Math 1342 Test 2 Review. Total number of students = = Students between the age of 26 and 35 = = 2012

Size: px
Start display at page:

Download "Math 1342 Test 2 Review. Total number of students = = Students between the age of 26 and 35 = = 2012"

Transcription

1 Math 1342 Test 2 Review 4) Total number of students = = 6397 Students between the age of 26 and 35 = = 2012 Students who are NOT between the age of 26 and 35 = = 4385 Therefore, the number of outcomes the comprise the event (not A) = ) Total number of students = = 6397 Students under the age of 31 = = 5363 Students NOT under the age of 31 = = 1084 Therefore, the number of outcomes the comprise the event (not A) = 1084

2

3

4 Computational tool at

5 Not: Histogram was constructed with tool at

6 14) Since the professor gives each student 10 minutes, "To wait no longer than 20 minutes" means that there must be no more than 2 students already waiting to see the professor. Therefore, P("Student has to wait no longer than 20 minutes") = P("No more than 2 students are already waiting") = P(X 2) = P(X = 0) + P(X=1) + P(X=2) = = ) Since the professor gives each student 10 minutes, "To wait at least 30 minutes" means that there must be at least 3 students already waiting to see the professor. Therefore, P("Student has to wait at least 30 minutes ") = P(at least 3 students are already waiting to see the professor) = P(X 3) = P(X = 3) + P(X=4) + P(X=5) = = ) "everyone will have a place to sit at our next party" means that number of people at the party must be less than or equal to 8. Therefore, P( "everyone will have a place to sit at our next party") = P(number of people at the party must less than or equal to 8) = P(X 8) = P(X = 5) + P(X + 6) + P(X = 7) + P(X = 8) = = 0.45

7 Computational Tool at

8

9

10

11

12 26) Computational Tool at

13 27) Computational Tool at Therefore, area to the left of 1.13 =

14 28) Computational Tool at

15 29) Computational Tool at

16 30) Computational Tool at

17 31) Computational Tool at

18 32) Computational Tool at Therefore, z-score = 1.75

19 33) Computational Tool at Therefore, z-score = -0.25

20 34) Computational Tool at Therefore, z-score = -1.34

21 35) Computational Tool at P(X < 53) means find area to the left of a score of 53. Therefore, P(X < 53) = area to the left of a score of 53 = = 4.01%

22 36) Computational Tool at P(X > 16.1) means find area to the right of a score of Therefore, P(X > 16.1) = area to the right of a score of 16.1 = = 15.87%

23 37) Computational Tool at P(19.7 < X < 25.3) means find area between the scores of 19.7 and Therefore, P(19.7 < X < 25.3) = area between the scores of 19.7 and 25.3 = = 74.6%

24 38) Q1 mean first quartile or 25th percentile. To find the first quartile Q1 means finding a score such that 25% of all observations are less than this score. Hence, we need to find score corresponding to a left-tailed area of 25% or 0.25.

25 39) Q3 mean third quartile or 75th percentile. To find the third quartile Q3 means finding a score such that 75% of all observations are less than this score. Hence, we need to find score corresponding to a left-tailed area of 75% or 0.75.

26 40) Q1 mean first quartile or 25th percentile. To find the first quartile Q1 means finding a score such that 25% of all observations are less than this score. Hence, we need to find score corresponding to a left-tailed area of 25% or 0.25.

27 Hence, we need to find score corresponding to a left-tailed area of 20% or 0.20.

28 42) Q3 mean third quartile or 75th percentile. To find the third quartile Q3 means finding a score such that 75% of all observations are less than this score. Hence, we need to find score corresponding to a left-tailed area of 75% or 0.75.

29

30

31

32

(a) Find the value of x. (4) Write down the standard deviation. (2) (Total 6 marks)

(a) Find the value of x. (4) Write down the standard deviation. (2) (Total 6 marks) 1. The following frequency distribution of marks has mean 4.5. Mark 1 2 3 4 5 6 7 Frequency 2 4 6 9 x 9 4 Find the value of x. (4) Write down the standard deviation. (Total 6 marks) 2. The following table

More information

Cumulative Frequency & Frequency Density

Cumulative Frequency & Frequency Density For more awesome GCSE and A level resources, visit us at www.savemyexams.co.uk Frequency & Frequency Density Diagrams Question Paper 2 Level IGCSE Subject Maths (0580) Exam Board Cambridge International

More information

Describing Distributions With Numbers

Describing Distributions With Numbers Describing Distributions With Numbers October 24, 2012 What Do We Usually Summarize? Measures of Center. Percentiles. Measures of Spread. A Summary Statement. Choosing Numerical Summaries. 1.0 What Do

