having the disease) occurs 95% of the time while a false positive result (positive test for a patient not having the disease) occurs 1% of the time. c- Find the predictive value positive and the predictive value negative of the test.
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