Math 1342 Test 2 Review. Total number of students = = Students between the age of 26 and 35 = = 2012
|
|
- Jeremy Waters
- 5 years ago
- Views:
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)
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 informationCumulative 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 informationDescribing 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 informationDiscrete 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 informationChapter 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 informationTopic 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 informationMath 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 informationDescribing 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 information4.2 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 informationFinal 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 informationThe 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 informationMean/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 informationPage 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 informationQuestion. 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 informationChapter 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 informationSTATISTICS. 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 informationThus, 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 informationIB 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 informationCentral 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 informationFREQUENCY 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 informationMeasures 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 informationIB 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 informationLecture 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 informationChapter 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 informationTeaching 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 informationSTAT/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 informationIntroduction 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 information6.2A 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 informationFRANKLIN 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 informationThe 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 informationSTATISTICS/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 informationPRACTICE 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 informationMath 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 informationAlgebra 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 information1-1. 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 informationReview 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 informationChapter 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 informationContinuous 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 informationChapter 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 informationH2 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 informationSampling 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 informationNumber 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 information6 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 informationDescriptive 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 information1. 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 informationEssential 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 informationUnit 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 informationStat 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 informationDescribing 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 informationDensity 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 informationLearning 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 informationNumber 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 informationUseful 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 informationChapter (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 informationFinal 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 informationAnswers 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 informationCS 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 informationDover- 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 informationSection 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 informationTopic 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: [ 2] ST301(AKI) Mid1 2010/10/07 Choose one answer for each question.
More informationThe 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 informationProbability 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 informationTesting 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 informationDescriptive 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 informationMath 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 informationMath 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 informationHistograms. 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 informationCHAPTER 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 informationREVIEW: 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 informationReview. 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 informationDensity 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 information7.1 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 informationLecture 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 informationChapter 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 informationTest 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 informationSome 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 informationCounting 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 informationLecture 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 informationSection 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 informationRecall 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 informationIn 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
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 informationAP 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 informationAP 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 informationPercentile: 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 informationArkansas 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 informationMath 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 informationMath 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 informationClassroom 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 informationContinuous 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 informationF78SC2 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 informationAlgebra 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 informationMacomb 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 informationChapter 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 informationare 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 informationSlide 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 informationCumulative 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 informationØ 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 informationa) 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