More information

Discrete and continuous

Discrete and continuous Discrete and continuous A curve, or a function, or a range of values of a variable, is discrete if it has gaps in it - it jumps from one value to another. In practice in S2 discrete variables are variables

More information

Chapter 1 - Lecture 3 Measures of Location

Chapter 1 - Lecture 3 Measures of Location Chapter 1 - Lecture 3 of Location August 31st, 2009 Chapter 1 - Lecture 3 of Location General Types of measures Median Skewness Chapter 1 - Lecture 3 of Location Outline General Types of measures What

More information

Topic 5: Statistics 5.3 Cumulative Frequency Paper 1

Topic 5: Statistics 5.3 Cumulative Frequency Paper 1 Topic 5: Statistics 5.3 Cumulative Frequency Paper 1 1. The following is a cumulative frequency diagram for the time t, in minutes, taken by students to complete a task. Standard Level Write down the median.

More information

Math 2311 Sections 4.1, 4.2 and 4.3

Math 2311 Sections 4.1, 4.2 and 4.3 Math 2311 Sections 4.1, 4.2 and 4.3 4.1 - Density Curves What do we know about density curves? Example: Suppose we have a density curve defined for defined by the line y = x. Sketch: What percent of observations

More information

Describing Distributions

Describing Distributions Describing Distributions With Numbers April 18, 2012 Summary Statistics. Measures of Center. Percentiles. Measures of Spread. A Summary Statement. Choosing Numerical Summaries. 1.0 What Are Summary Statistics?

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

Final Exam STAT On a Pareto chart, the frequency should be represented on the A) X-axis B) regression C) Y-axis D) none of the above

Final Exam STAT On a Pareto chart, the frequency should be represented on the A) X-axis B) regression C) Y-axis D) none of the above King Abdul Aziz University Faculty of Sciences Statistics Department Final Exam STAT 0 First Term 49-430 A 40 Name No ID: Section: You have 40 questions in 9 pages. You have 90 minutes to solve the exam.

More information

The Central Limit Theorem

The Central Limit Theorem - The Central Limit Theorem Definition Sampling Distribution of the Mean the probability distribution of sample means, with all samples having the same sample size n. (In general, the sampling distribution

More information

Mean/Modal Class Grouped Data

Mean/Modal Class Grouped Data For more awesome GCSE and A level resources, visit us at www.savemyexams.co.uk Mean/Modal Class Grouped Data Question Paper 1 Level IGCSE Subject Maths (58) Exam Board Cambridge International Examinations

More information

Page 312, Exercise 50

Page 312, Exercise 50 Millersville University Name Answer Key Department of Mathematics MATH 130, Elements of Statistics I, Homework 4 November 5, 2009 Page 312, Exercise 50 Simulation According to the U.S. National Center

More information

Question. z-scores. What We Will Cover in This Section. On which of the following tests did Pat do best compared to the other students?

Question. z-scores. What We Will Cover in This Section. On which of the following tests did Pat do best compared to the other students? z-scores 9/17/2003 P225 Z-scores 1 What We Will Cover in This Section What a z-score is. Computation. Properties. Assumptions. Uses 9/17/2003 P225 Z-scores 2 Question On which of the following tests did

More information

Chapter 3. Measuring data

Chapter 3. Measuring data Chapter 3 Measuring data 1 Measuring data versus presenting data We present data to help us draw meaning from it But pictures of data are subjective They re also not susceptible to rigorous inference Measuring

More information

STATISTICS. 1. Measures of Central Tendency

STATISTICS. 1. Measures of Central Tendency STATISTICS 1. Measures o Central Tendency Mode, median and mean For a sample o discrete data, the mode is the observation, x with the highest requency,. 1 N F For grouped data in a cumulative requency

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

IB MATH SL Test Review 2.1

IB MATH SL Test Review 2.1 Name IB MATH SL Test Review 2.1 Date 1. A student measured the diameters of 80 snail shells. His results are shown in the following cumulative frequency graph. The lower quartile (LQ) is 14 mm and is marked

More information

Central Limit Theorem for Averages

Central Limit Theorem for Averages Last Name First Name Class Time Chapter 7-1 Central Limit Theorem for Averages Suppose that we are taking samples of size n items from a large population with mean and standard deviation. Each sample taken

More information

FREQUENCY DISTRIBUTIONS AND PERCENTILES

FREQUENCY DISTRIBUTIONS AND PERCENTILES FREQUENCY DISTRIBUTIONS AND PERCENTILES New Statistical Notation Frequency (f): the number of times a score occurs N: sample size Simple Frequency Distributions Raw Scores The scores that we have directly

