L04: Homework Answer Key
|
|
- Barnaby Carr
- 5 years ago
- Views:
Transcription
1 L04: Homework Answer Key Instructions: You are encouraged to collaborate with other students on the homework, but it is important that you do your own work. Before working with someone else on the assignment, you should attempt each problem on your own. 1. In your own words, list the three rules of probability. A class survey in a statistics class asked students to list which state they were from. The results of the survey are given in the following table. Use this information to answer questions 2 through One of the probabilities is missing from the table. What should that missing probability be, if the table is supposed to be a probability distribution? Which rule of probability helped you answer this question? 38.3% 3. Randomly select a student in the class. According to the table, what is the probability of selecting a student that is from Washington or Oregon? 15.8% 4. Randomly select a student in the class. According to the table, what is the probability of selecting a student that is not from Idaho? Which rule of probability helped you answer this question? 78.1% 5. Randomly select a student in the class. According to the table, what is the probability of selecting a student that is not from Utah or California? 81.4% 6. Randomly select a student in the class. According to the table, what is the probability of selecting a student that is from Texas? It is not possible to answer this question using the data given. There may or may not be students from Texas, but we can t tell how many just from this data.
2 In the finance industry, investors make decisions based on past and present performance of the market. A stock is a share in the ownership of a company. For example, if you were to purchase stock in McDonald's, you would own a small part of that company. If the company does well in the future, the value of your stock would be expected to rise. Then, you could sell your shares in the company for a profit. Stocks are sold in a stock market. We will apply the methods of this lesson to find the mean and standard deviation of the annual change in the value of a stock or bond. Using historical data, a market analyst forecasts that the probability is 0.30 that the value of McDonald s stock will go up by 60% in the next year. The analyst calculates that the probability that the stock will increase by 15% is Some of the analyst s other forecasts are summarized in the table below: 7. Use the information in the table above to determine the probability that McDonald s stock will go down by 10% over the next year By adding two columns to this table, we can compute the mean and standard deviation of the value of McDonald's stock. Use this table to answer questions 8 through Complete the table above. What number should go in the position marked A? Use the table above to find the population mean (i.e. the expected value) for the percentage of growth for McDonald s stock over the next year. Give a number. μ = 19 %
3 10. If you were an executive at McDonald s, how would you interpret the population mean, μ, to a potential investor? Choose the answer that provides the best interpretation of this value. a. The price of McDonald's stock will probably increase over the next year. b. The price of McDonald's stock will probably decrease over the next year. c. The price of McDonald's stock has the potential of varying dramatically over the next year. d. The price of McDonald's stock will probably be fairly consistent over the next year. 11. What number should be entered in the position marked "B"? What is the population variance for the percent change in the price of McDonald s stock over the next year? σ 2 = Compute the population standard deviation of the annual change in the price of McDonald s stock. σ = 29.9 % 14. If you were an executive as McDonald s, how would you interpret the population standard deviation, σ, to a potential investor? Choose the answer that provides the best interpretation of this value. e. The price of McDonald s stock will probably increase over the next year. f. The price of McDonald s stock will probably decrease over the next year. g. The price of McDonald s stock has the potential of varying dramatically over the next year. h. The price of McDonald's stock will probably by fairly consistent over the next year. As you read previously, a stock is a share in the ownership of a company. If the company is perceived as increasing in value, this is usually reflected in an increase in the price per share of the stock. Bonds are used by the U.S. Government to raise money. When a bond is issued, the government promises to pay the purchase price of the bond plus an additional amount as interest at some future date (when the bond matures.) Some investors do not keep the bonds until they mature. These bonds can be bought and sold in the bond market. The price of the bond is determined by the perceived value of the bond at the time of sale. Bonds tend to provide a lower return on the investment, but they tend to be more secure. If an investor purchases a bond and keeps it until it matures, the government promises they will earn a fixed amount of interest. However, when people buy and sell bonds on the bond market, there is the possibility of both large gains and large losses. There is no guarantee that someone who buys and sells either stocks in the stock market or bonds in the bond market will make a profit. To protect against large fluctuations in either the stock market or the bond market, investors diversify their portfolio. They purchase a collection of stocks and bonds that will manage their risk and provide the greatest return possible at that level of risk.
