1) What is the range of the data shown in the box and whisker plot? 2) True or False: 75% of the data falls between 6 and 12.
|
|
|
- Georgina Heath
- 5 years ago
- Views:
Transcription
1 DO NOW 1) What is the range of the data shown in the box and whisker plot? 2) True or False: 75% of the data falls between 6 and 12. May 21 7:19 AM Min = 17, Q 1 = 18.5, Med = 21.5, Q 3 = 25, Max = 47 HW Answers Min = 67, Q 1 = 76, Med = 85, Q 3 = 91, Max = (a) 21 (b) 45 (c) 12 (d) More people are speeding. Since the median is 37mph, that means that more than 50% of people are going over the speed limit of 35 mph May 11 9:44 AM 1
2 Measures of Spread Measures of central tendency give us information about the center of data. Measures of spread give us information about the variation in our data. include the range, quartiles and the interquartile range and standard deviation Interquartile Range The Value of Quartile 3 The Value of Quartile 1 May 4 9:09 AM Standard Deviation Tells us, on average, how far a data point is away from the mean of the data set. The larger the standard deviation, the greater the variation within the data set. (shown as on the calculator) May 13 12:49 PM 2
3 Exercise #1: The two data sets below each have equal means but differ in the variation within the data set. Determine the Interquartile Range (IQR) of each data set. Data Set #1: 3, 3, 4, 4, 5, 5, 6, 6, 7, 8, 8, 9, 9, 10, 10, 11, 11 Data Set #2: 5, 5, 6, 6, 7, 7, 8, 8, 9, 9 Calculator Instructions STAT 1: Edit... Type data into L1 STAT CALC 1: 1 Var Stats May 8 12:39 PM Data Set #1 Data Set #2 May 13 8:13 AM 3
4 Exercise #2: Using the same data sets above, use your calculator to produce the standard deviation of the two data sets. Round your answers to the nearest tenth. Data Set #1: 3, 3, 4, 4, 5, 5, 6, 6, 7, 8, 8, 9, 9, 10, 10, 11, 11 Data Set #2: 5, 5, 6, 6, 7, 7, 8, 8, 9, 9 May 8 12:41 PM Data Set #1 Data Set #2 May 13 8:17 AM 4
5 Exercise #3: A farm is studying the weight of baby chickens (chicks) after 1 week of growth. They find the weight, in ounces, of 20 chicks. The weights are shown below. Find the mean, the interquartile range and the standard deviation for this data set. Round any non integer values to the nearest tenth. Include appropriate units in your answers. Give an interpretation of the standard deviation. 2, 1, 3, 4, 2, 2, 3, 1, 5, 3, 4, 4, 5, 6, 3, 8, 5, 4, 6, 3 mean interquartile range (IQR) standard deviation Q 3 = 5 Q 1 = = 2 IQR = 2 May 8 12:42 PM Exercise #4: A marketing company is trying to determine how much diversity there is in the age of people who drink different soft drinks. They take a sample of people and ask them which soda they prefer. For the two sodas, the age of those people who preferred them is given below. Soda A: 18, 16, 22, 16, 28, 18, 21, 38, 22, 29, 25, 44, 36, 27, 40 Soda B: 25, 22, 18, 30, 27, 19, 22, 28, 25, 19, 23, 29, 26, 18, 20 (a) Explain why standard deviation is a better measure of the diversity in age than the mean. Diversity means variety or a range of different ages which is what standard deviation measures. Mean would only tell you the average age (b) Which soda appears to have a greater diversity in the age of people who prefer it? How did you decide on this? Soda A has more diversity because the min age is 16 and max age is 40 (c) Use your calculator to determine the sample standard deviation, normally given as s x, for both data sets. Round your answers to the nearest tenth. Did this answer reinforce your pick from (b)? How? May 8 12:44 PM 5
6 Exercise #5: Which of the following data sets would have a standard deviation (population) closest to zero? Do this without your calculator. Explain how you arrived at your answer. (1) { 5, 2, 1, 0,1, 2, 5} (3) {11,11,12,13,13} (2) {5, 8,10,16, 20} (4) {3, 7,11,11,11,18} May 8 12:46 PM May 4 9:04 AM 6
