Elisha Mae Kostka 243 Assignment Mock Test 1 due 02/11/2015 at 09:01am PST

Size: px
Start display at page:

Download "Elisha Mae Kostka 243 Assignment Mock Test 1 due 02/11/2015 at 09:01am PST"

Transcription

1 Elisha Mae Kostka 243 Assignment Mock Test 1 due 02/11/2015 at 09:01am PST 1. (1 pt) Luis Gonzalez began his career as a major league baseball player in You are given a sample of the number of homeruns hit in 5 of the seasons. What type of study is this?. DESCRIPTIVE. INFERENTIAL 2. (1 pt) Annual tuition rates are a concern for the majority of college students at public universities. Suppose you are provided with the resident annual tuition (for 15 credit hours) for each public university in the U.S. for the school year. What type of study is this?. DESCRIPTIVE. INFERENTIAL 3. (1 pt) A sample of 30 dentists from Seattle is taken to estimate the median income of all Seattle residents. Is this study. REPRESENTATIVE?. NON-REPRESENTATIVE? A simple random sample of men over age 18 is taken to estimate the mean weight of all adult males. Is this study. REPRESENTATIVE?. NON-REPRESENTATIVE? A simple random sample of voters is taken in order to determine the chances of a certain candidate winning an election. Is this study. REPRESENTATIVE?. NON-REPRESENTATIVE? Using a sample of 40 patients from a local hospital, researchers measured cholesterol level in an attempt to estimate the mean cholesterol level of U.S. citizens. Is this study. REPRESENTATIVE?. NON-REPRESENTATIVE? 1 4. (1 pt) Of the variables you have studied so far, which type yields nonnumerical data?. Quantitative discrete. Quantitative continuous C. Qualitative. None of the above C 5. (1 pt) a - Qualitative data b - Discrete, quantitative data c - Continuous, quantitative data Fill in the appropriate letter (from above) of the term defined in each of the parts below. a) Data obtained by observing numerical values which form some interval of numbers b) Data obtained from a nonnumerically valued variable c) Data obtained by observing numerical values which form a finite, or countably infinite, set of numbers C 6. (1 pt) Industry Research polled teenagers on sunscreen use. The survey revealed that 46% of teenage girls and 30% of teenage boys regularly use sunscreen before going out in the sun. identify the two populations. all teenagers. teenage girls and teenage boys who use sunscreen regularly C. teenage girls and teenage boys. None of the above identify the specified attribute

2 . uses sunscreen before going out in the sun. being a teenager C. being a teenage girl or a teenage boy. None of the above are the proportions 0.46 (46%) and 0.30 (30%) population proportions or a sample proportions?. population proportions. sample proportions C. None of the above Grade on Statistics Exam Below Relative Frequency C Before leaving a particular restaurant, patrons are asked to respond to a questionaire containing the questions given below. For each question, indicate (using the pull-down menu) whether the possible responses are Interval, Nominal, or Ordinal.? 1. Would your overall rating of this restaurant be excellent, good, fair, or poor?? 2. Which of the following attributes of this restaurant do you find most attractive: service, prices, quality of food, menu options?? 3. Do you consider our prices to be high, average, or low?? 4. Have you eaten at this restaurant previously? O N O N 8. (1 pt) Grade on Statistics Exam Frequency Below Given the frequency table above, construct the following: (a) The relative frequency table that corresponds with the above table. 9. (1 pt) The following data contains days when road rage occured according to a study. The goal of the study is to determine when road rage occurs most often. F, Tu, Th, Th, M, M, F, F, F, M, Su, Sa, F, Su, Tu, F, Sa, M, F, F, Th, F, F, Th, Su, Th, Th, F, F, Sa, M, W, W, Th, Tu, Tu, W, M, F, F, W, Su, F, Tu, Sa, W, Th Find the mode of the above data. Mode = F 10. (1 pt) For the given data, find Σx, n, and x: x 1 = 15, x 2 = 12, x 3 = 12, x 4 = 17, x 5 = 13, x 6 = 12, x 7 = 6, x 8 = 11 Σx = n = x =

3 11. (1 pt) The standard deviation is preferable to the range as a measure of variation because it takes into account all the observations, not only the largest and the smallest ones. True. False One major drawback to the standard deviation as a measure of variation is that it is. Not resistant. Decreasing C. Increasing. None of the above Now use the same data set, but this time regard it as a population. Calculate the mean and the standard deviation. population mean = population standard deviation = (1 pt) The timeplot below gives the share price in dollars of General Electric stock, with the bar chart giving the volume in millions of shares. The plots are for the one-year period September 2001-September (Click on the image for a larger view. ) 12. (1 pt) Calculate the mode, mean, and median of the following data: (a) Which of the following is a true statement? Mode = Mean = Median = (1 pt) 13, 16, 11, 18, 8, 13, 12, 13 The length (in pages) of math research projects is given below. Using this information, calculate the mean and the standard deviation regarding the data set as a sample.. The price of General Electric stock has been stable for this year.. There has been a general upward trend in the stock price over this time period. C. The price should return to 40 dollars within six months because of the cycle.. There has been a general downward trend in the stock price over this time period. (b) If you bought a single share of stock at the maximum price and sold it at the minimum price during this one-year period, you would have lost about. 45 dollars.. 25 dollars. C. 35 dollars.. 15 dollars. E. Cannot be determined from the graph. (c) The maximum price per share for this time period was about 24, 22, 23, 22, 31, 14, 26, 35, 40 sample mean = sample standard deviation = dollars.. 20 dollars. C. 45 dollars.. 25 dollars.