4 Using historical data, the market analyst examined the profitability of investing in a 10-Year bond in the bond market. The probability that the price of a 10-year bond will change by the certain percentages is given below: Use this table to answer questions 15 and Find the population mean for the possible percent change in the price of a 10-year bond over the next year. Round your answer to 2 decimal places and include a minus (-) sign if your answer is negative. µ = % 16. Compute the population standard deviation of the annual change in the price of a 10-year bond. Round your answer to 2 decimal places. σ = % A fair coin is tossed 3 times. Let X be the number of heads observed. The possible values of X are 0,1,2, or 3. The probability of each of these outcomes is given here: X P(x) 1/8 3/8? 1/8 Use this table to answer questions 17 through What is the probability of getting exactly two heads on three tosses? 3/8
5 18. Compute the mean of the distribution of the number of heads observed in three tosses of a fair coin. Round your answer to 1 decimal place. µ = 1.5 % 19. Compute the standard deviation of the distribution of the number of heads observed in three tosses of a fair coin. Round your answer to 3 decimal places. σ = %
Examples: Random Variables. Discrete and Continuous Random Variables. Probability Distributions
Random Variables Examples: Random variable a variable (typically represented by x) that takes a numerical value by chance. Number of boys in a randomly selected family with three children. Possible values:
More informationMA 1125 Lecture 14 - Expected Values. Wednesday, October 4, Objectives: Introduce expected values.
MA 5 Lecture 4 - Expected Values Wednesday, October 4, 27 Objectives: Introduce expected values.. Means, Variances, and Standard Deviations of Probability Distributions Two classes ago, we computed the
More informationMA 1125 Lecture 12 - Mean and Standard Deviation for the Binomial Distribution. Objectives: Mean and standard deviation for the binomial distribution.
MA 5 Lecture - Mean and Standard Deviation for the Binomial Distribution Friday, September 9, 07 Objectives: Mean and standard deviation for the binomial distribution.. Mean and Standard Deviation of the
More informationMATH 264 Problem Homework I
MATH Problem Homework I Due to December 9, 00@:0 PROBLEMS & SOLUTIONS. A student answers a multiple-choice examination question that offers four possible answers. Suppose that the probability that the
More informationPart 1 In which we meet the law of averages. The Law of Averages. The Expected Value & The Standard Error. Where Are We Going?
1 The Law of Averages The Expected Value & The Standard Error Where Are We Going? Sums of random numbers The law of averages Box models for generating random numbers Sums of draws: the Expected Value Standard
More informationMidterm Test 1 (Sample) Student Name (PRINT):... Student Signature:... Use pencil, so that you can erase and rewrite if necessary.
MA 180/418 Midterm Test 1 (Sample) Student Name (PRINT):............................................. Student Signature:................................................... Use pencil, so that you can erase
More informationExpected Value of a Random Variable
Knowledge Article: Probability and Statistics Expected Value of a Random Variable Expected Value of a Discrete Random Variable You're familiar with a simple mean, or average, of a set. The mean value of
More informationMA 1125 Lecture 18 - Normal Approximations to Binomial Distributions. Objectives: Compute probabilities for a binomial as a normal distribution.
MA 25 Lecture 8 - Normal Approximations to Binomial Distributions Friday, October 3, 207 Objectives: Compute probabilities for a binomial as a normal distribution.. Normal Approximations to the Binomial
More informationUniform Probability Distribution. Continuous Random Variables &
Continuous Random Variables & What is a Random Variable? It is a quantity whose values are real numbers and are determined by the number of desired outcomes of an experiment. Is there any special Random
More informationThe Central Limit Theorem. Sec. 8.2: The Random Variable. it s Distribution. it s Distribution
The Central Limit Theorem Sec. 8.1: The Random Variable it s Distribution Sec. 8.2: The Random Variable it s Distribution X p and and How Should You Think of a Random Variable? Imagine a bag with numbers
More informationDiscrete Probability Distribution
1 Discrete Probability Distribution Key Definitions Discrete Random Variable: Has a countable number of values. This means that each data point is distinct and separate. Continuous Random Variable: Has
More informationValue (x) probability Example A-2: Construct a histogram for population Ψ.