Numerical Descriptions of Data
Numerical Descriptions of Data Measures of Center Mean x = x i n Excel: = average ( ) Weighted mean x = (x i w i ) w i x = data values x i = i th data value w i = weight of the i th data value Median =
NOTES TO CONSIDER BEFORE ATTEMPTING EX 2C BOX PLOTS
NOTES TO CONSIDER BEFORE ATTEMPTING EX 2C BOX PLOTS A box plot is a pictorial representation of the data and can be used to get a good idea and a clear picture about the distribution of the data. It shows
Math 140 Introductory Statistics. First midterm September
Math 140 Introductory Statistics First midterm September 23 2010 Box Plots Graphical display of 5 number summary Q1, Q2 (median), Q3, max, min Outliers If a value is more than 1.5 times the IQR from the
Measures of Center. Mean. 1. Mean 2. Median 3. Mode 4. Midrange (rarely used) Measure of Center. Notation. Mean
Measure of Center Measures of Center The value at the center or middle of a data set 1. Mean 2. Median 3. Mode 4. Midrange (rarely used) 1 2 Mean Notation The measure of center obtained by adding the values
Some estimates of the height of the podium
Some estimates of the height of the podium 24 36 40 40 40 41 42 44 46 48 50 53 65 98 1 5 number summary Inter quartile range (IQR) range = max min 2 1.5 IQR outlier rule 3 make a boxplot 24 36 40 40 40
Chapter 3. Numerical Descriptive Measures. Copyright 2016 Pearson Education, Ltd. Chapter 3, Slide 1
Chapter 3 Numerical Descriptive Measures Copyright 2016 Pearson Education, Ltd. Chapter 3, Slide 1 Objectives In this chapter, you learn to: Describe the properties of central tendency, variation, and
2 Exploring Univariate Data
2 Exploring Univariate Data A good picture is worth more than a thousand words! Having the data collected we examine them to get a feel for they main messages and any surprising features, before attempting
3.1 Measures of Central Tendency
3.1 Measures of Central Tendency n Summation Notation x i or x Sum observation on the variable that appears to the right of the summation symbol. Example 1 Suppose the variable x i is used to represent
Ti 83/84. Descriptive Statistics for a List of Numbers
Ti 83/84 Descriptive Statistics for a List of Numbers Quiz scores in a (fictitious) class were 10.5, 13.5, 8, 12, 11.3, 9, 9.5, 5, 15, 2.5, 10.5, 7, 11.5, 10, and 10.5. It s hard to get much of a sense
Mini-Lecture 3.1 Measures of Central Tendency
Mini-Lecture 3.1 Measures of Central Tendency Objectives 1. Determine the arithmetic mean of a variable from raw data 2. Determine the median of a variable from raw data 3. Explain what it means for a
STAT 113 Variability
STAT 113 Variability Colin Reimer Dawson Oberlin College September 14, 2017 1 / 48 Outline Last Time: Shape and Center Variability Boxplots and the IQR Variance and Standard Deviaton Transformations 2
Percentiles, STATA, Box Plots, Standardizing, and Other Transformations
Percentiles, STATA, Box Plots, Standardizing, and Other Transformations Lecture 3 Reading: Sections 5.7 54 Remember, when you finish a chapter make sure not to miss the last couple of boxes: What Can Go
How Wealthy Are Europeans?
How Wealthy Are Europeans? Grades: 7, 8, 11, 12 (course specific) Description: Organization of data of to examine measures of spread and measures of central tendency in examination of Gross Domestic Product
Describing Data: One Quantitative Variable
STAT 250 Dr. Kari Lock Morgan The Big Picture Describing Data: One Quantitative Variable Population Sampling SECTIONS 2.2, 2.3 One quantitative variable (2.2, 2.3) Statistical Inference Sample Descriptive
Monte Carlo Simulation (Random Number Generation)
Monte Carlo Simulation (Random Number Generation) Revised: 10/11/2017 Summary... 1 Data Input... 1 Analysis Options... 6 Summary Statistics... 6 Box-and-Whisker Plots... 7 Percentiles... 9 Quantile Plots...
