We saw in chapter 6 that we can use \(z\)-scores to split up a normal distribution and calculate the proportion of the area under the curve in one of the new regions, giving us the probability of rand...We saw in chapter 6 that we can use \(z\)-scores to split up a normal distribution and calculate the proportion of the area under the curve in one of the new regions, giving us the probability of randomly selecting a \(z\)-score in that range. As the sample size n increased, the standard error decreased, which in turn caused the value of \(z\) to increase, which finally caused the \(p\)-value (a term for probability we will use a lot in Unit 2) to decrease.
