STAT 111 Lecture Notes - Lecture 16: Junk Food, Confidence Interval, Normal Distribution

• School: University of Vermont
• Department: Statistics
• Course: STAT 111
• Professor: Jacob William Martin

Document Summary

The symmetric bell-shaped curve we have seen for almost all of our distribution of statistics is called a normal distribution. For random samples with a sufficiently large sample size, the distribution of many common sample statistics can be approximated with a normal distribution. The larger the sample sizes, the more normal the distribution of the statistic will be. The normal distribution is fully described by its mean and standard deviation: n(mean, standard deviation) If a randomization distribution is normally distributed: n(statistic, se) We can compare the original statistic to this normal distribution to find the p-value! Often, we standardize the statistic to have mean 0 and standard deviation 1. Z = x mean x = statistic mean = null value sd = se. The standardized test statistic (also known as a z-statistic) is: Calculating the number of standard errors a statistic is from the null lets us assess extremity on a common scale.