Chapter 7 Assignment SOLUTIONS WOMEN: Plus, add your pulse rate to the histogram.
|
|
- May Nicholson
- 6 years ago
- Views:
Transcription
1 Instructor: Linda C. Stephenson WOMEN: Plus, add your pulse rate to the histogram.
2 Instructor: Linda C. Stephenson MEN: Plus, add your pulse rate to the histogram.
3 1a. For z = -1.17: P (below) = b. For z = 0.29: P(below) = P(above) = = c. For z = 0.44: P(below) = For z = 0.58: P(below) = P(between) = =
4 1d. For z = 0.86: P(below) = For z = 1.72: P(below) = P(above) = = P(total) = = For area below = 0.28: z = (closest area in table is ) 3. For area below = 0.225: z = 0.76 (closest area in table is ) Using symmetry, the positive z is: z = = 0.45, divide that equally between the two tails, therefore on each side.
5 4. Does the STATDISK histogram indicate that a normal distribution could be used as a model for the variable? Yes (yes or no) List the mean : Men: , Women: (bpm) List the standard deviation : Men: , Women: (bpm) List your pulse rate: (bpm) 4a. Minimum usual value = Men: 46.92, Women: (bpm) Maximum usual value = Men: 92.24, Women: (bpm) 4b. Men: Based on the result in part a, would a man with a pulse rate of 95 bpm be considered unusual? Explain why or why not. Women: Based on the result in part a, would a woman with a pulse rate of 95 bpm be considered unusual? Explain why or why not. Men: Yes, it would be unusual, because 95 is greater than the max usual. Women: No, it would NOT be unusual, because 95 is less than the max usual. 4c. z = P(below) = P(above) = =
6 z = P(below) = P(above) = = d. z65 = P(below) = z95 = P(below) = P(between) = =
7 z65 = P(below) = z95 = P(below) = P(between) = = e. For area below = 0.30: z = (closest area in table = ) = (-0.52)( ) = bpm For area below = 0.30: z = (closest area in table = ) = (-0.52)( ) = bpm
8 4f. For area below = 0.15: z = 1.04 (closest area in table = ) = 0.30, divide that equally between the two tails, therefore 0.15 on each side. = (-1.04)( ) = bpm The symmetric z- score on the top half is 1.04: = (1.04)( ) = bpm The interval is from 57.8 to 81.4 bpm.
9 For area below = 0.15: z = 1.04 (closest area in table = ) = (-1.04)( ) = bpm The symmetric z- score on the top half is 1.04: = (1.04)( ) = bpm 4g. The interval is from 61.0 to 87.1 bpm. Calculate your z- score, and find the area below it from the table. The area below it will correspond to the percentile. Example: my pulse rate was z90 = P(below) = 0.898, x100 to get to %. Therefore, I m in about the 90 th percentile. See example to left. Guys, you need to use the men s mean and standard deviation. Therefore, my pulse rate was in the 90 th percentile, because the area below was about 90%.
10 4h. Unusual or not? Explain. Because this is a normal distribution, you can use either the Empirical Rule or the probabilities. Using the Empirical Rule, you already calculated the minimum and maximum usual values above. If your pulse is less than the minimum, or greater than the maximum, then it would be considered unusual. Using the probabilities rule, if your percentile is < 5% or > 95%, it would be considered unusual.
Chapter 7 Assignment SOLUTIONS WOMEN:
SOLUTIONS WOMEN: MEN: 1a. For z -0.79: P (below) 0.2148 1b. For z 1.46: 0.9279 P(above) 1 0.9279 0.0721 1c. For z 1.23: 0.1093 For z 1.65: 0.9505 P(between) 0.9505 0.1093 0.8412 1d. For z 0.71: 0.2389
More informationChapter 7 Assignment due Wednesday, May 24
due Wednesday, May 24 Calculating Probabilities for Normal Distributions Overview What you re going to do in this assignment is use an online applet to calculate: probabilities associated with given -scores
More informationCh6: The Normal Distribution
Ch6: The Normal Distribution Introduction Review: A continuous random variable can assume any value between two endpoints. Many continuous random variables have an approximately normal distribution, which
More informationThe Normal Distribution & z-scores
& z-scores Distributions: Who needs them? Why are we interested in distributions? Important link between distributions and probabilities of events If we know the distribution of a set of events, then we
More informationMath 14 Lecture Notes Ch. 6.1
6.1 Normal Distribution What is normal? a 10-year old boy that is 4' tall? 5' tall? 6' tall? a 25-year old woman with a shoe size of 5? 7? 9? an adult alligator that weighs 200 pounds? 500 pounds? 800
More informationMeasures of Position
Measures of Position In this section, we will learn to use fractiles. Fractiles are numbers that partition, or divide, an ordered data set into equal parts (each part has the same number of data entries).