Exploratory Data Analysis
Exploratory Data Analysis Stemplots (or Stem-and-leaf plots) Stemplot and Boxplot T -- leading digits are called stems T -- final digits are called leaves STAT 74 Descriptive Statistics 2 Example: (number
Center and Spread. Measures of Center and Spread. Example: Mean. Mean: the balance point 2/22/2009. Describing Distributions with Numbers.
Chapter 3 Section3-: Measures of Center Section 3-3: Measurers of Variation Section 3-4: Measures of Relative Standing Section 3-5: Exploratory Data Analysis Describing Distributions with Numbers The overall
MATH SPEAK - TO BE UNDERSTOOD AND MEMORIZED
FOM 11 T9 STANDARD DEVIATION 1 MATH SPEAK - TO BE UNDERSTOOD AND MEMORIZED 1) STATISTICS = the branch of mathematics used to analyze and interpret data. 2) DATA = information, often in the form of numbers,
Descriptive Statistics
Petra Petrovics Descriptive Statistics 2 nd seminar DESCRIPTIVE STATISTICS Definition: Descriptive statistics is concerned only with collecting and describing data Methods: - statistical tables and graphs
Empirical Rule (P148)
Interpreting the Standard Deviation Numerical Descriptive Measures for Quantitative data III Dr. Tom Ilvento FREC 408 We can use the standard deviation to express the proportion of cases that might fall
Data that can be any numerical value are called continuous. These are usually things that are measured, such as height, length, time, speed, etc.
Chapter 8 Measures of Center Data that can be any numerical value are called continuous. These are usually things that are measured, such as height, length, time, speed, etc. Data that can only be integer
Unit 2 Measures of Variation
1. (a) Weight in grams (w) 6 < w 8 4 8 < w 32 < w 1 6 1 < w 1 92 1 < w 16 8 6 Median 111, Inter-quartile range 3 Distance in km (d) < d 1 1 < d 2 17 2 < d 3 22 3 < d 4 28 4 < d 33 < d 6 36 Median 2.2,
appstats5.notebook September 07, 2016 Chapter 5
Chapter 5 Describing Distributions Numerically Chapter 5 Objective: Students will be able to use statistics appropriate to the shape of the data distribution to compare of two or more different data sets.
Multiple Choice: Identify the choice that best completes the statement or answers the question.
U8: Statistics Review Name: Date: Multiple Choice: Identify the choice that best completes the statement or answers the question. 1. A floral delivery company conducts a study to measure the effect of
Handout 4 numerical descriptive measures part 2. Example 1. Variance and Standard Deviation for Grouped Data. mf N 535 = = 25
Handout 4 numerical descriptive measures part Calculating Mean for Grouped Data mf Mean for population data: µ mf Mean for sample data: x n where m is the midpoint and f is the frequency of a class. Example
FINALS REVIEW BELL RINGER. Simplify the following expressions without using your calculator. 1) 6 2/3 + 1/2 2) 2 * 3(1/2 3/5) 3) 5/ /2 4
FINALS REVIEW BELL RINGER Simplify the following expressions without using your calculator. 1) 6 2/3 + 1/2 2) 2 * 3(1/2 3/5) 3) 5/3 + 7 + 1/2 4 4) 3 + 4 ( 7) + 3 + 4 ( 2) 1) 36/6 4/6 + 3/6 32/6 + 3/6 35/6
Math 243 Lecture Notes
Assume the average annual rainfall for in Portland is 36 inches per year with a standard deviation of 9 inches. Also assume that the average wind speed in Chicago is 10 mph with a standard deviation of
STATISTICAL DISTRIBUTIONS AND THE CALCULATOR
STATISTICAL DISTRIBUTIONS AND THE CALCULATOR 1. Basic data sets a. Measures of Center - Mean ( ): average of all values. Characteristic: non-resistant is affected by skew and outliers. - Median: Either
Chapter 2: Descriptive Statistics. Mean (Arithmetic Mean): Found by adding the data values and dividing the total by the number of data.