4 15. (1 pt) Consider the histogram given below: (Click on the image for a larger view. ) (a) Which of the following is a correct statement?. The histogram is symmetric.. The tallest person must have a height of at least 79 inches. C. Approximately half the students have heights between 65 and 71 inches.. None of the above are correct. (b) The interval that contains closest to 10 students is inches inches. C inches inches. 16. (1 pt) In a statistics class with 136 students, the professor records how much money each student has in their possession during the first class of the semester. The histogram below is of the data collected. (Click on the image for a larger view. ) (a) The histogram. is asymmetric.. is skewed right. C. has an outlier.. all of the above. (b) The percentage of students with over 20 dollars in their possession is. over 40%.. about 20%. C. about 10%.. about 30%. (c) The number of students with under 10 dollars in their possession is closest to C (1 pt) Consumers Union measured the gas mileage in miles per gallon of model automobiles on a special test track. The pie chart below provides information about the country of manufacture of the model cars used by Consumers Union. (Click on the image for a larger view. ) (a) Based on this pie chart, we may conclude that. more than half of the cars in the study were from the United States.. Mercedes Benz, Audi, Porsche, and BMW represent approximately one quarter of the cars tested. C. Japanese cars get significantly lower gas mileage than cars of other countries. This is because their slice of the pie is at the bottom of the chart.. Swedish cars get gas mileages that are between those of Japanese and American cars. (b) A pie chart is equivalent to a. timeplot. histogram. C. scatter plot.. bar chart. 18. (1 pt) Data set A: Data set B: Data set C: 81,83,84,86,87,90 7,7,11,13,18,21 6,7,8,8,8,10 Above are three different data sets. Without calculating anything, decide which set A, B, or C has the smaller standard deviation. Just enter the letter of the data set as your answer. C

5 19. (1 pt) For each of the given the data sets below, calculate the mean, variance, and standard deviation. (a) 80, 51, 15, 5, 99, 89, 62, 21, 10 mean = standard deviation = (b) 55, 48, 46, 51, 40, 51 mean = standard deviation = (c) 4.1, 3.9, 2.3, 3.8, 2.6 mean = standard deviation = (1 pt) Consider the following data set. Find the mean and standard deviation. Data set: 74, 44, 62, 54, 85 Mean: Standard deviation: If the data value 63 was added to the set, would the standard deviation become larger (L) or smaller (S). You do not need to calculate this second standard deviation to answer this question. L or S: S 21. (1 pt) Consider the data set given below: 27, 31, 23, 52, 47, 41, 37, 14, 28, 23, 25 a)find the minimum value of the data set: b)find the maximum value of the data set: c)find the arithmetic mean of the data set: d)find the median of the data set: Let s include one more data point in the data set. Suppose this new data value lies between the values 14 and 52, inclusively. e)find the smallest possible value of the mean of the new data set: f)find the largest possible value of the mean of the new data set: g)find the smallest possible value of the median of the new data set: h)find the largest possible value of the median of the new data 5 set: (1 pt) Calculate the mean and median of the following grades on a math test: Mean = Median = 89, 82, 76, 73, 73, 72, 69, 69, 54, 40, 24 Is this data set skewed to the right, symmetric, or skewed to the left? (Enter SR, SYM, or SL); SL 23. (1 pt) Calculate the 5 number summary and the interquartile range of the following data: 44, 36, 28, 62, 39, 40, 69, 32, 22, 50, 46, 12, 37, 17, 54 Q1 = Q2 = Q3 = Min = Max = IQR = There is a potential outlier in this data set. False

6 . True (1 pt) Calculate the 5 number summary and the interquartile range of the following data: 40, 26, 60, 56, 34, 39, 12, 30, 31, 14, 38, 48, 72, 6, 42, 22 Q1 = Q2 = Q3 = Min = Max = IQR = There is a potential outlier in this data set. True. False (1 pt) Two six-sided dice are rolled (one red and one green). Some possibilities are (Red=1,Green=5) or (Red=2,Green=2) etc. (a) How many total possibilities are there? For the rest of the questions, we will assume that the dice are fair and that all of the possibilities in (a) are equally likely. 6 (b) What is the probability that the sum on the two dice comes out to be 10? (c) What is the probability that the sum on the two dice comes out to be 7? (d) What is the probability that the numbers on the two dice are equal? (1 pt) One die is rolled. List the outcomes comprising the following events: (make sure you use the correct notation with the set braces, put a comma between each outcome, and do not put a space between them): (a) event the die comes up 4 or more (b) event the die comes up even (c) event the die comes up 3 {4,5,6} {2,4,6} {3} 27. (1 pt) (Note that an Ace is considered a face card for this problem) In drawing a single card from a regular deck of 52 cards we have: (a) P( black or a face card ) = (b) P( Queen and a 3 ) = (c) P( black and a Queen ) = (d) P( face card or a number card ) = (e) P( black and a face card ) = 34/52 0/52 2/52 52/52 8/ (1 pt) Consider the experiment where a pair of fair dice is thrown. Let X denote the random variable whose value is determined by taking the maximum of the spots showing on either of the two dice thrown. For example, if a 3 and a 5 were thrown, then X would take the value of Maximum(3,5) = 5. The range of values that X can assume are the positive integers 1,2,3,4,5,6.

7 Please give the corresponding probabilities for the values of X given below. Pr(X = 1) = Pr(X = 2) = Pr(X = 3) = Pr(X = 4) = Pr(X = 5) = Pr(X = 6) = Further, find the probability that X is divisible by 3. Probability that X is divisible by 3 equals (1 pt) The boxplot below represents annual salaries of attorneys in thousands of dollars in Los Angeles. About what percentage of the attorneys have salaries between $155,000 and $299,000?. 40%. 75% C. 80%. None of the Above 30. (1 pt) Which of the following are true?. All the data values for boxplot D1 are greater than the median value for D2. 7. At least three quarters of the data values represented in D1 are greater than the median value of D3. C. At least one quarter of the data values for D3 are less than the median value for D2. The data represented in D2 is symmetric. E. The data for D1 has a greater median value than the data for D3. BCE 31. (1 pt) Harry tosses a nickel 4 times. The probability that he gets at least as many heads as tails is. Solution Notice that he can get 4 heads in just one way: namely HHHH. He can get 3 heads in four ways: HHHT (that is, a tail on his last toss), HHTH ( a tail on his next to last toss), HTHH, and THHH ; He can get 2 heads in 6 ways: HHTT, HTHT, HTTH, THHT, THTH, THHT, TTHH. Since there are 2 4 = 16 ordered ways that the nickel can land, the probability of at least two heads (which guarantees that he gets at least as many heads as tails) is = Another way of thinking of it is that after computing the number of ways of getting 4, 3, 2 heads, we know there are 5 ways that heads exceed tail and that means that there must be 5 ways that tails exceed heads so we don t really need to do anything more to know the denominator. 11/ (1 pt) A red die (sometimes called a number cube) and a blue die are tossed Determine the probability of the red die showing a 3 and the blue die showing a 4 as a reduced fraction. Solution The probability of the red die showing a 3 is 1 6 since the die has six faces and only one shows a 3. Similarly the probability of the blue die showing a 4 is 6 1. So the probability of both happening is = / (1 pt) If A and B are two mutually exclusive events with P(A) = 0.3 and P(B) = 0.6, find the following probabilities: a) P(A and B) = b) P(A or B) = c) P(not A) =