More informationMAT 155. Z score. August 31, S3.4o3 Measures of Relative Standing and Boxplots
MAT 155 Dr. Claude Moore Cape Fear Community College Chapter 3 Statistics for Describing, Exploring, and Comparing Data 3 1 Review and Preview 3 2 Measures of Center 3 3 Measures of Variation 3 4 Measures
More informationThe Normal Distribution
The Normal Distribution Lecture 20 Section 6.3.1 Robb T. Koether Hampden-Sydney College Wed, Sep 28, 2011 Robb T. Koether (Hampden-Sydney College) The Normal Distribution Wed, Sep 28, 2011 1 / 41 Outline
More informationPrepare a stem-and-leaf graph for the following data. In your final display, you should arrange the leaves for each stem in increasing order.
Chapter 2 2.1 Descriptive Statistics A stem-and-leaf graph, also called a stemplot, allows for a nice overview of quantitative data without losing information on individual observations. It can be a good
More informationIT 403 Practice Problems (1-2) Answers
IT 403 Practice Problems (1-2) Answers #1. Using Tukey's Hinges method ('Inclusionary'), what is Q3 for this dataset? 2 3 5 7 11 13 17 a. 7 b. 11 c. 12 d. 15 c (12) #2. How do quartiles and percentiles
More informationIntroduction to the Practice of Statistics Fifth Edition Moore, McCabe
Introduction to the Practice of Statistics Fifth Edition Moore, McCabe Section 1.3 Homework Answers Assignment 5 1.80 If you ask a computer to generate "random numbers between 0 and 1, you uniform will
More informationappstats6.notebook September 27, 2016
Chapter 6 The Standard Deviation as a Ruler and the Normal Model Objectives: 1.Students will calculate and interpret z scores. 2.Students will compare/contrast values from different distributions using
More informationCHAPTER 2: DESCRIPTIVE STATISTICS Lecture Notes for Introductory Statistics 1. Daphne Skipper, Augusta University (2016)
CHAPTER 2: DESCRIPTIVE STATISTICS Lecture Notes for Introductory Statistics 1 Daphne Skipper, Augusta University (2016) 1. Stem-and-Leaf Graphs, Line Graphs, and Bar Graphs The distribution of data is
More informationLecture 6: Chapter 6 Summary
1 Lecture 6: Chapter 6 Summary Z-score: Is the distance of each data value from the mean in standard deviation Standardizes data values Standardization changes the mean and the standard deviation: o Z
More informationCHAPTER 2 DESCRIPTIVE STATISTICS
CHAPTER 2 DESCRIPTIVE STATISTICS 1. Stem-and-Leaf Graphs, Line Graphs, and Bar Graphs The distribution of data is how the data is spread or distributed over the range of the data values. This is one of
More informationProbability and Statistics. Copyright Cengage Learning. All rights reserved.
Probability and Statistics Copyright Cengage Learning. All rights reserved. 14.6 Descriptive Statistics (Graphical) Copyright Cengage Learning. All rights reserved. Objectives Data in Categories Histograms
More informationChapter 6: Continuous Random Variables & the Normal Distribution. 6.1 Continuous Probability Distribution
Chapter 6: Continuous Random Variables & the Normal Distribution 6.1 Continuous Probability Distribution and the Normal Probability Distribution 6.2 Standardizing a Normal Distribution 6.3 Applications
More informationLecture 3 Questions that we should be able to answer by the end of this lecture:
Lecture 3 Questions that we should be able to answer by the end of this lecture: Which is the better exam score? 67 on an exam with mean 50 and SD 10 or 62 on an exam with mean 40 and SD 12 Is it fair
More informationSection 10.4 Normal Distributions
Section 10.4 Normal Distributions Random Variables Suppose a bank is interested in improving its services to customers. The manager decides to begin by finding the amount of time tellers spend on each
More informationMath 120 Introduction to Statistics Mr. Toner s Lecture Notes 3.1 Measures of Central Tendency
Math 1 Introduction to Statistics Mr. Toner s Lecture Notes 3.1 Measures of Central Tendency lowest value + highest value midrange The word average: is very ambiguous and can actually refer to the mean,
More informationVocabulary. 5-number summary Rule. Area principle. Bar chart. Boxplot. Categorical data condition. Categorical variable.