Calculus 111, section 08.x The Central Limit Theorem notes by Tim Pilachowski If you haven t done it yet, go to the Math 111 page and download the handout: Central Limit Theorem supplement. Today s lecture
More informationDiscrete Probability Distributions
Page 1 of 6 Discrete Probability Distributions In order to study inferential statistics, we need to combine the concepts from descriptive statistics and probability. This combination makes up the basics
More informationMath 14 Lecture Notes Ch. 4.3
4.3 The Binomial Distribution Example 1: The former Sacramento King's DeMarcus Cousins makes 77% of his free throws. If he shoots 3 times, what is the probability that he will make exactly 0, 1, 2, or
More informationMA 1125 Lecture 05 - Measures of Spread. Wednesday, September 6, Objectives: Introduce variance, standard deviation, range.
MA 115 Lecture 05 - Measures of Spread Wednesday, September 6, 017 Objectives: Introduce variance, standard deviation, range. 1. Measures of Spread In Lecture 04, we looked at several measures of central
More informationA random variable (r. v.) is a variable whose value is a numerical outcome of a random phenomenon.
Chapter 14: random variables p394 A random variable (r. v.) is a variable whose value is a numerical outcome of a random phenomenon. Consider the experiment of tossing a coin. Define a random variable
More informationA random variable X is a function that assigns (real) numbers to the elements of the sample space S of a random experiment.
RANDOM VARIABLES and PROBABILITY DISTRIBUTIONS A random variable X is a function that assigns (real) numbers to the elements of the samle sace S of a random exeriment. The value sace V of a random variable
More informationUsing the Central Limit Theorem It is important for you to understand when to use the CLT. If you are being asked to find the probability of the
Using the Central Limit Theorem It is important for you to understand when to use the CLT. If you are being asked to find the probability of the mean, use the CLT for the mean. If you are being asked to
More informationRandom Variables CHAPTER 6.3 BINOMIAL AND GEOMETRIC RANDOM VARIABLES
Random Variables CHAPTER 6.3 BINOMIAL AND GEOMETRIC RANDOM VARIABLES Essential Question How can I determine whether the conditions for using binomial random variables are met? Binomial Settings When the
More informationECON 214 Elements of Statistics for Economists 2016/2017
ECON 214 Elements of Statistics for Economists 2016/2017 Topic The Normal Distribution Lecturer: Dr. Bernardin Senadza, Dept. of Economics bsenadza@ug.edu.gh College of Education School of Continuing and
More informationBinomial Random Variables. Binomial Random Variables
Bernoulli Trials Definition A Bernoulli trial is a random experiment in which there are only two possible outcomes - success and failure. 1 Tossing a coin and considering heads as success and tails as
More informationStatistics vs. statistics
Statistics vs. statistics Question: What is Statistics (with a capital S)? Definition: Statistics is the science of collecting, organizing, summarizing and interpreting data. Note: There are 2 main ways
More informationPart 10: The Binomial Distribution
Part 10: The Binomial Distribution The binomial distribution is an important example of a probability distribution for a discrete random variable. It has wide ranging applications. One readily available
More informationA random variable is a quantitative variable that represents a certain
Section 6.1 Discrete Random Variables Example: Probability Distribution, Spin the Spinners Sum of Numbers on Spinners Theoretical Probability 2 0.04 3 0.08 4 0.12 5 0.16 6 0.20 7 0.16 8 0.12 9 0.08 10
More informationThe Binomial Probability Distribution
The Binomial Probability Distribution MATH 130, Elements of Statistics I J. Robert Buchanan Department of Mathematics Fall 2017 Objectives After this lesson we will be able to: determine whether a probability
More information4 Random Variables and Distributions
4 Random Variables and Distributions Random variables A random variable assigns each outcome in a sample space. e.g. called a realization of that variable to Note: We ll usually denote a random variable