8 d) P(not B) = e) P(not (A or B)) = f) P(A and (not B)) = (1 pt) If P(A) = 0.7, P(B) = 0.45 and P(A and B) = 0.2, find the following probabilities: a) P(A or B) = b) P(not A) = c) P(not B) = d) P(A and (not B)) = e) P(not (A and B)) = (1 pt) The sample space for an experiment contains five sample points. The probabilities of the sample points are: P(1) = P(2) = 0.15 P(3) = P(4) = 0.2 P(5) = 0.3 Find the probability of each of the following events: A : { Either 3 or 5 occurs } B : { Either 3, 1, or 4 occurs } C : { 2 does not occur } P(A) = P(B) = P(C) = (1 pt) A fair coin is tossed three times and the events A, B, and C are defined as follows: A : { At least one head is observed } B : { At least two heads are observed } C : { The number of heads observed is odd } Find the following probabilities by summing the probabilities of the appropriate sample points: (a) P(A) = (b) P(A C) = (c) P(A B C) = Generated by c WeBWorK, Mathematical Association of America 8

Sem. 1 Review Ch. 1-3

Sem. 1 Review Ch. 1-3 AP Stats Sem. 1 Review Ch. 1-3 Name 1. You measure the age, marital status and earned income of an SRS of 1463 women. The number and type of variables you have measured is a. 1463; all quantitative. b.

More information

Chapter 01 : What is Statistics?

Chapter 01 : What is Statistics? Chapter 01 : What is Statistics? Feras Awad Data: The information coming from observations, counts, measurements, and responses. Statistics: The science of collecting, organizing, analyzing, and interpreting

More information

PROBABILITY THEORY. Prof. S. J. Soni. Assistant Professor Computer Engg. Department SPCE, Visnagar

PROBABILITY THEORY. Prof. S. J. Soni. Assistant Professor Computer Engg. Department SPCE, Visnagar PROBABILITY THEORY By Prof. S. J. Soni Assistant Professor Computer Engg. Department SPCE, Visnagar Introduction Signals whose values at any instant t are determined by their analytical or graphical description

More information

Chapters 1 & 2 Exam Review

Chapters 1 & 2 Exam Review Problems 1-3 refer to the following five boxplots. 1.) To which of the above boxplots does the following histogram correspond? (A) A (B) B (C) C (D) D (E) E 2.) To which of the above boxplots does the

More information

Math 140 Introductory Statistics

Math 140 Introductory Statistics Math 140 Introductory Statistics Professor Silvia Fernández Chapter 2 Based on the book Statistics in Action by A. Watkins, R. Scheaffer, and G. Cobb. Visualizing Distributions Recall the definition: The

More information

Math 140 Introductory Statistics

Math 140 Introductory Statistics Visualizing Distributions Math 140 Introductory Statistics Professor Silvia Fernández Chapter Based on the book Statistics in Action by A. Watkins, R. Scheaffer, and G. Cobb. Recall the definition: The

More information

Name: Exam 2 Solutions. March 13, 2017

Name: Exam 2 Solutions. March 13, 2017 Department of Mathematics University of Notre Dame Math 00 Finite Math Spring 07 Name: Instructors: Conant/Galvin Exam Solutions March, 07 This exam is in two parts on pages and contains problems worth

More information

3.2 Probability Rules

3.2 Probability Rules 3.2 Probability Rules The idea of probability rests on the fact that chance behavior is predictable in the long run. In the last section, we used simulation to imitate chance behavior. Do we always need

More information

1. Consider the independent events A and B. Given that P(B) = 2P(A), and P(A B) = 0.52, find P(B). (Total 7 marks)

1. Consider the independent events A and B. Given that P(B) = 2P(A), and P(A B) = 0.52, find P(B). (Total 7 marks) 1. Consider the independent events A and B. Given that P(B) = 2P(A), and P(A B) = 0.52, find P(B). (Total 7 marks) 2. In a school of 88 boys, 32 study economics (E), 28 study history (H) and 39 do not

More information

Event A: at least one tail observed A:

Event A: at least one tail observed A: Chapter 3 Probability 3.1 Events, sample space, and probability Basic definitions: An is an act of observation that leads to a single outcome that cannot be predicted with certainty. A (or simple event)

More information

Sets and Set notation. Algebra 2 Unit 8 Notes

Sets and Set notation. Algebra 2 Unit 8 Notes Sets and Set notation Section 11-2 Probability Experimental Probability experimental probability of an event: Theoretical Probability number of time the event occurs P(event) = number of trials Sample

More information

Statistics 100 Exam 2 March 8, 2017

Statistics 100 Exam 2 March 8, 2017 STAT 100 EXAM 2 Spring 2017 (This page is worth 1 point. Graded on writing your name and net id clearly and circling section.) PRINT NAME (Last name) (First name) net ID CIRCLE SECTION please! L1 (MWF

More information

Introduction to Probability, Fall 2009

Introduction to Probability, Fall 2009 Introduction to Probability, Fall 2009 Math 30530 Review questions for exam 1 solutions 1. Let A, B and C be events. Some of the following statements are always true, and some are not. For those that are

More information

Introduction to Statistics

Introduction to Statistics Introduction to Statistics Data and Statistics Data consists of information coming from observations, counts, measurements, or responses. Statistics is the science of collecting, organizing, analyzing,