-3: Measure of Central Tendency Chapter : Descriptive Statistics The value at the center or middle of a data set. It is a tool for analyzing data. Part 1: Basic concepts of Measures of Center Ex. Data
Unit 2 Statistics of One Variable
Unit 2 Statistics of One Variable Day 6 Summarizing Quantitative Data Summarizing Quantitative Data We have discussed how to display quantitative data in a histogram It is useful to be able to describe
Chapter 3. Descriptive Measures. Copyright 2016, 2012, 2008 Pearson Education, Inc. Chapter 3, Slide 1
Chapter 3 Descriptive Measures Copyright 2016, 2012, 2008 Pearson Education, Inc. Chapter 3, Slide 1 Chapter 3 Descriptive Measures Mean, Median and Mode Copyright 2016, 2012, 2008 Pearson Education, Inc.
DATA HANDLING Five-Number Summary
DATA HANDLING Five-Number Summary The five-number summary consists of the minimum and maximum values, the median, and the upper and lower quartiles. The minimum and the maximum are the smallest and greatest
Math 2311 Bekki George Office Hours: MW 11am to 12:45pm in 639 PGH Online Thursdays 4-5:30pm And by appointment
Math 2311 Bekki George bekki@math.uh.edu Office Hours: MW 11am to 12:45pm in 639 PGH Online Thursdays 4-5:30pm And by appointment Class webpage: http://www.math.uh.edu/~bekki/math2311.html Math 2311 Class
1 Describing Distributions with numbers
1 Describing Distributions with numbers Only for quantitative variables!! 1.1 Describing the center of a data set The mean of a set of numerical observation is the familiar arithmetic average. To write
Putting Things Together Part 2
Frequency Putting Things Together Part These exercise blend ideas from various graphs (histograms and boxplots), differing shapes of distributions, and values summarizing the data. Data for, and are in
Stat 201: Business Statistics I Additional Exercises on Chapter Chapter 3
Stat 201: Business Statistics I Additional Exercises on Chapter Chapter 3 Student Name: Solve the problem. 1) A sociologist recently conducted a survey of senior citizens who have net worths too high to
Chapter 3 Descriptive Statistics: Numerical Measures Part A
Slides Prepared by JOHN S. LOUCKS St. Edward s University Slide 1 Chapter 3 Descriptive Statistics: Numerical Measures Part A Measures of Location Measures of Variability Slide Measures of Location Mean
STOR 155 Practice Midterm 1 Fall 2009
STOR 155 Practice Midterm 1 Fall 2009 INSTRUCTIONS: BOTH THE EXAM AND THE BUBBLE SHEET WILL BE COLLECTED. YOU MUST PRINT YOUR NAME AND SIGN THE HONOR PLEDGE ON THE BUBBLE SHEET. YOU MUST BUBBLE-IN YOUR
= P25 = Q1 = = P50 = Q2 = = = P75 = Q3
NOMINAL- No ordering of the items ORDINAL- are categorical data where there is a logical ordering to the categories. (The simplest ordinal scale is a ranking) INTERVAL- 0 is only an arbitrary reference
Chapter 3. Lecture 3 Sections
Chapter 3 Lecture 3 Sections 3.4 3.5 Measure of Position We would like to compare values from different data sets. We will introduce a z score or standard score. This measures how many standard deviation
2CORE. Summarising numerical data: the median, range, IQR and box plots
C H A P T E R 2CORE Summarising numerical data: the median, range, IQR and box plots How can we describe a distribution with just one or two statistics? What is the median, how is it calculated and what
Standardized Data Percentiles, Quartiles and Box Plots Grouped Data Skewness and Kurtosis
Descriptive Statistics (Part 2) 4 Chapter Percentiles, Quartiles and Box Plots Grouped Data Skewness and Kurtosis McGraw-Hill/Irwin Copyright 2009 by The McGraw-Hill Companies, Inc. Chebyshev s Theorem
DATA ANALYSIS EXAM QUESTIONS
DATA ANALYSIS EXAM QUESTIONS Question 1 (**) The number of phone text messages send by 11 different students is given below. 14, 25, 31, 36, 37, 41, 51, 52, 55, 79, 112. a) Find the lower quartile, the
Basic Procedure for Histograms
Basic Procedure for Histograms 1. Compute the range of observations (min. & max. value) 2. Choose an initial # of classes (most likely based on the range of values, try and find a number of classes that
Math146 - Chapter 3 Handouts. The Greek Alphabet. Source: Page 1 of 39
Source: www.mathwords.com The Greek Alphabet Page 1 of 39 Some Miscellaneous Tips on Calculations Examples: Round to the nearest thousandth 0.92431 0.75693 CAUTION! Do not truncate numbers! Example: 1
The Standard Deviation as a Ruler and the Normal Model. Copyright 2009 Pearson Education, Inc.
