MAT-1010 Lecture Notes - Lecture 5: Central Limit Theorem, Standard Deviation, Normal Distribution

• School: App State
• Department: Mathematics
• Course: MAT-1010
• Professor: Jacob Winebarger

Document Summary

List the probabilities of rolling the sum of the numbers for 2 through 12 respectively. When you put this as a bar graph, you can see that it is normally distributed. Normal distribution- central limit theorem and the law of large numbers are the 2 fundamental theorems of probability (symmetric) It is equal to one because all probabilities added together equal 1. The mean is the the average for the date. Standard deviation is a way you can split up your data. Discrete data is analogous numbers (nothing in between 2 numbers, a whole number) Height times width added with the rest of the data will equal 1 (this is for when you look at the bar graph created earlier) Continuous data is not analogous, it is most applicable in the real world, most numbers in the real world (like height and weight) are not exact (like 6 feet and 200 pounds)