More information

Math 243 Section 3.1 Introduction to Probability Lab

Math 243 Section 3.1 Introduction to Probability Lab Math 243 Section 3.1 Introduction to Probability Lab Overview Why Study Probability? Outcomes, Events, Sample Space, Trials Probabilities and Complements (not) Theoretical vs. Empirical Probability The

More information

Elementary Statistics

Elementary Statistics Elementary Statistics Q: What is data? Q: What does the data look like? Q: What conclusions can we draw from the data? Q: Where is the middle of the data? Q: Why is the spread of the data important? Q:

More information

Random variables (section 6.1)

Random variables (section 6.1) Random variables (section 6.1) random variable: a number attached to the outcome of a random process (r.v is usually denoted with upper case letter, such as \) discrete random variables discrete random

More information

STP 226 ELEMENTARY STATISTICS

STP 226 ELEMENTARY STATISTICS STP 226 ELEMENTARY STATISTICS CHAPTER 5 Probability Theory - science of uncertainty 5.1 Probability Basics Equal-Likelihood Model Suppose an experiment has N possible outcomes, all equally likely. Then

More information

Math 221, REVIEW, Instructor: Susan Sun Nunamaker

Math 221, REVIEW, Instructor: Susan Sun Nunamaker Math 221, REVIEW, Instructor: Susan Sun Nunamaker Good Luck & Contact me through through e-mail if you have any questions. 1. Bar graphs can only be vertical. a. true b. false 2.

More information

University of Jordan Fall 2009/2010 Department of Mathematics

University of Jordan Fall 2009/2010 Department of Mathematics handouts Part 1 (Chapter 1 - Chapter 5) University of Jordan Fall 009/010 Department of Mathematics Chapter 1 Introduction to Introduction; Some Basic Concepts Statistics is a science related to making

More information

Marquette University Executive MBA Program Statistics Review Class Notes Summer 2018

Marquette University Executive MBA Program Statistics Review Class Notes Summer 2018 Marquette University Executive MBA Program Statistics Review Class Notes Summer 2018 Chapter One: Data and Statistics Statistics A collection of procedures and principles

More information

AP Statistics Semester I Examination Section I Questions 1-30 Spend approximately 60 minutes on this part of the exam.

AP Statistics Semester I Examination Section I Questions 1-30 Spend approximately 60 minutes on this part of the exam. AP Statistics Semester I Examination Section I Questions 1-30 Spend approximately 60 minutes on this part of the exam. Name: Directions: The questions or incomplete statements below are each followed by

More information

Announcements. Lecture 5: Probability. Dangling threads from last week: Mean vs. median. Dangling threads from last week: Sampling bias

Announcements. Lecture 5: Probability. Dangling threads from last week: Mean vs. median. Dangling threads from last week: Sampling bias Recap Announcements Lecture 5: Statistics 101 Mine Çetinkaya-Rundel September 13, 2011 HW1 due TA hours Thursday - Sunday 4pm - 9pm at Old Chem 211A If you added the class last week please make sure to

More information

The point value of each problem is in the left-hand margin. You must show your work to receive any credit, except in problem 1. Work neatly.

The point value of each problem is in the left-hand margin. You must show your work to receive any credit, except in problem 1. Work neatly. Introduction to Statistics Math 1040 Sample Final Exam - Chapters 1-11 6 Problem Pages Time Limit: 1 hour and 50 minutes Open Textbook Calculator Allowed: Scientific Name: The point value of each problem

More information

Computations - Show all your work. (30 pts)

Computations - Show all your work. (30 pts) Math 1012 Final Name: Computations - Show all your work. (30 pts) 1. Fractions. a. 1 7 + 1 5 b. 12 5 5 9 c. 6 8 2 16 d. 1 6 + 2 5 + 3 4 2.a Powers of ten. i. 10 3 10 2 ii. 10 2 10 6 iii. 10 0 iv. (10 5

More information

MTH302 Quiz # 4. Solved By When a coin is tossed once, the probability of getting head is. Select correct option:

MTH302 Quiz # 4. Solved By When a coin is tossed once, the probability of getting head is. Select correct option: MTH302 Quiz # 4 Solved By konenuchiha@gmail.com When a coin is tossed once, the probability of getting head is. 0.55 0.52 0.50 (1/2) 0.51 Suppose the slope of regression line is 20 and the intercept is

More information

UNIT 5 ~ Probability: What Are the Chances? 1

UNIT 5 ~ Probability: What Are the Chances? 1 UNIT 5 ~ Probability: What Are the Chances? 1 6.1: Simulation Simulation: The of chance behavior, based on a that accurately reflects the phenomenon under consideration. (ex 1) Suppose we are interested

More information

MTH001- Elementary Mathematics Solved Final Term Papers For Final Term Exam Preparation

MTH001- Elementary Mathematics Solved Final Term Papers For Final Term Exam Preparation MTH001- Elementary Mathematics Solved Final Term Papers For Final Term Exam Preparation Question No: 1 The difference between the upper and the lower class boundaries of a class are known as: Class Marks

More information

Thus, P(F or L) = P(F) + P(L) - P(F & L) = = 0.553

Thus, P(F or L) = P(F) + P(L) - P(F & L) = = 0.553 Test 2 Review: Solutions 1) The following outcomes have at least one Head: HHH, HHT, HTH, HTT, THH, THT, TTH Thus, P(at least one head) = 7/8 2) The following outcomes have a sum of 9: (6,3), (5,4), (4,5),

More information

Topic 5 Basics of Probability

Topic 5 Basics of Probability Topic 5 Basics of Probability Equally Likely Outcomes and the Axioms of Probability 1 / 13 Outline Equally Likely Outcomes Axioms of Probability Consequences of the Axioms 2 / 13 Introduction A probability

More information

date: math analysis 2 chapter 18: curve fitting and models

date: math analysis 2 chapter 18: curve fitting and models name: period: date: math analysis 2 mr. mellina chapter 18: curve fitting and models Sections: 18.1 Introduction to Curve Fitting; the Least-Squares Line 18.2 Fitting Exponential Curves 18.3 Fitting Power