The Standard Deviation as a Ruler and the Normal Mol Copyright 2009 Pearson Education, Inc. The trick in comparing very different-looking values is to use standard viations as our rulers. The standard
KING FAHD UNIVERSITY OF PETROLEUM & MINERALS DEPARTMENT OF MATHEMATICAL SCIENCES DHAHRAN, SAUDI ARABIA. Name: ID# Section
KING FAHD UNIVERSITY OF PETROLEUM & MINERALS DEPARTMENT OF MATHEMATICAL SCIENCES DHAHRAN, SAUDI ARABIA STAT 11: BUSINESS STATISTICS I Semester 04 Major Exam #1 Sunday March 7, 005 Please circle your instructor
Section3-2: Measures of Center
Chapter 3 Section3-: Measures of Center Notation Suppose we are making a series of observations, n of them, to be exact. Then we write x 1, x, x 3,K, x n as the values we observe. Thus n is the total number
Statistics (This summary is for chapters 18, 29 and section H of chapter 19)
Statistics (This summary is for chapters 18, 29 and section H of chapter 19) Mean, Median, Mode Mode: most common value Median: middle value (when the values are in order) Mean = total how many = x n =
Stat 101 Exam 1 - Embers Important Formulas and Concepts 1
1 Chapter 1 1.1 Definitions Stat 101 Exam 1 - Embers Important Formulas and Concepts 1 1. Data Any collection of numbers, characters, images, or other items that provide information about something. 2.
Today s plan: Section 4.1.4: Dispersion: Five-Number summary and Standard Deviation.
1 Today s plan: Section 4.1.4: Dispersion: Five-Number summary and Standard Deviation. 2 Once we know the central location of a data set, we want to know how close things are to the center. 2 Once we know
MVE051/MSG Lecture 7
MVE051/MSG810 2017 Lecture 7 Petter Mostad Chalmers November 20, 2017 The purpose of collecting and analyzing data Purpose: To build and select models for parts of the real world (which can be used for
Simple Descriptive Statistics
Simple Descriptive Statistics These are ways to summarize a data set quickly and accurately The most common way of describing a variable distribution is in terms of two of its properties: Central tendency
Lecture 1: Review and Exploratory Data Analysis (EDA)
Lecture 1: Review and Exploratory Data Analysis (EDA) Ani Manichaikul amanicha@jhsph.edu 16 April 2007 1 / 40 Course Information I Office hours For questions and help When? I ll announce this tomorrow
Statistics (This summary is for chapters 17, 28, 29 and section G of chapter 19)
Statistics (This summary is for chapters 17, 28, 29 and section G of chapter 19) Mean, Median, Mode Mode: most common value Median: middle value (when the values are in order) Mean = total how many = x
Description of Data I
Description of Data I (Summary and Variability measures) Objectives: Able to understand how to summarize the data Able to understand how to measure the variability of the data Able to use and interpret
Manual for the TI-83, TI-84, and TI-89 Calculators
Manual for the TI-83, TI-84, and TI-89 Calculators to accompany Mendenhall/Beaver/Beaver s Introduction to Probability and Statistics, 13 th edition James B. Davis Contents Chapter 1 Introduction...4 Chapter
CHAPTER 2 Describing Data: Numerical
CHAPTER Multiple-Choice Questions 1. A scatter plot can illustrate all of the following except: A) the median of each of the two variables B) the range of each of the two variables C) an indication of
Lecture 2 Describing Data
Lecture 2 Describing Data Thais Paiva STA 111 - Summer 2013 Term II July 2, 2013 Lecture Plan 1 Types of data 2 Describing the data with plots 3 Summary statistics for central tendency and spread 4 Histograms
Unit 2: Statistics Probability
Applied Math 30 3-1: Distributions Probability Distribution: - a table or a graph that displays the theoretical probability for each outcome of an experiment. - P (any particular outcome) is between 0
MgtOp 215 TEST 1 (Golden) Spring 2016 Dr. Ahn. Read the following instructions very carefully before you start the test.