More information

Measures of the Location of the Data

Measures of the Location of the Data Measures of the Location of the Data 1. 5. Mark has 51 films in his collection. Each movie comes with a rating on a scale from 0.0 to 10.0. The following table displays the ratings of the aforementioned

More information

IB Questionbank Mathematical Studies 3rd edition. Grouped discrete. 184 min 183 marks

IB Questionbank Mathematical Studies 3rd edition. Grouped discrete. 184 min 183 marks IB Questionbank Mathematical Studies 3rd edition Grouped discrete 184 min 183 marks 1. The weights in kg, of 80 adult males, were collected and are summarized in the box and whisker plot shown below. Write

More information

Lecture 10: The Normal Distribution. So far all the random variables have been discrete.

Lecture 10: The Normal Distribution. So far all the random variables have been discrete. Lecture 10: The Normal Distribution 1. Continuous Random Variables So far all the random variables have been discrete. We need a different type of model (called a probability density function) for continuous

More information

Chapter 3 Probability Distributions and Statistics Section 3.1 Random Variables and Histograms

Chapter 3 Probability Distributions and Statistics Section 3.1 Random Variables and Histograms Math 166 (c)2013 Epstein Chapter 3 Page 1 Chapter 3 Probability Distributions and Statistics Section 3.1 Random Variables and Histograms The value of the result of the probability experiment is called

More information

Teaching a Prestatistics Course: Propelling Non-STEM Students Forward

Teaching a Prestatistics Course: Propelling Non-STEM Students Forward Teaching a Prestatistics Course: Propelling Non-STEM Students Forward Jay Lehmann College of San Mateo MathNerdJay@aol.com www.pearsonhighered.com/lehmannseries Learning Is in the Details Detailing concepts

More information

STAT/SOC/CSSS 221 Statistical Concepts and Methods for the Social Sciences. Random Variables

STAT/SOC/CSSS 221 Statistical Concepts and Methods for the Social Sciences. Random Variables STAT/SOC/CSSS 221 Statistical Concepts and Methods for the Social Sciences Random Variables Christopher Adolph Department of Political Science and Center for Statistics and the Social Sciences University

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

6.2A Linear Transformations

6.2A Linear Transformations 6.2 Transforming and Combining Random Variables 6.2A Linear Transformations El Dorado Community College considers a student to be full time if he or she is taking between 12 and 18 credits. The number

More information

FRANKLIN UNIVERSITY PROFICIENCY EXAM (FUPE) STUDY GUIDE

FRANKLIN UNIVERSITY PROFICIENCY EXAM (FUPE) STUDY GUIDE FRANKLIN UNIVERSITY PROFICIENCY EXAM (FUPE) STUDY GUIDE Course Title: Probability and Statistics (MATH 80) Recommended Textbook(s): Number & Type of Questions: Probability and Statistics for Engineers

More information

The Normal Distribution. Chapter 6

The Normal Distribution. Chapter 6 + The Normal Distribution Chapter 6 + Applications of the Normal Distribution Section 6-2 + The Standard Normal Distribution and Practical Applications! We can convert any variable that in normally distributed

More information

STATISTICS/MATH /1760 SHANNON MYERS

STATISTICS/MATH /1760 SHANNON MYERS STATISTICS/MATH 103 11/1760 SHANNON MYERS π 100 POINTS POSSIBLE π YOUR WORK MUST SUPPORT YOUR ANSWER FOR FULL CREDIT TO BE AWARDED π YOU MAY USE A SCIENTIFIC AND/OR A TI-83/84/85/86 CALCULATOR ONCE YOU

More information

PRACTICE WORKSHEET FOR MA3ENA EXAM

PRACTICE WORKSHEET FOR MA3ENA EXAM PRACTICE WORKSHEET FOR MA3ENA EXAM What you definitely need to know: - definition of an arithmetic and geometric sequence - a formula for the general term (u n ) of each of these sequences - a formula

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

Algebra Calculator Skills Inventory Solutions

Algebra Calculator Skills Inventory Solutions Algebra Calculator Skills Inventory Solutions 1. The equation P = 1.25x 15 represents the profit in dollars when x widgets are sold. Find the profit if 450 widgets are sold. A. $427.50 B. $697.50 C. $562.50

More information

1-1. Chapter 1. Sampling and Descriptive Statistics by The McGraw-Hill Companies, Inc. All rights reserved.