More information

Lecture Lecture 5

Lecture Lecture 5 Lecture 4 --- Lecture 5 A. Basic Concepts (4.1-4.2) 1. Experiment: A process of observing a phenomenon that has variation in its outcome. Examples: (E1). Rolling a die, (E2). Drawing a card form a shuffled

More information

CHAPTER 1. Introduction

CHAPTER 1. Introduction CHAPTER 1 Introduction Engineers and scientists are constantly exposed to collections of facts, or data. The discipline of statistics provides methods for organizing and summarizing data, and for drawing

More information

Math 10 - Compilation of Sample Exam Questions + Answers

Math 10 - Compilation of Sample Exam Questions + Answers Math 10 - Compilation of Sample Exam Questions + Sample Exam Question 1 We have a population of size N. Let p be the independent probability of a person in the population developing a disease. Answer the

More information

Data Presentation. Naureen Ghani. May 4, 2018

Data Presentation. Naureen Ghani. May 4, 2018 Data Presentation Naureen Ghani May 4, 2018 Data is only as good as how it is presented. How do you take hundreds or thousands of data points and create something a human can understand? This is a problem

More information

TOPIC 12 PROBABILITY SCHEMATIC DIAGRAM

TOPIC 12 PROBABILITY SCHEMATIC DIAGRAM TOPIC 12 PROBABILITY SCHEMATIC DIAGRAM Topic Concepts Degree of Importance References NCERT Book Vol. II Probability (i) Conditional Probability *** Article 1.2 and 1.2.1 Solved Examples 1 to 6 Q. Nos

More information

HW1 Solutions. October 5, (20 pts.) Random variables, sample space and events Consider the random experiment of ipping a coin 4 times.

HW1 Solutions. October 5, (20 pts.) Random variables, sample space and events Consider the random experiment of ipping a coin 4 times. HW1 Solutions October 5, 2016 1. (20 pts.) Random variables, sample space and events Consider the random experiment of ipping a coin 4 times. 1. (2 pts.) Dene the appropriate random variables. Answer:

More information

CHAPTER - 16 PROBABILITY Random Experiment : If an experiment has more than one possible out come and it is not possible to predict the outcome in advance then experiment is called random experiment. Sample

More information

Chapter 6 Assessment. 3. Which points in the data set below are outliers? Multiple Choice. 1. The boxplot summarizes the test scores of a math class?

Chapter 6 Assessment. 3. Which points in the data set below are outliers? Multiple Choice. 1. The boxplot summarizes the test scores of a math class? Chapter Assessment Multiple Choice 1. The boxplot summarizes the test scores of a math class? Test Scores 3. Which points in the data set below are outliers? 73, 73, 7, 75, 75, 75, 77, 77, 77, 77, 7, 7,

More information

1.3.1 Measuring Center: The Mean

1.3.1 Measuring Center: The Mean 1.3.1 Measuring Center: The Mean Mean - The arithmetic average. To find the mean (pronounced x bar) of a set of observations, add their values and divide by the number of observations. If the n observations

More information

What is statistics? Statistics is the science of: Collecting information. Organizing and summarizing the information collected

What is statistics? Statistics is the science of: Collecting information. Organizing and summarizing the information collected What is statistics? Statistics is the science of: Collecting information Organizing and summarizing the information collected Analyzing the information collected in order to draw conclusions Two types

More information

Lesson One Hundred and Sixty-One Normal Distribution for some Resolution

Lesson One Hundred and Sixty-One Normal Distribution for some Resolution STUDENT MANUAL ALGEBRA II / LESSON 161 Lesson One Hundred and Sixty-One Normal Distribution for some Resolution Today we re going to continue looking at data sets and how they can be represented in different

More information

MATH STUDENT BOOK. 12th Grade Unit 9

MATH STUDENT BOOK. 12th Grade Unit 9 MATH STUDENT BOOK 12th Grade Unit 9 Unit 9 COUNTING PRINCIPLES MATH 1209 COUNTING PRINCIPLES INTRODUCTION 1. PROBABILITY DEFINITIONS, SAMPLE SPACES, AND PROBABILITY ADDITION OF PROBABILITIES 11 MULTIPLICATION

More information

Chapter 5, 6 and 7: Review Questions: STAT/MATH Consider the experiment of rolling a fair die twice. Find the indicated probabilities.

Chapter 5, 6 and 7: Review Questions: STAT/MATH Consider the experiment of rolling a fair die twice. Find the indicated probabilities. Chapter5 Chapter 5, 6 and 7: Review Questions: STAT/MATH3379 1. Consider the experiment of rolling a fair die twice. Find the indicated probabilities. (a) One of the dice is a 4. (b) Sum of the dice equals

More information

(a) Fill in the missing probabilities in the table. (b) Calculate P(F G). (c) Calculate P(E c ). (d) Is this a uniform sample space?

(a) Fill in the missing probabilities in the table. (b) Calculate P(F G). (c) Calculate P(E c ). (d) Is this a uniform sample space? Math 166 Exam 1 Review Sections L.1-L.2, 1.1-1.7 Note: This review is more heavily weighted on the new material this week: Sections 1.5-1.7. For more practice problems on previous material, take a look

More information

The area under a probability density curve between any two values a and b has two interpretations:

The area under a probability density curve between any two values a and b has two interpretations: Chapter 7 7.1 The Standard Normal Curve Introduction Probability density curve: The area under a probability density curve between any two values a and b has two interpretations: 1. 2. The region above

More information

Stochastic processes and stopping time Exercises

Stochastic processes and stopping time Exercises Stochastic processes and stopping time Exercises Exercise 2.1. Today is Monday and you have one dollar in your piggy bank. Starting tomorrow, every morning until Friday (inclusively), you toss a coin.

More information

AP Final Review II Exploring Data (20% 30%)

AP Final Review II Exploring Data (20% 30%) AP Final Review II Exploring Data (20% 30%) Quantitative vs Categorical Variables Quantitative variables are numerical values for which arithmetic operations such as means make sense. It is usually a measure

More information

Histograms allow a visual interpretation

Histograms allow a visual interpretation Chapter 4: Displaying and Summarizing i Quantitative Data s allow a visual interpretation of quantitative (numerical) data by indicating the number of data points that lie within a range of values, called

More information

Chapter # classifications of unlikely, likely, or very likely to describe possible buying of a product?

