of binomial experiments. Testing a pain reliever using 20 people to determine if it is effective. The random variable represents the number of people who find the pain reliever to be effective. 3. Use the binomial probability distribution to answer the following probability questions. According to government data, the probability that an adult under 35 was never married is 25%. In a random survey of 10 adults under 35, what is the probability that: Exactly 5 were never married? 4. Use the binomial
Words: 1336 - Pages: 6
Risk and Return “Believe me! The secret of reaping the greatest fruitfulness and the greatest enjoyment from life is to live dangerously!” —Friedrich Wilhelm Nietzsche Are You the “Go-for-It” Type? The financial crisis has people buzzing about “systematic risk.” This term means different things in different contexts. Traditionally, systematic risk has referred to the non-diversifiable risk that comes from the impact the overall market has on individual investments. This risk is also known
Words: 13535 - Pages: 55
distributions b. Measures of Central Tendency/Location (Mean/Mode/Median) c. Dispersion, Measures of Dispersion (Variance/SD/Quartiles/Percentiles/Ranges) and its relevance to Risk Management d. Correlations 2. Introduction to Probability Theory a. Random variables b. Probability and its uses c. Probability Rules d. Conditional Probabilities e. Probability Distributions (Single Variable) i. Continuous Time/Discreet Time; Continuous Value/ Discreet
Words: 1406 - Pages: 6
Statistics Chapter 5 - Review - A random variable is a variable (typically represented by x) that has a single numerical value, determined by chance, for each outcome of a procedure. A probability distribution is a description that gives the probability for each value of the random variable. It is often expressed in the format of a graph, table, or formula. A discrete random variable has either a finite number of values or a countable number of values, where “countable” refers to the fact
Words: 389 - Pages: 2
page 3 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. Lost revenue of Jet Copies due to breakdown can be done by generating random numbers from different probability distributions according the given probability law. The different steps of this simulation and assumption made are explained below. 1. Simulation for the repair time. It is given that the repair time follows: |Repair
Words: 655 - Pages: 3
Statistics for Psychology Mary Hale 7/8/2013 PSY 315 Dr. Ellis-Morris Prepare a written response to the following assignments located in the text: Ch. 1, Practice Problems: 12, 15, 19, 20, 21, & 22 (12) Explain and give an example for each of the following types of variables: A) equal interval- A variable whose value is not known and can take on different values. For example 0 degrees
Words: 747 - Pages: 3
SAMPLING DISTRIBUTIONS Simple Random Sample A simple random sample X 1 , , X n , taken from a population represented by a random variable X with mean and standard deviation , has the following characteristics. Each X i , i 1,, n , is a random variable that has the same distribution as X, and thus the same mean and standard deviation . The X i ’s are independent random variables implying the following identity: V X 1 X n V X 1 V X n 2 2
Words: 360 - Pages: 2
UNCERTAINTY AND DECISION MAKING In many countries, the majority of the consumers pay a fixed price per unit of electricity used regardless of when their consumption occurs. However, the costs to produce electricity vary a lot at different times of the day. Electricity cannot be stored. It must be generated and supplied to each customer as it is called for instantly, day or night, in extremely variable quantities. In virtually all power systems, electricity is produced by generators that are dispatched
Words: 1107 - Pages: 5
Binomial Distributions How to recognize binomial random variable: 1. The sample size n is fixed. 2. The n observations (or trials) are independent. 3. There are only 2 possible outcomes for each observation. They are labeled “Success” and “Failure” 4. The probability of success is the same for each trial. Let p = success probability and 1 – p = failure probability 5. The binomial random variable is . . . X = the number of successes out of n observations
Words: 371 - Pages: 2
CHOICE 1. A numerical description of the outcome of an experiment is called a a. descriptive statistic b. probability function c. variance d. random variable ANS: D PTS: 1 TOP: Discrete Probability Distributions 2. A random variable that can assume only a finite number of values is referred to as a(n) a. infinite sequence b. finite sequence c. discrete random variable d. discrete probability function ANS: C PTS: 1 TOP: Discrete Probability Distributions 3. A probability distribution showing the
Words: 9797 - Pages: 40