5-number summary 68-95-99.7 Rule Area principle Bar chart Bimodal Boxplot Case Categorical data Categorical variable Center Changing center and spread Conditional distribution Context Contingency table
More information10.4 Measures of Central Tendency and Variation
10.4 Measures of Central Tendency and Variation Mode-->The number that occurs most frequently; there can be more than one mode ; if each number appears equally often, then there is no mode at all. (mode
More information10.4 Measures of Central Tendency and Variation
10.4 Measures of Central Tendency and Variation Mode-->The number that occurs most frequently; there can be more than one mode ; if each number appears equally often, then there is no mode at all. (mode
More informationThe Normal Distribution & z-scores
& z-scores Distributions: Who needs them? Why are we interested in distributions? Important link between distributions and probabilities of events If we know the distribution of a set of events, then we
More informationSections 4.3 and 4.4
Sections 4.3 and 4.4 Timothy Hanson Department of Statistics, University of South Carolina Stat 205: Elementary Statistics for the Biological and Life Sciences 1 / 32 4.3 Areas under normal densities Every
More informationConfidence Intervals: Estimators
Confidence Intervals: Estimators Point Estimate: a specific value at estimates a parameter e.g., best estimator of e population mean ( ) is a sample mean problem is at ere is no way to determine how close
More information4.3 The Normal Distribution
4.3 The Normal Distribution Objectives. Definition of normal distribution. Standard normal distribution. Specialties of the graph of the standard normal distribution. Percentiles of the standard normal
More information23.2 Normal Distributions
1_ Locker LESSON 23.2 Normal Distributions Common Core Math Standards The student is expected to: S-ID.4 Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate
More informationChapter 3 Analyzing Normal Quantitative Data
Chapter 3 Analyzing Normal Quantitative Data Introduction: In chapters 1 and 2, we focused on analyzing categorical data and exploring relationships between categorical data sets. We will now be doing
More informationThe Normal Distribution & z-scores
& z-scores Distributions: Who needs them? Why are we interested in distributions? Important link between distributions and probabilities of events If we know the distribution of a set of events, then we
More informationChapter 2 Modeling Distributions of Data
Chapter 2 Modeling Distributions of Data Section 2.1 Describing Location in a Distribution Describing Location in a Distribution Learning Objectives After this section, you should be able to: FIND and
More informationDensity Curve (p52) Density curve is a curve that - is always on or above the horizontal axis.
1.3 Density curves p50 Some times the overall pattern of a large number of observations is so regular that we can describe it by a smooth curve. It is easier to work with a smooth curve, because the histogram
More informationBIOL Gradation of a histogram (a) into the normal curve (b)
(التوزيع الطبيعي ( Distribution Normal (Gaussian) One of the most important distributions in statistics is a continuous distribution called the normal distribution or Gaussian distribution. Consider the
More informationAssignment 3 due Thursday Oct. 11
Instructor Linda C. Stephenson due Thursday Oct. 11 GENERAL NOTE: These assignments often build on each other what you learn in one assignment may be carried over to subsequent assignments. If I have already
More informationMeasures of Central Tendency. A measure of central tendency is a value used to represent the typical or average value in a data set.
Measures of Central Tendency A measure of central tendency is a value used to represent the typical or average value in a data set. The Mean the sum of all data values divided by the number of values in
More informationUnit 8: Normal Calculations
Unit 8: Normal Calculations Prerequisites This unit requires familiarity with basic facts about normal distributions, which are covered in Unit 7, Normal Curves. In addition, students need some background
More information4.2 Data Distributions
NOTES Data Distribution: Write your questions here! Dotplots Histograms Find the mean number of siblings: Find the median number of siblings: Types of distributions: The mean on the move: Compare the mean
More informationThe main issue is that the mean and standard deviations are not accurate and should not be used in the analysis. Then what statistics should we use?