More informationThe Binomial Distribution
The Binomial Distribution Properties of a Binomial Experiment 1. It consists of a fixed number of observations called trials. 2. Each trial can result in one of only two mutually exclusive outcomes labeled
More informationChapter 7: Random Variables
Chapter 7: Random Variables 7.1 Discrete and Continuous Random Variables 7.2 Means and Variances of Random Variables 1 Introduction A random variable is a function that associates a unique numerical value
More informationSection 8.4 The Binomial Distribution
Section 8.4 The Binomial Distribution Binomial Experiment A binomial experiment has the following properties: 1. The number of trials in the experiment is fixed. 2. There are two outcomes of each trial:
More informationChapter 7 Study Guide: The Central Limit Theorem
Chapter 7 Study Guide: The Central Limit Theorem Introduction Why are we so concerned with means? Two reasons are that they give us a middle ground for comparison and they are easy to calculate. In this
More informationMath 14 Lecture Notes Ch Mean
4. Mean, Expected Value, and Standard Deviation Mean Recall the formula from section. for find the population mean of a data set of elements µ = x 1 + x + x +!+ x = x i i=1 We can find the mean of the
More informationChapter 5. Sampling Distributions
Lecture notes, Lang Wu, UBC 1 Chapter 5. Sampling Distributions 5.1. Introduction In statistical inference, we attempt to estimate an unknown population characteristic, such as the population mean, µ,
More informationStatistics 6 th Edition
Statistics 6 th Edition Chapter 5 Discrete Probability Distributions Chap 5-1 Definitions Random Variables Random Variables Discrete Random Variable Continuous Random Variable Ch. 5 Ch. 6 Chap 5-2 Discrete
More informationCentral Limit Theorem 11/08/2005
Central Limit Theorem 11/08/2005 A More General Central Limit Theorem Theorem. Let X 1, X 2,..., X n,... be a sequence of independent discrete random variables, and let S n = X 1 + X 2 + + X n. For each
More informationCover Page Homework #8
MODESTO JUNIOR COLLEGE Department of Mathematics MATH 134 Fall 2011 Problem 11.6 Cover Page Homework #8 (a) What does the population distribution describe? (b) What does the sampling distribution of x
More informationMath 140 Introductory Statistics. Next test on Oct 19th
Math 140 Introductory Statistics Next test on Oct 19th At the Hockey games Construct the probability distribution for X, the probability for the total number of people that can attend two distinct games
More informationWebAssign Math 3680 Homework 5 Devore Fall 2013 (Homework)
WebAssign Math 3680 Homework 5 Devore Fall 2013 (Homework) Current Score : 135.45 / 129 Due : Friday, October 11 2013 11:59 PM CDT Mirka Martinez Applied Statistics, Math 3680-Fall 2013, section 2, Fall
More informationLecture 9. Probability Distributions. Outline. Outline
Outline Lecture 9 Probability Distributions 6-1 Introduction 6- Probability Distributions 6-3 Mean, Variance, and Expectation 6-4 The Binomial Distribution Outline 7- Properties of the Normal Distribution
More informationStatistics and Their Distributions
Statistics and Their Distributions Deriving Sampling Distributions Example A certain system consists of two identical components. The life time of each component is supposed to have an expentional distribution
More informationStat511 Additional Materials
Binomial Random Variable Stat511 Additional Materials The first discrete RV that we will discuss is the binomial random variable. The binomial random variable is a result of observing the outcomes from
More informationLecture 9. Probability Distributions
Lecture 9 Probability Distributions Outline 6-1 Introduction 6-2 Probability Distributions 6-3 Mean, Variance, and Expectation 6-4 The Binomial Distribution Outline 7-2 Properties of the Normal Distribution
More informationDiscrete Probability Distributions
Discrete Probability Distributions Answers 1. Suppose a statistician working for CSULA Federal Credit Union collected data on ATM withdrawals for the population of the credit union s customers. The statistician
More informationExercise Questions: Chapter What is wrong? Explain what is wrong in each of the following scenarios.
