Slide 1OverviewOnwardPROBABILITY AND STATISTICS IN COMPUTER SCIENCE AND SOFTWARE ENGINEERING Chapter 10: Statistical Inference – part 21OVERVIEWIn Chapter 9, we looked at how to apply statistical inference for parameter estimation …We saw how to estimate the population mean and population proportions, and how we could create confidence intervals using the standard normal (z-variable) and t-distributions (t-variable)We explored how to do hypothesis tests, and compute p-values using these distributions for population means and proportionsWe then explored parameter estimation for variance (or standard deviation), and saw similar tools could be constructed using and F- distributions•:2ONWARDWe will now expand our use of statistical inference to draw conclusions about nonparametric qualities of the population distributionFor example, can we test whether a population is in fact normally distributed? Or does it follow some other distribution?We will also see how to test independence of two factors, which is helpful in determining causality In this lecture, we will develop a statistic that will help us test hypothesis about these types of
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