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AP statistics chapter 22 by Stats modelling the world third edition by David E. Bock

● Variances of independent - The variance of a sum or difference of independent random variables is the sum of the variances random variables add of those variables. ● Sampling distribution - The sampling distribution of is, under appropriate assumptions, modeled by a Normal the difference between two proportions model with mean and standard deviation .

● Two-proportion z-interval - A two-proportion z-interval gives a confidence interval for the true difference in proportions, , in two independent groups. The confidence interval is , where z* is a critical value from the standard Normal model corresponding to the specified confidence level. ● Pooling - When we have data from different sources that we believe are homogeneous, we can get a better estimate of the common proportion and its standard deviation. We can combine, or pool, the data into a single group for the purpose of estimating the common proportion. The resulting pooled standard error is based on more data and is thus more reliable (if the null hypothesis is true and the groups are truly homogeneous). Two-proportion z-test - Test the null hypothesis by referring the statistic to a standard Normal model.

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AP statistics chapter 22 by Stats modelling the world third edition by David E. Bock

● Variances of independent - The variance of a sum or difference of independent random variables is the sum of the variances random variables add of those variables. ● Sampling distribution - The sampling distribution of is, under appropriate assumptions, modeled by a Normal the difference between two proportions model with mean and standard deviation .

● Two-proportion z-interval - A two-proportion z-interval gives a confidence interval for the true difference in proportions, , in two independent groups. The confidence interval is , where z* is a critical value from the standard Normal model corresponding to the specified confidence level. ● Pooling - When we have data from different sources that we believe are homogeneous, we can get a better estimate of the common proportion and its standard deviation. We can combine, or pool, the data into a single group for the purpose of estimating the common proportion. The resulting pooled standard error is based on more data and is thus more reliable (if the null hypothesis is true and the groups are truly homogeneous). Two-proportion z-test - Test the null hypothesis by referring the statistic to a standard Normal model.