Unit 6. Normal Distribution Solution to problems Statistics I. International Group Departamento de Economa Aplicada Universitat de Valncia May 20‚ 2010 Problem 35 Random variable X : weekly ticket sales (units) of a museum. X ∼ N(1000‚ 180) Find the probability of weekly sales exceeding 850 tickets. Find the probability of the interval 1000 to 1200 Take 5 weeks at random. Find the probability of weekly sales not exceeding 850 tickets in more than two weeks Ticket price is 4.5 Euros
Premium Random variable Probability theory Cumulative distribution function
example 2 2 10 6 a) Describe the characteristics of Normal probability distribution. b) In a sample of 120 workers in a factory‚ the mean and standard deviation of wages were Rs. 11.35 and Rs.3.03 respectively. Find the percentage of workers getting wages between Rs.9 and Rs.17 in the whole factory assuming that the wages are normally distributed. Characteristics of Normal probability distribution Formula/Computation/Solution to the problem 3 4 10 6 a) The procedure
Premium Normal distribution Stratified sampling Sampling
Statistics Math 1342 Final Exam Review Name___________________________________ MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Provide an appropriate response. 1) A card is drawn from a standard deck of 52 playing cards. Find the probability that the card is an ace or a heart. 17 7 3 4 A) B) C) D) 52 52 13 13 Answer: D 2) The events A and B are mutually exclusive. If P(A) = 0.7 and P(B) = 0.2‚ what is P(A or B)? A) 0.5 B) 0.9 C) 0.14 D)
Premium Normal distribution Standard deviation
Study Set for Midterm II‚ Chapters 7 & 8 ESSAY. Write your answer in the space provided or on a separate sheet of paper. 1) The average score of all pro golfers for a particular course has a mean of 70 and a standard deviation of 3.0. Suppose 36 golfers played the course today. Find the probability that the average score of the 36 golfers exceeded 71. 2) At a computer manufacturing company‚ the actual size of computer chips is normally distributed with a mean of 1 centimeter
Premium Normal distribution Standard deviation Arithmetic mean
Rating for Load Compensation With Nonstiff Source Srinivas Bhaskar Karanki‚ Nagesh Geddada‚ Student Member‚ IEEE‚ Mahesh K. Mishra‚ Senior Member‚ IEEE‚ and B. Kalyan Kumar‚ Member‚ IEEE Abstract—The distribution static compensator (DSTATCOM) is used for load compensation in power distribution network. In this paper‚ a new topology for DSTATCOM applications with nonstiff source is proposed. The proposed topology enables DSTATCOM to have a reduced dc-link voltage without compromising the compensation
Premium Capacitor Control theory Electricity distribution
How Distribution Is Arranged To Provide Customer Convenience? There are several ways in which businesses arrange distribution to provide customer convenience. The methods used may vary slightly based on what sort of business is being operated. For example‚ those who are running an e-commerce business will have different techniques than those who have a standard "real world" business headquarters. Also‚ different real world businesses may have different techniques dependent upon the size of the
Premium Supply chain management Marketing Transport
Discrete and Continuous Probability All probability distributions can be categorized as discrete probability distributions or as continuous probability distributions (stattrek.com). A random variable is represented by “x” and it is the result of the discrete or continuous probability. A discrete probability is a random variable that can either be a finite or infinite of countable numbers. For example‚ the number of people who are online at the same time taking a statistics class at CTU on
Premium Random variable Probability theory
The Pareto Principle (also known as the 80/20 Rule or the Law of the Vital Few) More than a century ago‚ an Italian economist by the name of Vilfredo Pareto observed that 80% of the land in Italy was owned by 20% of the population. Subsequently‚ others observed a similar phenomenon in other situations‚ e.g. 80% of sales come from 20% of customers‚ 80% of the rise (or fall) in the value a stock portfolio comes from 20% of the stocks‚ 80% of complaints come from 20% of problems‚ 80% of results are
Premium Vilfredo Pareto Pareto principle Pareto distribution
A useful distribution for fitting discrete data: revival of the Conway–Maxwell–Poisson distribution Galit Shmueli‚ University of Maryland‚ College Park‚ USA Thomas P. Minka and Joseph B. Kadane‚ Carnegie Mellon University‚ Pittsburgh‚ USA Sharad Borle Rice University‚ Houston‚ USA and Peter Boatwright Carnegie Mellon University‚ Pittsburgh‚ USA [Received June 2003. Revised December 2003] Summary. A useful discrete distribution (the Conway–Maxwell–Poisson distribution) is revived
Premium Binomial distribution Poisson distribution Normal distribution
term "Pareto principle" can also refer to Pareto efficiency. The Pareto principle (also known as the 80–20 rule‚ the law of the vital few‚ and the principle of factor sparsity) states that‚ for many events‚ roughly 80% of the effects come from 20% of the causes.[1][2] Business-management consultant Joseph M. Juran suggested the principle and named it after Italian economist Vilfredo Pareto‚ who observed in 1906 that 80% of the land in Italy was owned by 20% of the population; he developed the principle
Premium Vilfredo Pareto Pareto principle Pareto distribution