"Next" to continue working on this unit -6 da A researcher wants to show that the proportion of mosquitoes that carry a certain disease is greater in Region 1 than Region 2. In a sample of 1,323 mosquitoes apped in Region 1, 1,045 test positive for the disease. In a sample of 1,5. mosquitoes trapped in Region 2, 1,189 test positive for the disease. Test the alternative hypothesis that the population proportion for Region 1 is greater than the population proportion for Region 2. The test statistic is z = 1.62. What is th correspondingp-value? Compute your answer using a value from the table below. z0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 1.00.841 0.844 0.846 0.848 0.851 0.8530.8550.858 0.8600.862 1.1 0.864 0.8670.869 0.8710.8730.875 0.877 0.879 0.881 0.883 1.2 0.885 0.887 0.889 0.891 0.893 0.894 0.896 0.898 0.9000.901 1.3 0.903 0.905 0.907 0.9080.9100.911 0.913 0.9150.916 0.918 1.4 0.919 0.921 0.922 0.9240.925 0.926|0.928 0.929 0.9310.932 1.5 0.933 0.934 0.936 0.9370.938 0.939 0.941 0.942 0.943 0.944 1.6 0.945 0.946 0.947 0.948 0.949 0.951 0.952 0.953 0.9540.954
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!

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