1-1. Chapter 1. Sampling and Descriptive Statistics by The McGraw-Hill Companies, Inc. All rights reserved. 1-1 Chapter 1 Sampling and Descriptive Statistics 1-2 Why Statistics? Deal with uncertainty in repeated scientific measurements Draw conclusions from data Design valid experiments and draw reliable conclusions

More information

Review for Exam #1. Chapter 1. The Nature of Data. Definitions. Population. Sample. Quantitative data. Qualitative (attribute) data

Review for Exam #1. Chapter 1. The Nature of Data. Definitions. Population. Sample. Quantitative data. Qualitative (attribute) data Review for Exam #1 1 Chapter 1 Population the complete collection of elements (scores, people, measurements, etc.) to be studied Sample a subcollection of elements drawn from a population 11 The Nature

More information

Chapter 6 Group Activity - SOLUTIONS

Chapter 6 Group Activity - SOLUTIONS Chapter 6 Group Activity - SOLUTIONS Group Activity Summarizing a Distribution 1. The following data are the number of credit hours taken by Math 105 students during a summer term. You will be analyzing

More information

Continuous random variables

Continuous random variables Continuous random variables A continuous random variable X takes all values in an interval of numbers. The probability distribution of X is described by a density curve. The total area under a density

More information

Chapter 6 The Normal Distribution

Chapter 6 The Normal Distribution Chapter 6 The Normal PSY 395 Oswald Outline s and area The normal distribution The standard normal distribution Setting probable limits on a score/observation Measures related to 2 s and Area The idea

More information

H2 Mathematics Probability ( )

H2 Mathematics Probability ( ) H2 Mathematics Probability (208 209) Practice Questions. For events A and B it is given that P(A) 0.7, P(B) 0. and P(A B 0 )0.8. Find (i) P(A \ B 0 ), [2] (ii) P(A [ B), [2] (iii) P(B 0 A). [2] For a third

More information

Sampling WITHOUT replacement, Order IS important Number of Samples = 6

Sampling WITHOUT replacement, Order IS important Number of Samples = 6 : Different strategies sampling 2 out of numbers {1,2,3}: Sampling WITHOUT replacement, Order IS important Number of Samples = 6 (1,2) (1,3) (2,1) (2,3) (3,1) (3,2) : Different strategies sampling 2 out

More information

Number of people in family Frequency

Number of people in family Frequency 1) 40 students are asked about the number of people in their families. The table shows the results. Number of people in family 2 3 4 5 6 7 Frequency 1 1 17 12 6 3 (a) Find (i) the mode, (ii) the median,

More information

6 THE NORMAL DISTRIBUTION

6 THE NORMAL DISTRIBUTION CHAPTER 6 THE NORMAL DISTRIBUTION 341 6 THE NORMAL DISTRIBUTION Figure 6.1 If you ask enough people about their shoe size, you will find that your graphed data is shaped like a bell curve and can be described

More information

Descriptive Statistics Class Practice [133 marks]

Descriptive Statistics Class Practice [133 marks] Descriptive Statistics Class Practice [133 marks] The weekly wages (in dollars) of 80 employees are displayed in the cumulative frequency curve below. 1a. (i) (ii) Write down the median weekly wage. Find

More information

1. I had a computer generate the following 19 numbers between 0-1. Were these numbers randomly selected?

1. I had a computer generate the following 19 numbers between 0-1. Were these numbers randomly selected? Activity #10: Continuous Distributions Uniform, Exponential, Normal) 1. I had a computer generate the following 19 numbers between 0-1. Were these numbers randomly selected? 0.12374454, 0.19609266, 0.44248450,

More information

Essential Question: How are the mean and the standard deviation determined from a discrete probability distribution?

Essential Question: How are the mean and the standard deviation determined from a discrete probability distribution? Probability and Statistics The Binomial Probability Distribution and Related Topics Chapter 5 Section 1 Introduction to Random Variables and Probability Distributions Essential Question: How are the mean

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

Stat 2300 International, Fall 2006 Sample Midterm. Friday, October 20, Your Name: A Number:

Stat 2300 International, Fall 2006 Sample Midterm. Friday, October 20, Your Name: A Number: Stat 2300 International, Fall 2006 Sample Midterm Friday, October 20, 2006 Your Name: A Number: The Midterm consists of 35 questions: 20 multiple-choice questions (with exactly 1 correct answer) and 15

More information

Describing Distributions With Numbers Chapter 12

Describing Distributions With Numbers Chapter 12 Describing Distributions With Numbers Chapter 12 May 1, 2013 What Do We Usually Summarize? Measures of Center. Percentiles. Measures of Spread. A Summary. 1.0 What Do We Usually Summarize? source: Prof.

