MGMT 1050 Chapter Notes - Chapter 8, 10 - 15: Null Hypothesis, Type I And Type Ii Errors, Confidence Interval
10 Dec 2016
School
Department
Course
Professor
Document Summary
8. 1 probability density functions f(x) that approximates the curve (area of the histogram) Requirements for a probability density function: 0, 1. 0. Uniform probability distribution: also called rectangular probability distribution. 8. 1b using a continuous distribution to approximate a discrete distribution. Frequently use continuous distribution to approximate a discrete one when it"s countable but too large: using normal distribution. Most important of all probability distributions because of its crucial role in statistical inference. The probability of a normal random variable: Standard normal random variable: standardized value of a normal variable; denoted by z. L = . Values of za are the 100(1-a)th percentiles of a standard normal random variable. Student t distribution (student"s t distribution): derived by william s. gosset under the pseudonym student uses the letter t to represent the random variable. Wx> v (greek letter nu) = the parameter of the student t distribution called the degree of freedom. Variance: v(t) = v/(v-2), v > 2.