Chapter # classifications of unlikely, likely, or very likely to describe possible buying of a product? A. Attribute data B. Numerical data C. Quantitative data D. Sample data E. Qualitative data F. Statistic G. Parameter Chapter #1 Match the following descriptions with the best term or classification given

More information

Discrete Mathematics and Probability Theory Spring 2016 Rao and Walrand Note 16. Random Variables: Distribution and Expectation

Discrete Mathematics and Probability Theory Spring 2016 Rao and Walrand Note 16. Random Variables: Distribution and Expectation CS 70 Discrete Mathematics and Probability Theory Spring 206 Rao and Walrand Note 6 Random Variables: Distribution and Expectation Example: Coin Flips Recall our setup of a probabilistic experiment as

More information

dates given in your syllabus.

dates given in your syllabus. Slide 2-1 For exams (MD1, MD2, and Final): You may bring one 8.5 by 11 sheet of paper with formulas and notes written or typed on both sides to each exam. For the rest of the quizzes, you will take your

More information

Chapter 2: Tools for Exploring Univariate Data

Chapter 2: Tools for Exploring Univariate Data Stats 11 (Fall 2004) Lecture Note Introduction to Statistical Methods for Business and Economics Instructor: Hongquan Xu Chapter 2: Tools for Exploring Univariate Data Section 2.1: Introduction What is

More information

Problem # Number of points 1 /20 2 /20 3 /20 4 /20 5 /20 6 /20 7 /20 8 /20 Total /150

Problem # Number of points 1 /20 2 /20 3 /20 4 /20 5 /20 6 /20 7 /20 8 /20 Total /150 Name Student ID # Instructor: SOLUTION Sergey Kirshner STAT 516 Fall 09 Practice Midterm #1 January 31, 2010 You are not allowed to use books or notes. Non-programmable non-graphic calculators are permitted.

More information

MIDTERM EXAMINATION (Spring 2011) STA301- Statistics and Probability

MIDTERM EXAMINATION (Spring 2011) STA301- Statistics and Probability STA301- Statistics and Probability Solved MCQS From Midterm Papers March 19,2012 MC100401285 Moaaz.pk@gmail.com Mc100401285@gmail.com PSMD01 MIDTERM EXAMINATION (Spring 2011) STA301- Statistics and Probability

More information

Random processes. Lecture 17: Probability, Part 1. Probability. Law of large numbers

Random processes. Lecture 17: Probability, Part 1. Probability. Law of large numbers Random processes Lecture 17: Probability, Part 1 Statistics 10 Colin Rundel March 26, 2012 A random process is a situation in which we know what outcomes could happen, but we don t know which particular

More information

Summarizing and Displaying Measurement Data/Understanding and Comparing Distributions

Summarizing and Displaying Measurement Data/Understanding and Comparing Distributions Summarizing and Displaying Measurement Data/Understanding and Comparing Distributions Histograms, Mean, Median, Five-Number Summary and Boxplots, Standard Deviation Thought Questions 1. If you were to

More information

SESSION 5 Descriptive Statistics

SESSION 5 Descriptive Statistics SESSION 5 Descriptive Statistics Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple

More information

Resistant Measure - A statistic that is not affected very much by extreme observations.

Resistant Measure - A statistic that is not affected very much by extreme observations. Chapter 1.3 Lecture Notes & Examples Section 1.3 Describing Quantitative Data with Numbers (pp. 50-74) 1.3.1 Measuring Center: The Mean Mean - The arithmetic average. To find the mean (pronounced x bar)

More information

Describing distributions with numbers

Describing distributions with numbers Describing distributions with numbers A large number or numerical methods are available for describing quantitative data sets. Most of these methods measure one of two data characteristics: The central

More information

The probability of an event is viewed as a numerical measure of the chance that the event will occur.

The probability of an event is viewed as a numerical measure of the chance that the event will occur. Chapter 5 This chapter introduces probability to quantify randomness. Section 5.1: How Can Probability Quantify Randomness? The probability of an event is viewed as a numerical measure of the chance that

More information

Outline. Probability. Math 143. Department of Mathematics and Statistics Calvin College. Spring 2010

Outline. Probability. Math 143. Department of Mathematics and Statistics Calvin College. Spring 2010 Outline Math 143 Department of Mathematics and Statistics Calvin College Spring 2010 Outline Outline 1 Review Basics Random Variables Mean, Variance and Standard Deviation of Random Variables 2 More Review

More information

4.2 Probability Models

4.2 Probability Models 4.2 Probability Models Ulrich Hoensch Tuesday, February 19, 2013 Sample Spaces Examples 1. When tossing a coin, the sample space is S = {H, T }, where H = heads, T = tails. 2. When randomly selecting a

More information

Topic 5: Probability. 5.4 Combined Events and Conditional Probability Paper 1

Topic 5: Probability. 5.4 Combined Events and Conditional Probability Paper 1 Topic 5: Probability Standard Level 5.4 Combined Events and Conditional Probability Paper 1 1. In a group of 16 students, 12 take art and 8 take music. One student takes neither art nor music. The Venn

More information

3.1 Measure of Center

3.1 Measure of Center 3.1 Measure of Center Calculate the mean for a given data set Find the median, and describe why the median is sometimes preferable to the mean Find the mode of a data set Describe how skewness affects

More information

$ and det A = 14, find the possible values of p. 1. If A =! # Use your graph to answer parts (i) (iii) below, Working:

$ and det A = 14, find the possible values of p. 1. If A =! # Use your graph to answer parts (i) (iii) below, Working: & 2 p 3 1. If A =! # $ and det A = 14, find the possible values of p. % 4 p p" Use your graph to answer parts (i) (iii) below, (i) Find an estimate for the median score. (ii) Candidates who scored less