5.9 What is wrong? Explain what is wrong in each of the following scenarios. (a) If you toss a fair coin three times and a head appears each time, then the next toss is more likely to be a tail than a
More information7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4
7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4 - Would the correlation between x and y in the table above be positive or negative? The correlation is negative. -
More informationA probability distribution shows the possible outcomes of an experiment and the probability of each of these outcomes.
Introduction In the previous chapter we discussed the basic concepts of probability and described how the rules of addition and multiplication were used to compute probabilities. In this chapter we expand
More informationVersion A. Problem 1. Let X be the continuous random variable defined by the following pdf: 1 x/2 when 0 x 2, f(x) = 0 otherwise.
Math 224 Q Exam 3A Fall 217 Tues Dec 12 Version A Problem 1. Let X be the continuous random variable defined by the following pdf: { 1 x/2 when x 2, f(x) otherwise. (a) Compute the mean µ E[X]. E[X] x
More informationProbability Distributions. Definitions Discrete vs. Continuous Mean and Standard Deviation TI 83/84 Calculator Binomial Distribution
Probability Distributions Definitions Discrete vs. Continuous Mean and Standard Deviation TI 83/84 Calculator Binomial Distribution Definitions Random Variable: a variable that has a single numerical value
More information3. The n observations are independent. Knowing the result of one observation tells you nothing about the other observations.
Binomial and Geometric Distributions - Terms and Formulas Binomial Experiments - experiments having all four conditions: 1. Each observation falls into one of two categories we call them success or failure.
More informationData Analysis and Statistical Methods Statistics 651
Review of previous lecture: Why confidence intervals? Data Analysis and Statistical Methods Statistics 651 http://www.stat.tamu.edu/~suhasini/teaching.html Suhasini Subba Rao Suppose you want to know the
More informationBinomial formulas: The binomial coefficient is the number of ways of arranging k successes among n observations.
Chapter 8 Notes Binomial and Geometric Distribution Often times we are interested in an event that has only two outcomes. For example, we may wish to know the outcome of a free throw shot (good or missed),
More informationLaw of Large Numbers, Central Limit Theorem
November 14, 2017 November 15 18 Ribet in Providence on AMS business. No SLC office hour tomorrow. Thursday s class conducted by Teddy Zhu. November 21 Class on hypothesis testing and p-values December
More informationNormal Cumulative Distribution Function (CDF)
The Normal Model 2 Solutions COR1-GB.1305 Statistics and Data Analysis Normal Cumulative Distribution Function (CDF 1. Suppose that an automobile muffler is designed so that its lifetime (in months is
More informationMath489/889 Stochastic Processes and Advanced Mathematical Finance Homework 5
Math489/889 Stochastic Processes and Advanced Mathematical Finance Homework 5 Steve Dunbar Due Fri, October 9, 7. Calculate the m.g.f. of the random variable with uniform distribution on [, ] and then
More informationWe use probability distributions to represent the distribution of a discrete random variable.
Now we focus on discrete random variables. We will look at these in general, including calculating the mean and standard deviation. Then we will look more in depth at binomial random variables which are
More informationOCR Statistics 1. Discrete random variables. Section 2: The binomial and geometric distributions. When to use the binomial distribution
Discrete random variables Section 2: The binomial and geometric distributions Notes and Examples These notes contain subsections on: When to use the binomial distribution Binomial coefficients Worked examples
More informationMath : Spring 2008
Math 1070-2: Spring 2008 Lecture 7 Davar Khoshnevisan Department of Mathematics University of Utah http://www.math.utah.edu/ davar February 27, 2008 An example A WHO study of health: In Canada, the systolic
More informationCHAPTER 6 Random Variables
CHAPTER 6 Random Variables 6.3 Binomial and Geometric Random Variables The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers Binomial and Geometric Random
More informationThe Normal Probability Distribution
1 The Normal Probability Distribution Key Definitions Probability Density Function: An equation used to compute probabilities for continuous random variables where the output value is greater than zero
More information3. The n observations are independent. Knowing the result of one observation tells you nothing about the other observations.
