Discrete probability distribution

Binomial Distribution This is a discrete random variable, where the process of obtaining the Binomial distribution is called “Bernoulli “ process. An experiment that often consists of repeated trials, each with two possible outcomes, which could be labeled as “success” or “failure”. This experiment is known as binomial experiment. A binomial experiment is one that possesses the following properties: 1. The experiment consists of n repeated trials. 2. Each trial has only 2 possible

Statistics – Lab Week 4 Name: MATH221 Statistical Concepts: * Probability * Binomial Probability Distribution Calculating Binomial Probabilities * Open a new MINITAB worksheet. * We are interested in a binomial experiment with 10 trials. First, we will make the probability of a success ¼. Use MINITAB to calculate the probabilities for this distribution. In column C1 enter the word ‘success’ as the variable name (in the shaded cell above row 1. Now in that same column

Solutions Due before the start of class, Wednesday January 16. 1. In Cook County, each day is either sunny or cloudy. If a day is sunny, the following day will be sunny with probability 0.60. If a day is cloudy, the following day will be cloudy with probability 0.70. Suppose it is cloudy on Monday. a) What is the probability that it will be sunny on Wednesday? There are two mutually exclusive ways that it could end up being sunny on Wednesday. P(Sunny Wednesday) = P(Sunny Tuesday AND Sunny Wednesday)

  19 Computing Expected Backorders  It is sometimes easier to first compute (for a given R), E[I ]   R x0 ( R  x ) Pr( X  x ) and then obtain E[B]=E[I] + E[X] – R.  For the case where leadtime demand has the Poisson distribution (with mean  = E(D)L), the following relationship (for a fixed R) applies E[B]= Pr(X=R)+(-R)[1-Pr(X R)]

Linear Programming D.V. – Decision Variables O.F. – Objective Funtion S.T. or CONST - Constraints Constrained Mathematical Model – a model with an objective and one or more constraints EXAMPLE: 50D + 30C + 6M is the total profit for a production run($50 profit for Desk, $30 profit for Chair and $6 per pound for steel) Functional Constraints - ≤ ≥ or = --Restrictions that involve expressions with 1 or more variables EXAMPLE: 7d+3c+1.5M <= 2000 (constraint on raw steel) Variable Constraints

Statistics – Lab #6 Name:__________ Statistical Concepts: * Data Simulation * Discrete Probability Distribution * Confidence Intervals Calculations for a set of variables Answer: Calculating Descriptive Statistics Answer: Variable N N* Mean SE Mean StDev Minimum Q1 Median Q3 Maximum Mean 20 0 3.560 0.106 0.476 2.600 3.225 3.550 3.775 4.500 Median 20 0 3.600 0.169 0.754 2.000 3.000 3.500 4.000 5.000 Calculating

- What features of the graph would you need for the expected proportionality to be verified? In other words, what should the graph look like to verify the inverse square law? (2 marks) The inverse square law states, that the intensity of the luminosity is inversely proportional to the square of the distance from the source. The graph would require features such as; evidence that the increase in distance away from the source results in the reduction of light exposure as well as, the contrast between

one year, as follows: 1. In Excel, use a suitable method for generating the number of days needed to repair the copier, when it is out of service, according to the discrete distribution shown. 2. In Excel, use a suitable method for simulating the interval between successive breakdowns, according to the continuous distribution shown.  3. In Excel, use a suitable method for simulating the lost revenue for each day the copier is out of service. 4. Put all of this together to simulate

value of sample information tutor: Expected value is the main thought in probability, in an intellect more general than probability itself. The expected value of a real-valued selection variable offers a compute of the center of the distribution of the variable. More considerably, by taking the expected value of various functions of a common random variable, we can calculate a lot of interesting features of its distribution, including spread and correlation. Tutor is a personality working in the

0/ 1.0 Points If events A and B are mutually exclusive, then the probability of both events occurring simultaneously is equal to A.0.0 (CORRECT) B.1.0 C.0.5 D.any value between 0.5 and 1.0 Question 3 of 25 1.0/ 1.0 Points The table below shows the preferences for elective courses of students who are undecided about their majors.    Philosophy Digital Art Film Studies Male 9 16 22 Female 6 18 14 What is the probability of randomly selecting a student who is female or prefers Digital