Chapter 4 Analyzing Skewed Quantitative Data Introduction: In chapter 3, we focused on analyzing bell shaped (normal) data, but many data sets are not bell shaped. How do we analyze quantitative data when
More informationMAT 102 Introduction to Statistics Chapter 6. Chapter 6 Continuous Probability Distributions and the Normal Distribution
MAT 102 Introduction to Statistics Chapter 6 Chapter 6 Continuous Probability Distributions and the Normal Distribution 6.2 Continuous Probability Distributions Characteristics of a Continuous Probability
More informationCHAPTER 2 Modeling Distributions of Data
CHAPTER 2 Modeling Distributions of Data 2.2 Density Curves and Normal Distributions The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers Density Curves
More informationChapter 3 - Displaying and Summarizing Quantitative Data
Chapter 3 - Displaying and Summarizing Quantitative Data 3.1 Graphs for Quantitative Data (LABEL GRAPHS) August 25, 2014 Histogram (p. 44) - Graph that uses bars to represent different frequencies or relative
More informationLecture Slides. Elementary Statistics Twelfth Edition. by Mario F. Triola. and the Triola Statistics Series. Section 6.2-1
Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series by Mario F. Triola Section 6.2-1 Chapter 6 Normal Probability Distributions 6-1 Review and Preview 6-2 The Standard
More informationDistributions of random variables
Chapter 3 Distributions of random variables 31 Normal distribution Among all the distributions we see in practice, one is overwhelmingly the most common The symmetric, unimodal, bell curve is ubiquitous
More informationLecture 3 Questions that we should be able to answer by the end of this lecture:
Lecture 3 Questions that we should be able to answer by the end of this lecture: Which is the better exam score? 67 on an exam with mean 50 and SD 10 or 62 on an exam with mean 40 and SD 12 Is it fair
More informationChapter 5: The normal model
Chapter 5: The normal model Objective (1) Learn how rescaling a distribution affects its summary statistics. (2) Understand the concept of normal model. (3) Learn how to analyze distributions using the
More information1. (15 points) Solve the decanting problem for containers of sizes 199 and 179; that is find integers x and y satisfying.
May 9, 2003 Show all work Name There are 260 points available on this test 1 (15 points) Solve the decanting problem for containers of sizes 199 and 179; that is find integers x and y satisfying where
More informationChapter 2: The Normal Distributions
Chapter 2: The Normal Distributions Measures of Relative Standing & Density Curves Z-scores (Measures of Relative Standing) Suppose there is one spot left in the University of Michigan class of 2014 and
More informationEcon 3790: Business and Economics Statistics. Instructor: Yogesh Uppal
Econ 3790: Business and Economics Statistics Instructor: Yogesh Uppal Email: yuppal@ysu.edu Chapter 8: Interval Estimation Population Mean: Known Population Mean: Unknown Margin of Error and the Interval
More informationNormal Data ID1050 Quantitative & Qualitative Reasoning
Normal Data ID1050 Quantitative & Qualitative Reasoning Histogram for Different Sample Sizes For a small sample, the choice of class (group) size dramatically affects how the histogram appears. Say we
More informationChapter 2: Frequency Distributions
Chapter 2: Frequency Distributions Chapter Outline 2.1 Introduction to Frequency Distributions 2.2 Frequency Distribution Tables Obtaining ΣX from a Frequency Distribution Table Proportions and Percentages
More informationMeasures of Central Tendency