More information

Density curves and the normal distribution

Density curves and the normal distribution Density curves and the normal distribution - Imagine what would happen if we measured a variable X repeatedly and make a histogram of the values. What shape would emerge? A mathematical model of this shape

More information

Learning Plan 09. Question 1. Question 2. Question 3. Question 4. What is the difference between the highest and lowest data values in a data set?

Learning Plan 09. Question 1. Question 2. Question 3. Question 4. What is the difference between the highest and lowest data values in a data set? Learning Plan 09 Question 1 What is the difference between the highest and lowest data values in a data set? The difference is called range. (p. 794) Question 2 Measures of Dispersion. Read the answer

More information

Number of fillings Frequency q 4 1. (a) Find the value of q. (2)

Number of fillings Frequency q 4 1. (a) Find the value of q. (2) 1. The table below shows the frequency distribution of the number of dental fillings for a group of 25 children. Number of fillings 0 1 2 3 4 5 Frequency 4 3 8 q 4 1 Find the value of q. Use your graphic

More information

Useful for Multiplication Rule: When two events, A and B, are independent, P(A and B) = P(A) P(B).

Useful for Multiplication Rule: When two events, A and B, are independent, P(A and B) = P(A) P(B). Probability Independence Last time: Two events are indpt if knowing that one did or did not happen tells you nothing about whether the other will or will not. It doesn't change the probability. Example:

More information

Chapter (4) Discrete Probability Distributions Examples

Chapter (4) Discrete Probability Distributions Examples Chapter (4) Discrete Probability Distributions Examples Example () Two balanced dice are rolled. Let X be the sum of the two dice. Obtain the probability distribution of X. Solution When the two balanced

More information

Final Exam Review (Math 1342)

Final Exam Review (Math 1342) Final Exam Review (Math 1342) 1) 5.5 5.7 5.8 5.9 6.1 6.1 6.3 6.4 6.5 6.6 6.7 6.7 6.7 6.9 7.0 7.0 7.0 7.1 7.2 7.2 7.4 7.5 7.7 7.7 7.8 8.0 8.1 8.1 8.3 8.7 Min = 5.5 Q 1 = 25th percentile = middle of first

More information

Answers Part A. P(x = 67) = 0, because x is a continuous random variable. 2. Find the following probabilities:

Answers Part A. P(x = 67) = 0, because x is a continuous random variable. 2. Find the following probabilities: Answers Part A 1. Woman s heights are normally distributed with a mean of 63.6 inches and a standard deviation of 2.5 inches. Find the probability that a single randomly selected woman will be 67 inches

More information

CS 147: Computer Systems Performance Analysis

CS 147: Computer Systems Performance Analysis CS 147: Computer Systems Performance Analysis Summarizing Variability and Determining Distributions CS 147: Computer Systems Performance Analysis Summarizing Variability and Determining Distributions 1

More information

Dover- Sherborn High School Mathematics Curriculum Probability and Statistics

Dover- Sherborn High School Mathematics Curriculum Probability and Statistics Mathematics Curriculum A. DESCRIPTION This is a full year courses designed to introduce students to the basic elements of statistics and probability. Emphasis is placed on understanding terminology and

More information

Section 3.2 Measures of Central Tendency

Section 3.2 Measures of Central Tendency Section 3.2 Measures of Central Tendency 1 of 149 Section 3.2 Objectives Determine the mean, median, and mode of a population and of a sample Determine the weighted mean of a data set and the mean of a

More information

Topic 2 Part 3 [189 marks]

Topic 2 Part 3 [189 marks] Topic 2 Part 3 [189 marks] The grades obtained by a group of 13 students are listed below. 5 3 6 5 7 3 2 6 4 6 6 6 4 1a. Write down the modal grade. Find the mean grade. 1b. Write down the standard deviation.

More information

[ 1] ST301(AKI) Mid1 2010/10/07. ST 301 (AKI) Mid 1 PLEASE DO NOT OPEN YET! TURN OFF YOUR CELL PHONE! FIRST NAME: LAST NAME: STUDENT ID:

[ 1] ST301(AKI) Mid1 2010/10/07. ST 301 (AKI) Mid 1 PLEASE DO NOT OPEN YET! TURN OFF YOUR CELL PHONE! FIRST NAME: LAST NAME: STUDENT ID: [ 1] ST301(AKI) Mid1 2010/10/07 ST 301 (AKI) Mid 1 PLEASE DO NOT OPEN YET! TURN OFF YOUR CELL PHONE! FIRST NAME: LAST NAME: STUDENT ID: [ 2] ST301(AKI) Mid1 2010/10/07 Choose one answer for each question.