More information

Chapter 5 : Probability. Exercise Sheet. SHilal. 1 P a g e

Chapter 5 : Probability. Exercise Sheet. SHilal. 1 P a g e 1 P a g e experiment ( observing / measuring ) outcomes = results sample space = set of all outcomes events = subset of outcomes If we collect all outcomes we are forming a sample space If we collect some

More information

Chapter. Probability

Chapter. Probability Chapter 3 Probability Section 3.1 Basic Concepts of Probability Section 3.1 Objectives Identify the sample space of a probability experiment Identify simple events Use the Fundamental Counting Principle

More information

Unit 4 Probability. Dr Mahmoud Alhussami

Unit 4 Probability. Dr Mahmoud Alhussami Unit 4 Probability Dr Mahmoud Alhussami Probability Probability theory developed from the study of games of chance like dice and cards. A process like flipping a coin, rolling a die or drawing a card from

More information

Statistics for Managers using Microsoft Excel 6 th Edition

Statistics for Managers using Microsoft Excel 6 th Edition Statistics for Managers using Microsoft Excel 6 th Edition Chapter 3 Numerical Descriptive Measures 3-1 Learning Objectives In this chapter, you learn: To describe the properties of central tendency, variation,

More information

Sections OPIM 303, Managerial Statistics H Guy Williams, 2006

Sections OPIM 303, Managerial Statistics H Guy Williams, 2006 Sections 3.1 3.5 The three major properties which describe a set of data: Central Tendency Variation Shape OPIM 303 Lecture 3 Page 1 Most sets of data show a distinct tendency to group or cluster around

More information

CHAPTER 4 PROBABILITY AND PROBABILITY DISTRIBUTIONS

CHAPTER 4 PROBABILITY AND PROBABILITY DISTRIBUTIONS CHAPTER 4 PROBABILITY AND PROBABILITY DISTRIBUTIONS 4.2 Events and Sample Space De nition 1. An experiment is the process by which an observation (or measurement) is obtained Examples 1. 1: Tossing a pair

More information

Math 140 Introductory Statistics

Math 140 Introductory Statistics Math 140 Introductory Statistics 5.1 Models of random behavior Outcome: Result or answer obtained from a chance process. Event: Collection of outcomes. Probability: Number between 0 and 1 (0% and 100%).

More information

DSST Principles of Statistics

DSST Principles of Statistics DSST Principles of Statistics Time 10 Minutes 98 Questions Each incomplete statement is followed by four suggested completions. Select the one that is best in each case. 1. Which of the following variables

More information

Example 2. Given the data below, complete the chart:

Example 2. Given the data below, complete the chart: Statistics 2035 Quiz 1 Solutions Example 1. 2 64 150 150 2 128 150 2 256 150 8 8 Example 2. Given the data below, complete the chart: 52.4, 68.1, 66.5, 75.0, 60.5, 78.8, 63.5, 48.9, 81.3 n=9 The data is

More information

Monty Hall Puzzle. Draw a tree diagram of possible choices (a possibility tree ) One for each strategy switch or no-switch

Monty Hall Puzzle. Draw a tree diagram of possible choices (a possibility tree ) One for each strategy switch or no-switch Monty Hall Puzzle Example: You are asked to select one of the three doors to open. There is a large prize behind one of the doors and if you select that door, you win the prize. After you select a door,

More information

AMS7: WEEK 2. CLASS 2

AMS7: WEEK 2. CLASS 2 AMS7: WEEK 2. CLASS 2 Introduction to Probability. Probability Rules. Independence and Conditional Probability. Bayes Theorem. Risk and Odds Ratio Friday April 10, 2015 Probability: Introduction Probability:

More information

*Karle Laska s Sections: There is no class tomorrow and Friday! Have a good weekend! Scores will be posted in Compass early Friday morning

*Karle Laska s Sections: There is no class tomorrow and Friday! Have a good weekend! Scores will be posted in Compass early Friday morning STATISTICS 100 EXAM 3 Spring 2016 PRINT NAME (Last name) (First name) *NETID CIRCLE SECTION: Laska MWF L1 Laska Tues/Thurs L2 Robin Tu Write answers in appropriate blanks. When no blanks are provided CIRCLE

More information

Further Mathematics 2018 CORE: Data analysis Chapter 2 Summarising numerical data

Further Mathematics 2018 CORE: Data analysis Chapter 2 Summarising numerical data Chapter 2: Summarising numerical data Further Mathematics 2018 CORE: Data analysis Chapter 2 Summarising numerical data Extract from Study Design Key knowledge Types of data: categorical (nominal and ordinal)

More information

STAT 101 Notes. Introduction to Statistics

STAT 101 Notes. Introduction to Statistics STAT 101 Notes Introduction to Statistics September 2017 CONTENTS 1 Introduction 1 1.1 Data........................................................ 2 1.2 Tabular, graphical and numerical summaries...............................

More information

Describing distributions with numbers

Describing distributions with numbers Describing distributions with numbers A large number or numerical methods are available for describing quantitative data sets. Most of these methods measure one of two data characteristics: The central

More information

Section 4.2 Basic Concepts of Probability

Section 4.2 Basic Concepts of Probability Section 4.2 Basic Concepts of Probability 2012 Pearson Education, Inc. All rights reserved. 1 of 88 Section 4.2 Objectives Identify the sample space of a probability experiment Identify simple events Use

More information

Independence 1 2 P(H) = 1 4. On the other hand = P(F ) =

Independence 1 2 P(H) = 1 4. On the other hand = P(F ) = Independence Previously we considered the following experiment: A card is drawn at random from a standard deck of cards. Let H be the event that a heart is drawn, let R be the event that a red card is

More information

Lecture notes for probability. Math 124

Lecture notes for probability. Math 124 Lecture notes for probability Math 124 What is probability? Probabilities are ratios, expressed as fractions, decimals, or percents, determined by considering results or outcomes of experiments whose result

More information

Math 2000 Practice Final Exam: Homework problems to review. Problem numbers

Math 2000 Practice Final Exam: Homework problems to review. Problem numbers Math 2000 Practice Final Exam: Homework problems to review Pages: Problem numbers 52 20 65 1 181 14 189 23, 30 245 56 256 13 280 4, 15 301 21 315 18 379 14 388 13 441 13 450 10 461 1 553 13, 16 561 13,

More information

Statistics 1. Edexcel Notes S1. Mathematical Model. A mathematical model is a simplification of a real world problem.