Page of 6 Measures of Central Tendency A measure of central tendency is a value used to represent the typical or average value in a data set. The Mean The sum of all data values divided by the number of
More informationChapter 6 Normal Probability Distributions
Chapter 6 Normal Probability Distributions 6-1 Review and Preview 6-2 The Standard Normal Distribution 6-3 Applications of Normal Distributions 6-4 Sampling Distributions and Estimators 6-5 The Central
More informationName: Date: Period: Chapter 2. Section 1: Describing Location in a Distribution
Name: Date: Period: Chapter 2 Section 1: Describing Location in a Distribution Suppose you earned an 86 on a statistics quiz. The question is: should you be satisfied with this score? What if it is the
More information2.1 Objectives. Math Chapter 2. Chapter 2. Variable. Categorical Variable EXPLORING DATA WITH GRAPHS AND NUMERICAL SUMMARIES
EXPLORING DATA WITH GRAPHS AND NUMERICAL SUMMARIES Chapter 2 2.1 Objectives 2.1 What Are the Types of Data? www.managementscientist.org 1. Know the definitions of a. Variable b. Categorical versus quantitative
More informationSTA Module 4 The Normal Distribution
STA 2023 Module 4 The Normal Distribution Learning Objectives Upon completing this module, you should be able to 1. Explain what it means for a variable to be normally distributed or approximately normally
More informationSTA /25/12. Module 4 The Normal Distribution. Learning Objectives. Let s Look at Some Examples of Normal Curves
STA 2023 Module 4 The Normal Distribution Learning Objectives Upon completing this module, you should be able to 1. Explain what it means for a variable to be normally distributed or approximately normally
More informationCHAPTER 2 Modeling Distributions of Data
CHAPTER 2 Modeling Distributions of Data 2.2 Density Curves and Normal Distributions The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers HW 34. Sketch
More informationSection 9: One Variable Statistics
The following Mathematics Florida Standards will be covered in this section: MAFS.912.S-ID.1.1 MAFS.912.S-ID.1.2 MAFS.912.S-ID.1.3 Represent data with plots on the real number line (dot plots, histograms,
More informationMATH 1070 Introductory Statistics Lecture notes Descriptive Statistics and Graphical Representation
MATH 1070 Introductory Statistics Lecture notes Descriptive Statistics and Graphical Representation Objectives: 1. Learn the meaning of descriptive versus inferential statistics 2. Identify bar graphs,
More informationFirst steps in SPSS. Figure 1
First steps in SPSS Statistical Package for Social Science (SPSS) is a computer program, working with the Windows operating system, and is specialized in the classification, processing and analysis of
More informationChapter 6 The Standard Deviation as Ruler and the Normal Model
ST 305 Chapter 6 Reiland The Standard Deviation as Ruler and the Normal Model Chapter Objectives: At the end of this chapter you should be able to: 1) describe how adding or subtracting the same value
More informationChapter 2 Describing, Exploring, and Comparing Data
Slide 1 Chapter 2 Describing, Exploring, and Comparing Data Slide 2 2-1 Overview 2-2 Frequency Distributions 2-3 Visualizing Data 2-4 Measures of Center 2-5 Measures of Variation 2-6 Measures of Relative
More informationAND NUMERICAL SUMMARIES. Chapter 2
EXPLORING DATA WITH GRAPHS AND NUMERICAL SUMMARIES Chapter 2 2.1 What Are the Types of Data? 2.1 Objectives www.managementscientist.org 1. Know the definitions of a. Variable b. Categorical versus quantitative
More informationWhat s Normal Anyway?
Name Class Problem 1 A Binomial Experiment 1. When rolling a die, what is the theoretical probability of rolling a 3? 2. When a die is rolled 100 times, how many times do you expect that a 3 will be rolled?