More information

The empirical ( ) rule

The empirical ( ) rule The empirical (68-95-99.7) rule With a bell shaped distribution, about 68% of the data fall within a distance of 1 standard deviation from the mean. 95% fall within 2 standard deviations of the mean. 99.7%

More information

Probability theory and mathematical statistics:

Probability theory and mathematical statistics: N.I. Lobachevsky State University of Nizhni Novgorod Probability theory and mathematical statistics: Geometric probability Practice Associate Professor A.V. Zorine Geometric probability Practice 1 / 7

More information

Testing a Claim about the Difference in 2 Population Means Independent Samples. (there is no difference in Population Means µ 1 µ 2 = 0) against

Testing a Claim about the Difference in 2 Population Means Independent Samples. (there is no difference in Population Means µ 1 µ 2 = 0) against Section 9 2A Lecture Testing a Claim about the Difference i Population Means Independent Samples Test H 0 : µ 1 = µ 2 (there is no difference in Population Means µ 1 µ 2 = 0) against H 1 : µ 1 > µ 2 or

More information

Descriptive Statistics and Probability Test Review Test on May 4/5

Descriptive Statistics and Probability Test Review Test on May 4/5 Descriptive Statistics and Probability Test Review Test on May 4/5 1. The following frequency distribution of marks has mean 4.5. Mark 1 2 3 4 5 6 7 Frequency 2 4 6 9 x 9 4 Find the value of x. Write down

More information

Math 1120 Solutions to Review for the Third Exam Spring 2011

Math 1120 Solutions to Review for the Third Exam Spring 2011 Math 20 Solutions to Review for the Third Exam Spring 20. Calculate the mean, median and mode for each of the following data sets. (a) 4, 8, 3, 3, 5, 3, 5, 7,, 9, 0, 2 First, order the set: 0,, 2, 3, 3,

More information

Math 416 Lecture 2 DEFINITION. Here are the multivariate versions: X, Y, Z iff P(X = x, Y = y, Z =z) = p(x, y, z) of X, Y, Z iff for all sets A, B, C,

Math 416 Lecture 2 DEFINITION. Here are the multivariate versions: X, Y, Z iff P(X = x, Y = y, Z =z) = p(x, y, z) of X, Y, Z iff for all sets A, B, C, Math 416 Lecture 2 DEFINITION. Here are the multivariate versions: PMF case: p(x, y, z) is the joint Probability Mass Function of X, Y, Z iff P(X = x, Y = y, Z =z) = p(x, y, z) PDF case: f(x, y, z) is

More information

Histograms. Mark Scheme. Save My Exams! The Home of Revision For more awesome GCSE and A level resources, visit us at

Histograms. Mark Scheme. Save My Exams! The Home of Revision For more awesome GCSE and A level resources, visit us at Save My Exams! The Home of Revision For more awesome GCSE and A level resources, visit us at www.savemyexams.co.uk/ Histograms Mark Scheme Level Subject Exam Board Topic Sub Topic Booklet IGCSE Maths Edexcel

More information

CHAPTER 5: EXPLORING DATA DISTRIBUTIONS. Individuals are the objects described by a set of data. These individuals may be people, animals or things.

CHAPTER 5: EXPLORING DATA DISTRIBUTIONS. Individuals are the objects described by a set of data. These individuals may be people, animals or things. (c) Epstein 2013 Chapter 5: Exploring Data Distributions Page 1 CHAPTER 5: EXPLORING DATA DISTRIBUTIONS 5.1 Creating Histograms Individuals are the objects described by a set of data. These individuals

More information

REVIEW: Midterm Exam. Spring 2012

REVIEW: Midterm Exam. Spring 2012 REVIEW: Midterm Exam Spring 2012 Introduction Important Definitions: - Data - Statistics - A Population - A census - A sample Types of Data Parameter (Describing a characteristic of the Population) Statistic

More information

Review. Midterm Exam. Midterm Review. May 6th, 2015 AMS-UCSC. Spring Session 1 (Midterm Review) AMS-5 May 6th, / 24

Review. Midterm Exam. Midterm Review. May 6th, 2015 AMS-UCSC. Spring Session 1 (Midterm Review) AMS-5 May 6th, / 24 Midterm Exam Midterm Review AMS-UCSC May 6th, 2015 Spring 2015. Session 1 (Midterm Review) AMS-5 May 6th, 2015 1 / 24 Topics Topics We will talk about... 1 Review Spring 2015. Session 1 (Midterm Review)