Binomial and Geometric Distributions - Terms and Formulas Binomial Experiments - experiments having all four conditions: 1. Each observation falls into one of two categories we call them success or failure.
More informationECON 214 Elements of Statistics for Economists
ECON 214 Elements of Statistics for Economists Session 7 The Normal Distribution Part 1 Lecturer: Dr. Bernardin Senadza, Dept. of Economics Contact Information: bsenadza@ug.edu.gh College of Education
More informationCHAPTER 6 Random Variables
CHAPTER 6 Random Variables 6.3 Binomial and Geometric Random Variables The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers Binomial and Geometric Random
More information5.1 Personal Probability
5. Probability Value Page 1 5.1 Personal Probability Although we think probability is something that is confined to math class, in the form of personal probability it is something we use to make decisions
More informationX P(X) (c) Express the event performing at least two tests in terms of X and find its probability.
AP Stats ~ QUIZ 6 Name Period 1. The probability distribution below is for the random variable X = number of medical tests performed on a randomly selected outpatient at a certain hospital. X 0 1 2 3 4
More informationStatistics 511 Supplemental Materials
Gaussian (or Normal) Random Variable In this section we introduce the Gaussian Random Variable, which is more commonly referred to as the Normal Random Variable. This is a random variable that has a bellshaped
More informationSection 3.4 The Normal Distribution
Section 3.4 The Normal Distribution Properties of the Normal Distribution Curve 1. We denote the normal random variable with X = x. 2. The curve has a peak at x = µ. 3. The curve is symmetric about the
More informationChapter 6: Random Variables
Chapter 6: Random Variables Section 6.3 The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE Chapter 6 Random Variables 6.1 Discrete and Continuous Random Variables 6.2 Transforming and
More informationInvesting. Managing Risk Time and Diversification
Unit 8 Investing Lesson 8A: Managing Risk Time and Diversification Rule 8: Grow your wealth safely. Investing requires three simple steps: (i) saving a portion of your income each year to invest, (ii)
More informationSTA Module 3B Discrete Random Variables
STA 2023 Module 3B Discrete Random Variables Learning Objectives Upon completing this module, you should be able to 1. Determine the probability distribution of a discrete random variable. 2. Construct
More informationChapter 3 - Lecture 5 The Binomial Probability Distribution
Chapter 3 - Lecture 5 The Binomial Probability October 12th, 2009 Experiment Examples Moments and moment generating function of a Binomial Random Variable Outline Experiment Examples A binomial experiment
More informationChapter Seven: Confidence Intervals and Sample Size
Chapter Seven: Confidence Intervals and Sample Size A point estimate is: The best point estimate of the population mean µ is the sample mean X. Three Properties of a Good Estimator 1. Unbiased 2. Consistent
More informationLecture 9: Plinko Probabilities, Part III Random Variables, Expected Values and Variances
Physical Principles in Biology Biology 3550 Fall 2018 Lecture 9: Plinko Probabilities, Part III Random Variables, Expected Values and Variances Monday, 10 September 2018 c David P. Goldenberg University
More informationMidTerm 1) Find the following (round off to one decimal place):
MidTerm 1) 68 49 21 55 57 61 70 42 59 50 66 99 Find the following (round off to one decimal place): Mean = 58:083, round off to 58.1 Median = 58 Range = max min = 99 21 = 78 St. Deviation = s = 8:535,
More information4.2 Probability Distributions
4.2 Probability Distributions Definition. A random variable is a variable whose value is a numerical outcome of a random phenomenon. The probability distribution of a random variable tells us what the
More informationChapter 7. Confidence Intervals and Sample Sizes. Definition. Definition. Definition. Definition. Confidence Interval : CI. Point Estimate.
