STATS 250 Lecture Notes - Lecture 7: Statistical Parameter, Statistical Significance, Statistical Inference
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STATS 250 Full Course Notes
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End of chapter 4 and chapter 5: learning about a population proportion. Normal approximation to the binomial distribution: if x has the binomial distribution and the sample size is large enough, then we can approximate the value with the following formula. A linear combination is a type of combination of variables: sum = x + y. Mean (x + y) = mean (x) + mean (y) Variance (x + y) = variance(x) + variance (y: difference = x y. Mean (x y) = mean (x) mean (y) Variance (x y) = variance (x) + variance (y) (chapter 5) parameters, statistics and statistical inference. Remember to distinguish population and parameter from sample and statistic. We usually take a sample and use the statistic to estimate the parameter: this could change every time we take a new sample. If our sample is random, we will be able to say something about the accuracy of the estimation process.