Statistics 1. Edexcel Notes S1. Mathematical Model. A mathematical model is a simplification of a real world problem. Statistics 1 Mathematical Model A mathematical model is a simplification of a real world problem. 1. A real world problem is observed. 2. A mathematical model is thought up. 3. The model is used to make

More information

Instructor: Doug Ensley Course: MAT Applied Statistics - Ensley

Instructor: Doug Ensley Course: MAT Applied Statistics - Ensley Student: Date: Instructor: Doug Ensley Course: MAT117 01 Applied Statistics - Ensley Assignment: Online 04 - Sections 2.5 and 2.6 1. A travel magazine recently presented data on the annual number of vacation

More information

MATH1231 Algebra, 2017 Chapter 9: Probability and Statistics

MATH1231 Algebra, 2017 Chapter 9: Probability and Statistics MATH1231 Algebra, 2017 Chapter 9: Probability and Statistics A/Prof. Daniel Chan School of Mathematics and Statistics University of New South Wales danielc@unsw.edu.au Daniel Chan (UNSW) MATH1231 Algebra

More information

A is one of the categories into which qualitative data can be classified.

A is one of the categories into which qualitative data can be classified. Chapter 2 Methods for Describing Sets of Data 2.1 Describing qualitative data Recall qualitative data: non-numerical or categorical data Basic definitions: A is one of the categories into which qualitative

More information

SS257a Midterm Exam Monday Oct 27 th 2008, 6:30-9:30 PM Talbot College 342 and 343. You may use simple, non-programmable scientific calculators.

SS257a Midterm Exam Monday Oct 27 th 2008, 6:30-9:30 PM Talbot College 342 and 343. You may use simple, non-programmable scientific calculators. SS657a Midterm Exam, October 7 th 008 pg. SS57a Midterm Exam Monday Oct 7 th 008, 6:30-9:30 PM Talbot College 34 and 343 You may use simple, non-programmable scientific calculators. This exam has 5 questions

More information

LC OL - Statistics. Types of Data

LC OL - Statistics. Types of Data LC OL - Statistics Types of Data Question 1 Characterise each of the following variables as numerical or categorical. In each case, list any three possible values for the variable. (i) Eye colours in a

More information

University of California, Berkeley, Statistics 131A: Statistical Inference for the Social and Life Sciences. Michael Lugo, Spring 2012

University of California, Berkeley, Statistics 131A: Statistical Inference for the Social and Life Sciences. Michael Lugo, Spring 2012 University of California, Berkeley, Statistics 3A: Statistical Inference for the Social and Life Sciences Michael Lugo, Spring 202 Solutions to Exam Friday, March 2, 202. [5: 2+2+] Consider the stemplot

More information

F71SM STATISTICAL METHODS

F71SM STATISTICAL METHODS F71SM STATISTICAL METHODS RJG SUMMARY NOTES 2 PROBABILITY 2.1 Introduction A random experiment is an experiment which is repeatable under identical conditions, and for which, at each repetition, the outcome

More information

Introduction to Statistics

Introduction to Statistics Why Statistics? Introduction to Statistics To develop an appreciation for variability and how it effects products and processes. Study methods that can be used to help solve problems, build knowledge and

More information

PRECALCULUS SEM. 1 REVIEW ( ) (additional copies available online!) Use the given functions to find solutions to problems 1 6.

PRECALCULUS SEM. 1 REVIEW ( ) (additional copies available online!) Use the given functions to find solutions to problems 1 6. PRECALCULUS SEM. 1 REVIEW (2011 2012) (additional copies available online!) Name: Period: Unit 1: Functions *** No Calculators!!**** Use the given functions to find solutions to problems 1 6. f (x) = x

More information

Math P (A 1 ) =.5, P (A 2 ) =.6, P (A 1 A 2 ) =.9r

Math P (A 1 ) =.5, P (A 2 ) =.6, P (A 1 A 2 ) =.9r Math 3070 1. Treibergs σιι First Midterm Exam Name: SAMPLE January 31, 2000 (1. Compute the sample mean x and sample standard deviation s for the January mean temperatures (in F for Seattle from 1900 to

More information

M 140 Test 1 B Name (1 point) SHOW YOUR WORK FOR FULL CREDIT! Problem Max. Points Your Points Total 75

M 140 Test 1 B Name (1 point) SHOW YOUR WORK FOR FULL CREDIT! Problem Max. Points Your Points Total 75 M 140 est 1 B Name (1 point) SHOW YOUR WORK FOR FULL CREDI! Problem Max. Points Your Points 1-10 10 11 10 12 3 13 4 14 18 15 8 16 7 17 14 otal 75 Multiple choice questions (1 point each) For questions

More information

( ) P A B : Probability of A given B. Probability that A happens

( ) P A B : Probability of A given B. Probability that A happens A B A or B One or the other or both occurs At least one of A or B occurs Probability Review A B A and B Both A and B occur ( ) P A B : Probability of A given B. Probability that A happens given that B

More information

Example. What is the sample space for flipping a fair coin? Rolling a 6-sided die? Find the event E where E = {x x has exactly one head}

Example. What is the sample space for flipping a fair coin? Rolling a 6-sided die? Find the event E where E = {x x has exactly one head} Chapter 7 Notes 1 (c) Epstein, 2013 CHAPTER 7: PROBABILITY 7.1: Experiments, Sample Spaces and Events Chapter 7 Notes 2 (c) Epstein, 2013 What is the sample space for flipping a fair coin three times?

More information

Correlation Coefficient: the quantity, measures the strength and direction of a linear relationship between 2 variables.

Correlation Coefficient: the quantity, measures the strength and direction of a linear relationship between 2 variables. AFM Unit 9 Regression Day 1 notes A mathematical model is an equation that best describes a particular set of paired data. These mathematical models are referred to as models and are used to one variable

More information