More information

Density Curves & Normal Distributions

Density Curves & Normal Distributions Density Curves & Normal Distributions Sections 4.1 & 4.2 Cathy Poliak, Ph.D. cathy@math.uh.edu Office in Fleming 11c Department of Mathematics University of Houston Lecture 9-2311 Cathy Poliak, Ph.D. cathy@math.uh.edu

More information

7.1 Sampling Error The Need for Sampling Distributions

7.1 Sampling Error The Need for Sampling Distributions 7.1 Sampling Error The Need for Sampling Distributions Tom Lewis Fall Term 2009 Tom Lewis () 7.1 Sampling Error The Need for Sampling Distributions Fall Term 2009 1 / 5 Outline 1 Tom Lewis () 7.1 Sampling

More information

Lecture 6: Chapter 4, Section 2 Quantitative Variables (Displays, Begin Summaries)

Lecture 6: Chapter 4, Section 2 Quantitative Variables (Displays, Begin Summaries) Lecture 6: Chapter 4, Section 2 Quantitative Variables (Displays, Begin Summaries) Summarize with Shape, Center, Spread Displays: Stemplots, Histograms Five Number Summary, Outliers, Boxplots Cengage Learning

More information

Chapter 6 The Standard Deviation as a Ruler and the Normal Model

Chapter 6 The Standard Deviation as a Ruler and the Normal Model Chapter 6 The Standard Deviation as a Ruler and the Normal Model Overview Key Concepts Understand how adding (subtracting) a constant or multiplying (dividing) by a constant changes the center and/or spread

More information

Test 3 SOLUTIONS. x P(x) xp(x)

Test 3 SOLUTIONS. x P(x) xp(x) 16 1. A couple of weeks ago in class, each of you took three quizzes where you randomly guessed the answers to each question. There were eight questions on each quiz, and four possible answers to each

More information

Some Basic Concepts of Probability and Information Theory: Pt. 1

Some Basic Concepts of Probability and Information Theory: Pt. 1 Some Basic Concepts of Probability and Information Theory: Pt. 1 PHYS 476Q - Southern Illinois University January 18, 2018 PHYS 476Q - Southern Illinois University Some Basic Concepts of Probability and

More information

Counting principles, including permutations and combinations.

Counting principles, including permutations and combinations. 1 Counting principles, including permutations and combinations. The binomial theorem: expansion of a + b n, n ε N. THE PRODUCT RULE If there are m different ways of performing an operation and for each

More information

Lecture 3. Measures of Relative Standing and. Exploratory Data Analysis (EDA)

Lecture 3. Measures of Relative Standing and. Exploratory Data Analysis (EDA) Lecture 3. Measures of Relative Standing and Exploratory Data Analysis (EDA) Problem: The average weekly sales of a small company are $10,000 with a standard deviation of $450. This week their sales were

More information

Section 5.1: Probability and area

Section 5.1: Probability and area Section 5.1: Probability and area Review Normal Distribution s z = x - m s Standard Normal Distribution s=1 m x m=0 z The area that falls in the interval under the nonstandard normal curve is the same

More information

Recall that the standard deviation σ of a numerical data set is given by

Recall that the standard deviation σ of a numerical data set is given by 11.1 Using Normal Distributions Essential Question In a normal distribution, about what percent of the data lies within one, two, and three standard deviations of the mean? Recall that the standard deviation

More information

In this chapter, you will study the normal distribution, the standard normal, and applications associated with them.

In this chapter, you will study the normal distribution, the standard normal, and applications associated with them. The Normal Distribution The normal distribution is the most important of all the distributions. It is widely used and even more widely abused. Its graph is bell-shaped. You see the bell curve in almost

More information

+ Check for Understanding

+ Check for Understanding n Measuring Position: Percentiles n One way to describe the location of a value in a distribution is to tell what percent of observations are less than it. Definition: The p th percentile of a distribution

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

AP STATISTICS: Summer Math Packet

AP STATISTICS: Summer Math Packet Name AP STATISTICS: Summer Math Packet DIRECTIONS: Complete all problems on this packet. Packet due by the end of the first week of classes. Attach additional paper if needed. Calculator may be used. 1.

