Similar documents
Version 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.

Lecture 23. STAT 225 Introduction to Probability Models April 4, Whitney Huang Purdue University. Normal approximation to Binomial

Chapter 2: Random Variables (Cont d)

(Practice Version) Midterm Exam 1

7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4

. (i) What is the probability that X is at most 8.75? =.875

Business Statistics Fall Quarter 2015 Midterm Answer Key

The Normal Distribution

Econ 250 Fall Due at November 16. Assignment 2: Binomial Distribution, Continuous Random Variables and Sampling

PRMIA Exam 8002 PRM Certification - Exam II: Mathematical Foundations of Risk Measurement Version: 6.0 [ Total Questions: 132 ]

STA 103: Final Exam. Print clearly on this exam. Only correct solutions that can be read will be given credit.

Normal Distribution. Notes. Normal Distribution. Standard Normal. Sums of Normal Random Variables. Normal. approximation of Binomial.

19. CONFIDENCE INTERVALS FOR THE MEAN; KNOWN VARIANCE

STA Module 3B Discrete Random Variables

Sampling Distribution

Lecture 37 Sections 11.1, 11.2, Mon, Mar 31, Hampden-Sydney College. Independent Samples: Comparing Means. Robb T. Koether.

STA 6166 Fall 2007 Web-based Course. Notes 10: Probability Models

Back to estimators...

STAT 201 Chapter 6. Distribution

INSTITUTE AND FACULTY OF ACTUARIES. Curriculum 2019 SPECIMEN EXAMINATION

Exam 2 Spring 2015 Statistics for Applications 4/9/2015

Week 2 Quantitative Analysis of Financial Markets Hypothesis Testing and Confidence Intervals

Financial Economics. Runs Test

Introduction to Probability and Inference HSSP Summer 2017, Instructor: Alexandra Ding July 19, 2017

MATH 10 INTRODUCTORY STATISTICS

Section 0: Introduction and Review of Basic Concepts

1) 3 points Which of the following is NOT a measure of central tendency? a) Median b) Mode c) Mean d) Range

Section 2: Estimation, Confidence Intervals and Testing Hypothesis

Math 1070 Sample Exam 2

Fall 2011 Exam Score: /75. Exam 3

Chapter 4 and 5 Note Guide: Probability Distributions

6. Continous Distributions

Bin(20,.5) and N(10,5) distributions

Chapter 7 1. Random Variables

SECTION 4.4: Expected Value

Section 2: Estimation, Confidence Intervals and Testing Hypothesis

Final/Exam #3 Form B - Statistics 211 (Fall 1999)

Chapter 4 Continuous Random Variables and Probability Distributions

Random variables. Discrete random variables. Continuous random variables.

Review for Final Exam Spring 2014 Jeremy Orloff and Jonathan Bloom

Continuous Probability Distributions & Normal Distribution

Honor Code: By signing my name below, I pledge my honor that I have not violated the Booth Honor Code during this examination.

The Normal Distribution

Introduction to Probability

CHAPTER 8. Confidence Interval Estimation Point and Interval Estimates

Chapter 16. Random Variables. Copyright 2010 Pearson Education, Inc.

Lecture 16: Estimating Parameters (Confidence Interval Estimates of the Mean)

Lecture 8. The Binomial Distribution. Binomial Distribution. Binomial Distribution. Probability Distributions: Normal and Binomial

Math489/889 Stochastic Processes and Advanced Mathematical Finance Homework 5

Chapter 6 Confidence Intervals

Chapter 4 Continuous Random Variables and Probability Distributions

STAT/MATH 395 PROBABILITY II

STA Rev. F Learning Objectives. What is a Random Variable? Module 5 Discrete Random Variables

Exam M Fall 2005 PRELIMINARY ANSWER KEY

continuous rv Note for a legitimate pdf, we have f (x) 0 and f (x)dx = 1. For a continuous rv, P(X = c) = c f (x)dx = 0, hence

CS 361: Probability & Statistics

Mean Note: Weights were measured to the nearest 0.1 kg.

Homework: Due Wed, Feb 20 th. Chapter 8, # 60a + 62a (count together as 1), 74, 82

15.063: Communicating with Data Summer Recitation 4 Probability III

Labor Economics Field Exam Spring 2011

Mean GMM. Standard error

Discrete Probability Distributions and application in Business

Model Paper Statistics Objective. Paper Code Time Allowed: 20 minutes

Quantitative Methods for Economics, Finance and Management (A86050 F86050)

Business Statistics Midterm Exam Fall 2013 Russell

Please have out... - notebook - calculator

Probability Theory and Simulation Methods. April 9th, Lecture 20: Special distributions

Lecture 39 Section 11.5

7.1 Comparing Two Population Means: Independent Sampling

Midterm 3. Math Summer Last Name: First Name: Student Number: Section (circle one): 921 (Warren Code) or 922 (Marc Carnovale)

PhD Qualifier Examination

MAKING SENSE OF DATA Essentials series

Law of Large Numbers, Central Limit Theorem

Chapter 5 Discrete Probability Distributions. Random Variables Discrete Probability Distributions Expected Value and Variance

Probability & Statistics

Math 1070 Sample Exam 2 Spring 2015

Chapter 8. Variables. Copyright 2004 Brooks/Cole, a division of Thomson Learning, Inc.