Chapter 7 Confidence Intervals and Sample Sizes 7. Estimating a Proportion p 7.3 Estimating a Mean µ (σ known) 7.4 Estimating a Mean µ (σ unknown) 7.5 Estimating a Standard Deviation σ In a recent poll,
More informationCentral Limit Theorem
Central Limit Theorem Lots of Samples 1 Homework Read Sec 6-5. Discussion Question pg 329 Do Ex 6-5 8-15 2 Objective Use the Central Limit Theorem to solve problems involving sample means 3 Sample Means
More informationTest 7A AP Statistics Name: Directions: Work on these sheets.
Test 7A AP Statistics Name: Directions: Work on these sheets. Part 1: Multiple Choice. Circle the letter corresponding to the best answer. 1. Suppose X is a random variable with mean µ. Suppose we observe
More informationProblem Set 07 Discrete Random Variables
Name Problem Set 07 Discrete Random Variables MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Find the mean of the random variable. 1) The random
More informationProblem A Grade x P(x) To get "C" 1 or 2 must be 1 0.05469 B A 2 0.16410 3 0.27340 4 0.27340 5 0.16410 6 0.05470 7 0.00780 0.2188 0.5468 0.2266 Problem B Grade x P(x) To get "C" 1 or 2 must 1 0.31150 be
More informationChapter 4 Discrete Random variables
Chapter 4 Discrete Random variables A is a variable that assumes numerical values associated with the random outcomes of an experiment, where only one numerical value is assigned to each sample point.
More informationAMS7: WEEK 4. CLASS 3
AMS7: WEEK 4. CLASS 3 Sampling distributions and estimators. Central Limit Theorem Normal Approximation to the Binomial Distribution Friday April 24th, 2015 Sampling distributions and estimators REMEMBER:
More informationConfidence Intervals: Review
University of Utah February 28, 2018 1 2 Law of Large Numbers Draw your samples from any population with finite mean µ. Then LLN says Law of Large Numbers Draw your samples from any population with finite
More information1. Confidence Intervals (cont.)
Math 1125-Introductory Statistics Lecture 23 11/1/06 1. Confidence Intervals (cont.) Let s review. We re in a situation, where we don t know µ, but we have a number from a normal population, either an
More informationA Derivation of the Normal Distribution. Robert S. Wilson PhD.
A Derivation of the Normal Distribution Robert S. Wilson PhD. Data are said to be normally distributed if their frequency histogram is apporximated by a bell shaped curve. In practice, one can tell by
More informationI. Standard Error II. Standard Error III. Standard Error 2.54
1) Original Population: Match the standard error (I, II, or III) with the correct sampling distribution (A, B, or C) and the correct sample size (1, 5, or 10) I. Standard Error 1.03 II. Standard Error
More informationCHAPTER 4 DISCRETE PROBABILITY DISTRIBUTIONS
CHAPTER 4 DISCRETE PROBABILITY DISTRIBUTIONS A random variable is the description of the outcome of an experiment in words. The verbal description of a random variable tells you how to find or calculate
More informationChapter 5 Student Lecture Notes 5-1. Department of Quantitative Methods & Information Systems. Business Statistics
Chapter 5 Student Lecture Notes 5-1 Department of Quantitative Methods & Information Systems Business Statistics Chapter 5 Discrete Probability Distributions QMIS 120 Dr. Mohammad Zainal Chapter Goals
More informationBinomial and multinomial distribution
1-Binomial distribution Binomial and multinomial distribution The binomial probability refers to the probability that a binomial experiment results in exactly "x" successes. The probability of an event
More informationStatistical Methods in Practice STAT/MATH 3379
Statistical Methods in Practice STAT/MATH 3379 Dr. A. B. W. Manage Associate Professor of Mathematics & Statistics Department of Mathematics & Statistics Sam Houston State University Overview 6.1 Discrete
More informationChapter 6 Section Review day s.notebook. May 11, Honors Statistics. Aug 23-8:26 PM. 3. Review team test.