More information

Percentile: Formula: To find the percentile rank of a score, x, out of a set of n scores, where x is included:

Percentile: Formula: To find the percentile rank of a score, x, out of a set of n scores, where x is included: AP Statistics Chapter 2 Notes 2.1 Describing Location in a Distribution Percentile: The pth percentile of a distribution is the value with p percent of the observations (If your test score places you in

More information

Arkansas Tech University MATH 3513: Applied Statistics I Dr. Marcel B. Finan

Arkansas Tech University MATH 3513: Applied Statistics I Dr. Marcel B. Finan 2.4 Random Variables Arkansas Tech University MATH 3513: Applied Statistics I Dr. Marcel B. Finan By definition, a random variable X is a function with domain the sample space and range a subset of 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

Classroom Activity 7 Math 113 Name : 10 pts Intro to Applied Stats

Classroom Activity 7 Math 113 Name : 10 pts Intro to Applied Stats Classroom Activity 7 Math 113 Name : 10 pts Intro to Applied Stats Materials Needed: Bags of popcorn, watch with second hand or microwave with digital timer. Instructions: Follow the instructions on the

More information

Continuous Distributions

Continuous Distributions Inferential Statistics and Probability a Holistic Approach Chapter 6 Continuous Random Variables This Course Material by Maurice Geraghty is licensed under a Creative Commons Attribution-ShareAlike 4.0

More information

F78SC2 Notes 2 RJRC. If the interest rate is 5%, we substitute x = 0.05 in the formula. This gives

F78SC2 Notes 2 RJRC. If the interest rate is 5%, we substitute x = 0.05 in the formula. This gives F78SC2 Notes 2 RJRC Algebra It is useful to use letters to represent numbers. We can use the rules of arithmetic to manipulate the formula and just substitute in the numbers at the end. Example: 100 invested

More information

Algebra 1: Spring Semester Review

Algebra 1: Spring Semester Review Class: Date: Algebra 1: Spring Semester Review What is the solution of the system? Use a graph. 1. y = x + 2 y = 3x 1 a. c. b. d. 2. 4x + 3y = 12 2x + 3y = 18 3. y = x + 5 y = 5x 1 4. 5x + 4y = 9 4x +

More information

Macomb Community College Department of Mathematics. Review for the Math 1340 Final Exam

Macomb Community College Department of Mathematics. Review for the Math 1340 Final Exam Macomb Community College Department of Mathematics Review for the Math 0 Final Exam WINTER 0 MATH 0 Practice Final Exam WI0 Math0PF/lm Page of MATH 0 Practice Final Exam MATH 0 DEPARTMENT REVIEW FOR THE

More information

Chapter 2 Solutions Page 15 of 28

Chapter 2 Solutions Page 15 of 28 Chapter Solutions Page 15 of 8.50 a. The median is 55. The mean is about 105. b. The median is a more representative average" than the median here. Notice in the stem-and-leaf plot on p.3 of the text that

More information

are the objects described by a set of data. They may be people, animals or things.

are the objects described by a set of data. They may be people, animals or things. ( c ) E p s t e i n, C a r t e r a n d B o l l i n g e r 2016 C h a p t e r 5 : E x p l o r i n g D a t a : D i s t r i b u t i o n s P a g e 1 CHAPTER 5: EXPLORING DATA DISTRIBUTIONS 5.1 Creating Histograms

More information

Slide 1. Slide 2. Slide 3. Pick a Brick. Daphne. 400 pts 200 pts 300 pts 500 pts 100 pts. 300 pts. 300 pts 400 pts 100 pts 400 pts.

Slide 1. Slide 2. Slide 3. Pick a Brick. Daphne. 400 pts 200 pts 300 pts 500 pts 100 pts. 300 pts. 300 pts 400 pts 100 pts 400 pts. Slide 1 Slide 2 Daphne Phillip Kathy Slide 3 Pick a Brick 100 pts 200 pts 500 pts 300 pts 400 pts 200 pts 300 pts 500 pts 100 pts 300 pts 400 pts 100 pts 400 pts 100 pts 200 pts 500 pts 100 pts 400 pts

More information

Cumulative Frequency.

Cumulative Frequency. Frequency www.q8maths.com 9 17 2 15 1 5 1 2 3 4 5 Time (seconds) 6 7 8 9 1 2 students take a reaction time test. The cumulative diagram shows the results. Find (a) the median, Answer(a)... s [1] (b) the

More information

Ø Set of mutually exclusive categories. Ø Classify or categorize subject. Ø No meaningful order to categorization.

Ø Set of mutually exclusive categories. Ø Classify or categorize subject. Ø No meaningful order to categorization. Statistical Tools in Evaluation HPS 41 Fall 213 Dr. Joe G. Schmalfeldt Types of Scores Continuous Scores scores with a potentially infinite number of values. Discrete Scores scores limited to a specific

More information

a) The runner completes his next 1500 meter race in under 4 minutes: <

a) The runner completes his next 1500 meter race in under 4 minutes: < I. Let X be the time it takes a runner to complete a 1500 meter race. It is known that for this specific runner, the random variable X has a normal distribution with mean μ = 250.0 seconds and standard

More information