More informationSection 1.2. Displaying Quantitative Data with Graphs. Mrs. Daniel AP Stats 8/22/2013. Dotplots. How to Make a Dotplot. Mrs. Daniel AP Statistics
Section. Displaying Quantitative Data with Graphs Mrs. Daniel AP Statistics Section. Displaying Quantitative Data with Graphs After this section, you should be able to CONSTRUCT and INTERPRET dotplots,
More informationDistributions of Continuous Data
C H A P T ER Distributions of Continuous Data New cars and trucks sold in the United States average about 28 highway miles per gallon (mpg) in 2010, up from about 24 mpg in 2004. Some of the improvement
More informationWhen comparing in different sets of, the deviations should be compared only if the two sets of data use the
CHEBYSHEV S THEOREM The (or fraction) of any data set lying within K standard deviations of the mean is always 2 the following statements: 1 1, K 1 K At least ¾ or 75% of all values lie within 2 standard
More informationNormal Distribution. 6.4 Applications of Normal Distribution
Normal Distribution 6.4 Applications of Normal Distribution 1 /20 Homework Read Sec 6-4. Discussion question p316 Do p316 probs 1-10, 16-22, 31, 32, 34-37, 39 2 /20 3 /20 Objective Find the probabilities
More informationChapter 1. Looking at Data-Distribution
Chapter 1. Looking at Data-Distribution Statistics is the scientific discipline that provides methods to draw right conclusions: 1)Collecting the data 2)Describing the data 3)Drawing the conclusions Raw
More informationLESSON 3: CENTRAL TENDENCY
LESSON 3: CENTRAL TENDENCY Outline Arithmetic mean, median and mode Ungrouped data Grouped data Percentiles, fractiles, and quartiles Ungrouped data Grouped data 1 MEAN Mean is defined as follows: Sum
More informationMAT 110 WORKSHOP. Updated Fall 2018
MAT 110 WORKSHOP Updated Fall 2018 UNIT 3: STATISTICS Introduction Choosing a Sample Simple Random Sample: a set of individuals from the population chosen in a way that every individual has an equal chance
More informationSTA Rev. F Learning Objectives. Learning Objectives (Cont.) Module 3 Descriptive Measures
STA 2023 Module 3 Descriptive Measures Learning Objectives Upon completing this module, you should be able to: 1. Explain the purpose of a measure of center. 2. Obtain and interpret the mean, median, and
More informationLecture Series on Statistics -HSTC. Frequency Graphs " Dr. Bijaya Bhusan Nanda, Ph. D. (Stat.)
Lecture Series on Statistics -HSTC Frequency Graphs " By Dr. Bijaya Bhusan Nanda, Ph. D. (Stat.) CONTENT Histogram Frequency polygon Smoothed frequency curve Cumulative frequency curve or ogives Learning
More informationAverages and Variation
Averages and Variation 3 Copyright Cengage Learning. All rights reserved. 3.1-1 Section 3.1 Measures of Central Tendency: Mode, Median, and Mean Copyright Cengage Learning. All rights reserved. 3.1-2 Focus
More information2.1: Frequency Distributions and Their Graphs
2.1: Frequency Distributions and Their Graphs Frequency Distribution - way to display data that has many entries - table that shows classes or intervals of data entries and the number of entries in each
More informationMATH& 146 Lesson 10. Section 1.6 Graphing Numerical Data
MATH& 146 Lesson 10 Section 1.6 Graphing Numerical Data 1 Graphs of Numerical Data One major reason for constructing a graph of numerical data is to display its distribution, or the pattern of variability
More informationChapter 2: Modeling Distributions of Data
Chapter 2: Modeling Distributions of Data Section 2.2 The Practice of Statistics, 4 th edition - For AP* STARNES, YATES, MOORE Chapter 2 Modeling Distributions of Data 2.1 Describing Location in a Distribution
More informationChapter 2 - Descriptive Statistics
Chapter 2 - Descriptive Statistics Our ultimate aim in this class is to study Inferential statistics but before we can start making decisions about data we need to know how to describe this data in a useful
More informationUCLA STAT 13 Introduction to Statistical Methods for the Life and Health Sciences
UCLA STAT 3 Introduction to Statistical Methods for the Life and Health Sciences!Instructor: Ivo Dinov, Asst. Prof. In Statistics and Neurology!Teaching Assistants: Ming heng, Annie Che UCLA Statistics
More informationChapter 5snow year.notebook March 15, 2018
Chapter 5: Statistical Reasoning Section 5.1 Exploring Data Measures of central tendency (Mean, Median and Mode) attempt to describe a set of data by identifying the central position within a set of data
More informationThe Normal Distribution. John McGready, PhD Johns Hopkins University
The Normal Distribution John McGready, PhD Johns Hopkins University General Properties of The Normal Distribution The material in this video is subject to the copyright of the owners of the material and
More informationFrequency Distributions and Descriptive Statistics in SPS
230 Combs Building 859.622.3050 studentcomputing.eku.edu studentcomputing@eku.edu Frequency Distributions and Descriptive Statistics in SPSS In this tutorial, we re going to work through a sample problem
More informationLet s go through some examples of applying the normal distribution in practice.
