01:960:285 Lecture Notes - Lecture 15: Probability Density Function, Sampling Distribution, Exponential Distribution

• School: Rutgers University
• Department: Statistics and Biostatistic
• Course: 01:960:285
• Professor: Zhanyun Zhao

Document Summary

(cid:1856), essentially one divided by the range at any given point in the range: mean: =(cid:4666)(cid:1855)+(cid:1856)(cid:4667)/(cid:884, variance: 2 = (cid:4666)(cid:1856) (cid:1855)(cid:4667)2/(cid:883)(cid:884) The thickness is a uniform variable between 150mm and 200mm: example, what is the mean and standard deviation, apply formulae learned earlier, mean = 175 mm, variance = ((200-150)^2)/12 = 2500 / 12, standard deviation = appr. 0. 2: exponential distribution, if the poisson distribution provides an appropriate description of the number of occurrences within a given time period, the exponential distribution describes the amount of time between each occurence, also called the waiting time distribution. Exponential and poisson are commonly used together: mean, variance: 2, probability density function: (cid:4666)(cid:4667) = / (x>0) To find the area a to the right of a particular probability a in the function(that is, finding the likelihood of getting a value greater than a) a. 2+4 = 6: range is -2 - 6.