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STAT-3090 Lecture Notes - Lecture 6: Binomial Distribution, Random Variable, Free Throw

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fuchsiamuskrat95
13 Feb 2018
School
Clemson University
Department
Statistics
Course
STAT-3090
Professor
kayla javiar

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Document Summary

Chapter 6 - discrete probability distributions: information about the future. In this section we explore a specific type of random variable called a binomial random variable. Characteristics of a binomial experiment: there are only two possible outcomes in each trial. We will denote one outcome by s (for success) and the other by f (for failure): the experiment consists of a fixed number n of identical trials, the probability of s remains the same from trial to trial. This probability is denoted by p, and the probability of f is thus 1 p: the n trials are independent. You plan to interview 50 people, and for the sake of convenience you decide to interview both the husband and the wife in 25 married couples. The random variable x is the number among the 50 persons interviewed who think mothers should not be employed. Kyrie irving"s free throw percentage was 93. 9% in the 2016 nba finals in which the cleveland.

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Related textbook solutions

Introductory Statistics
OER Edition, 2013
Openstax
ISBN: 9781938168208

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Related Questions

What are the four conditions necessary for x to have a binomial distribution? Mark all that apply.

A) The probability of success, p, is constant from trial to trial.

B) There can only be two outcomes, success and failure.

C) The trials must be independent.

D) You must have at least 10 successes and 10 failures.

E) X can take on any value in an interval.

F) X counts the number of trials until you get a success.

G) There are n set trials.

Consider 3 trials, each having the same probability of success. Let X denote the total number of successes in these trials. If E[X]=1.8, what is (a) the largest possible value of P{X=3}? (b) the smallest possible value of P{X=3}? In both cases, construct a probability scenario that results in P{X=3} having the stated value. Hint: For part (b), you might start by letting U be a uniform random variable on (0, 1) and then defining the trials in terms of the value of U.