18.05 Problem Set 3, Spring 2014 Solutions

Introduction to Statistics I

Mathematics of Finance Final Preparation December 19. To be thoroughly prepared for the final exam, you should

STAT 1220 FALL 2010 Common Final Exam December 10, 2010

Discrete Random Variables

8.1 Estimation of the Mean and Proportion

Probability Distributions

A continuous random variable is one that can theoretically take on any value on some line interval. We use f ( x)

Lecture Slides. Elementary Statistics Tenth Edition. by Mario F. Triola. and the Triola Statistics Series. Slide 1

Probability Distribution Unit Review

Chapter 3 - Lecture 3 Expected Values of Discrete Random Va

4 Random Variables and Distributions

A) The first quartile B) The Median C) The third quartile D) None of the previous. 2. [3] If P (A) =.8, P (B) =.7, and P (A B) =.

Chapter 16. Random Variables. Copyright 2010, 2007, 2004 Pearson Education, Inc.

STA2601. Tutorial letter 105/2/2018. Applied Statistics II. Semester 2. Department of Statistics STA2601/105/2/2018 TRIAL EXAMINATION PAPER

MidTerm 1) Find the following (round off to one decimal place):

Econ Financial Markets Spring 2011 Professor Robert Shiller. Problem Set 2

**BEGINNING OF EXAMINATION** A random sample of five observations from a population is:

μ: ESTIMATES, CONFIDENCE INTERVALS, AND TESTS Business Statistics

PSTAT 172A: ACTUARIAL STATISTICS FINAL EXAM

ECON Introductory Econometrics. Lecture 1: Introduction and Review of Statistics

PhD Qualifier Examination

Tests for One Variance

Transcription:

Name: CS3130: Probability and Statistics for Engineers Practice Final Exam Instructions: You may use any notes that you like, but no calculators or computers are allowed. Be sure to show all of your work. It is not necessary to simplify your answers. Note: You may also want to see the practice exams for the ECE class: http://www.ece.utah.edu/~ece3530/ 1. It is estimated that 6 out of every 1,000 people have autism spectrum disorder, i.e., there is a 0.6% chance of being born with the disorder. Of people with autism spectrum disorder, 80% are male. Let A be the event that a person has autism spectrum disorder, and M be the event that a person is a male. Also, assume in this problem that it is equally likely to be born male or female, that is, P (M) = P (M c ) = 0.5. (a) What does P (M A) mean in English? What is its value? (b) What does P (A M) mean in English? What is its value? (c) What is the probability of being a female with autism spectrum disorder? (First write down the probability expression in terms of A and M, and then compute.)

2. Let X be a geometric random variable, with probability p of success. Hint: you will need the following identity somewhere in this problem: n (1 p) i 1 p = 1 (1 p) n. i=1 (a) What is the probability that the first success is not on the first attempt? In other words, what is P (X > 1)? (b) What is P (X n)? (c) What is P (X > n), i.e., the probability of starting on a losing streak of length n? Hint: use your answer in (b). Also, check that this matches (a) when n = 1. (d) Show that starting on a losing streak does not change the probability of continuing a losing streak. That is, use your result in (c) to show that P (X = k + n X > n) = P (X = k).

3. Consider a random variable X with cummulative distribution function (cdf): 0 for x < 0 F X (x) = k (x + sin(x)) for 0 x π 1 for x > π (a) What is the value for k that makes F X a valid cdf? (b) What is the probability density function (pdf) for X? (c) What is P ( X π 2 ) (d) What is the integral to compute E[X]? (you don t need to solve it)

4. Say you are given two random variables X and Y that have the same variance, Var(X) = Var(Y ) = σ 2. (a) If X and Y are uncorrelated, what is Var(X + Y )? (b) If X and Y are negatively correlated with ρ(x, Y ) = 1, what is Var(X + Y )? (c) For both parts (a) and (b) above, state whether X and Y are dependent, independent, or not enough information to tell. Explain your answers.

5. A baseball player has a batting average of 0.305 after 100 at-bats. Use a normal approximation to give a 99% confidence interval for the player s true probability of hitting safely. To be conservative, you should use a worst case value of σ = 0.25 in your formula (this is the largest that σ can get for an estimate of a percentage). You just need to set up the formula and plug the correct numbers into it, you don t need to do the arithmetic. You will want to use one of the following values: z 0.05 = 1.64, z 0.025 = 1.96, z 0.005 = 2.58, z 0.01 = 2.33

6. You ve started a company that creates phone apps. At your current price point, you need to sell 800 apps per month to stay profitable. Over the last 4 months, you have sold 805 apps on average each month. The sample standard deviation during that time period is 10 apps. (a) Set up a hypothesis test that your average monthly sales exceed the goal. What is your null hypothesis and alternate hypothesis? (b) Let F denote the cdf for the appropriate t distribution. Using a level of α = 0.05, circle one of the options below for your critical value: F (0.05) = 0.518, F 1 (0.05) = 2.53, F (0.95) = 0.794, F 1 (0.95) = 2.35 (c) Compute the statistic you would use to test the hypothesis. Hint: its a simple number! (d) Would you reject the null hypothesis at the α = 0.05 level? Circle one: Yes or No