Honors Statistics Aug 23-8:26 PM 3. Review team test Aug 23-8:31 PM 1 Nov 27-10:28 PM 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9 6.10 6.11 6.12 Nov 27-9:53 PM 2 May 8-7:44 PM May 1-9:09 PM 3 Dec 1-2:08 PM Sep
More informationMATH1215: Mathematical Thinking Sec. 08 Spring Worksheet 9: Solution. x P(x)
N. Name: MATH: Mathematical Thinking Sec. 08 Spring 0 Worksheet 9: Solution Problem Compute the expected value of this probability distribution: x 3 8 0 3 P(x) 0. 0.0 0.3 0. Clearly, a value is missing
More informationSec 5.2. Mean Variance Expectation. Bluman, Chapter 5 1
Sec 5.2 Mean Variance Expectation Bluman, Chapter 5 1 Review: Do you remember the following? The symbols for Variance Standard deviation Mean The relationship between variance and standard deviation? Bluman,
More informationMr. Orchard s Math 141 WIR 8.5, 8.6, 5.1 Week 13
1. Find the following probabilities, where Z is a random variable with a standard normal distribution and X is a normal random variable with mean µ = 380 and standard deviation σ = 21: (Round your answers
More informationME3620. Theory of Engineering Experimentation. Spring Chapter III. Random Variables and Probability Distributions.
ME3620 Theory of Engineering Experimentation Chapter III. Random Variables and Probability Distributions Chapter III 1 3.2 Random Variables In an experiment, a measurement is usually denoted by a variable
More informationChapter 8: Binomial and Geometric Distributions
Chapter 8: Binomial and Geometric Distributions Section 8.1 Binomial Distributions The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE Section 8.1 Binomial Distribution Learning Objectives
More informationChapter 5. Discrete Probability Distributions. McGraw-Hill, Bluman, 7 th ed, Chapter 5 1
Chapter 5 Discrete Probability Distributions McGraw-Hill, Bluman, 7 th ed, Chapter 5 1 Chapter 5 Overview Introduction 5-1 Probability Distributions 5-2 Mean, Variance, Standard Deviation, and Expectation
More informationSTOR 155 Introductory Statistics (Chap 5) Lecture 14: Sampling Distributions for Counts and Proportions
The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL STOR 155 Introductory Statistics (Chap 5) Lecture 14: Sampling Distributions for Counts and Proportions 5/31/11 Lecture 14 1 Statistic & Its Sampling Distribution
More informationSec$on 6.1: Discrete and Con.nuous Random Variables. Tuesday, November 14 th, 2017
Sec$on 6.1: Discrete and Con.nuous Random Variables Tuesday, November 14 th, 2017 Discrete and Continuous Random Variables Learning Objectives After this section, you should be able to: ü COMPUTE probabilities
More informationStandard Deviation. 1 Motivation 1
Standard Deviation Table of Contents 1 Motivation 1 2 Standard Deviation 2 3 Computing Standard Deviation 4 4 Calculator Instructions 7 5 Homework Problems 8 5.1 Instructions......................................
More informationBusiness Statistics 41000: Probability 4
Business Statistics 41000: Probability 4 Drew D. Creal University of Chicago, Booth School of Business February 14 and 15, 2014 1 Class information Drew D. Creal Email: dcreal@chicagobooth.edu Office:
More information5.4 Normal Approximation of the Binomial Distribution Lesson MDM4U Jensen
5.4 Normal Approximation of the Binomial Distribution Lesson MDM4U Jensen Review From Yesterday Bernoulli Trials have 3 properties: 1. 2. 3. Binomial Probability Distribution In a binomial experiment with
More information