Let s go through some examples of applying the normal distribution in practice. 1 We will work with gestation period of domestic cats. Suppose that the length of pregnancy in cats (which we will denote
More informationChapter 6. THE NORMAL DISTRIBUTION
Chapter 6. THE NORMAL DISTRIBUTION Introducing Normally Distributed Variables The distributions of some variables like thickness of the eggshell, serum cholesterol concentration in blood, white blood cells
More informationChapter 5. Normal. Normal Curve. the Normal. Curve Examples. Standard Units Standard Units Examples. for Data
curve Approximation Part II Descriptive Statistics The Approximation Approximation The famous normal curve can often be used as an 'ideal' histogram, to which histograms for data can be compared. Its equation
More informationAP Statistics. Study Guide
Measuring Relative Standing Standardized Values and z-scores AP Statistics Percentiles Rank the data lowest to highest. Counting up from the lowest value to the select data point we discover the percentile
More informationSection 3.1 Shapes of Distributions MDM4U Jensen
Section 3.1 Shapes of Distributions MDM4U Jensen Part 1: Histogram Review Example 1: Earthquakes are measured on a scale known as the Richter Scale. There data are a sample of earthquake magnitudes in
More informationa. divided by the. 1) Always round!! a) Even if class width comes out to a, go up one.
Probability and Statistics Chapter 2 Notes I Section 2-1 A Steps to Constructing Frequency Distributions 1 Determine number of (may be given to you) a Should be between and classes 2 Find the Range a The
More informationSections 2.3 and 2.4
Sections 2.3 and 2.4 Shiwen Shen Department of Statistics University of South Carolina Elementary Statistics for the Biological and Life Sciences (STAT 205) 2 / 25 Descriptive statistics For continuous
More informationCHAPTER 6. The Normal Probability Distribution
The Normal Probability Distribution CHAPTER 6 The normal probability distribution is the most widely used distribution in statistics as many statistical procedures are built around it. The central limit
More information1. Determine the population mean of x denoted m x. Ans. 10 from bottom bell curve.
6. Using the regression line, determine a predicted value of y for x = 25. Does it look as though this prediction is a good one? Ans. The regression line at x = 25 is at height y = 45. This is right at
More informationChapter 5: The standard deviation as a ruler and the normal model p131
Chapter 5: The standard deviation as a ruler and the normal model p131 Which is the better exam score? 67 on an exam with mean 50 and SD 10 62 on an exam with mean 40 and SD 12? Is it fair to say: 67 is
More informationLearner Expectations UNIT 1: GRAPICAL AND NUMERIC REPRESENTATIONS OF DATA. Sept. Fathom Lab: Distributions and Best Methods of Display
CURRICULUM MAP TEMPLATE Priority Standards = Approximately 70% Supporting Standards = Approximately 20% Additional Standards = Approximately 10% HONORS PROBABILITY AND STATISTICS Essential Questions &
More informationUNIT 1A EXPLORING UNIVARIATE DATA
A.P. STATISTICS E. Villarreal Lincoln HS Math Department UNIT 1A EXPLORING UNIVARIATE DATA LESSON 1: TYPES OF DATA Here is a list of important terms that we must understand as we begin our study of statistics
More informationMeasures of Dispersion
Measures of Dispersion 6-3 I Will... Find measures of dispersion of sets of data. Find standard deviation and analyze normal distribution. Day 1: Dispersion Vocabulary Measures of Variation (Dispersion
More informationBasic Statistical Terms and Definitions
I. Basics Basic Statistical Terms and Definitions Statistics is a collection of methods for planning experiments, and obtaining data. The data is then organized and summarized so that professionals can
More informationSection 7.2: Applications of the Normal Distribution
Section 7.2: Applications of the Normal Distribution Objectives By the end of this lesson, you will be able to... 1. find and interpret the area under a normal curve 2. find the value of a normal random
More informationChapter 6. THE NORMAL DISTRIBUTION
Chapter 6. THE NORMAL DISTRIBUTION Introducing Normally Distributed Variables The distributions of some variables like thickness of the eggshell, serum cholesterol concentration in blood, white blood cells
More informationSTA Module 2B Organizing Data and Comparing Distributions (Part II)
STA 2023 Module 2B Organizing Data and Comparing Distributions (Part II) Learning Objectives Upon completing this module, you should be able to 1 Explain the purpose of a measure of center 2 Obtain and
More information