MgtOp 15 TEST 1 (Golden) Spring 016 Dr. Ahn Name: ID: Section (Circle one): 4, 5, 6 Read the following instructions very carefully before you start the test. This test is closed book and notes; one summary
Math Take Home Quiz on Chapter 2
Math 116 - Take Home Quiz on Chapter 2 Show the calculations that lead to the answer. Due date: Tuesday June 6th Name Time your class meets Provide an appropriate response. 1) A newspaper surveyed its
Normal Probability Distributions
C H A P T E R Normal Probability Distributions 5 Section 5.2 Example 3 (pg. 248) Normal Probabilities Assume triglyceride levels of the population of the United States are normally distributed with a mean
STA 248 H1S Winter 2008 Assignment 1 Solutions
1. (a) Measures of location: STA 248 H1S Winter 2008 Assignment 1 Solutions i. The mean, 100 1=1 x i/100, can be made arbitrarily large if one of the x i are made arbitrarily large since the sample size
Copyright 2005 Pearson Education, Inc. Slide 6-1
Copyright 2005 Pearson Education, Inc. Slide 6-1 Chapter 6 Copyright 2005 Pearson Education, Inc. Measures of Center in a Distribution 6-A The mean is what we most commonly call the average value. It is
AP Stats ~ Lesson 6B: Transforming and Combining Random variables
AP Stats ~ Lesson 6B: Transforming and Combining Random variables OBJECTIVES: DESCRIBE the effects of transforming a random variable by adding or subtracting a constant and multiplying or dividing by a
SOLUTIONS TO THE LAB 1 ASSIGNMENT
SOLUTIONS TO THE LAB 1 ASSIGNMENT Question 1 Excel produces the following histogram of pull strengths for the 100 resistors: 2 20 Histogram of Pull Strengths (lb) Frequency 1 10 0 9 61 63 6 67 69 71 73
Categorical. A general name for non-numerical data; the data is separated into categories of some kind.
Chapter 5 Categorical A general name for non-numerical data; the data is separated into categories of some kind. Nominal data Categorical data with no implied order. Eg. Eye colours, favourite TV show,
1.2 Describing Distributions with Numbers, Continued
1.2 Describing Distributions with Numbers, Continued Ulrich Hoensch Thursday, September 6, 2012 Interquartile Range and 1.5 IQR Rule for Outliers The interquartile range IQR is the distance between the
A LEVEL MATHEMATICS ANSWERS AND MARKSCHEMES SUMMARY STATISTICS AND DIAGRAMS. 1. a) 45 B1 [1] b) 7 th value 37 M1 A1 [2]
![A LEVEL MATHEMATICS ANSWERS AND MARKSCHEMES SUMMARY STATISTICS AND DIAGRAMS. 1. a) 45 B1 [1] b) 7 th value 37 M1 A1 [2]](/thumbs/81/83043398.jpg "A LEVEL MATHEMATICS ANSWERS AND MARKSCHEMES SUMMARY STATISTICS AND DIAGRAMS. 1. a) 45 B1 [1] b) 7 th value 37 M1 A1 [2]")
1. a) 45 [1] b) 7 th value 37 [] n c) LQ : 4 = 3.5 4 th value so LQ = 5 3 n UQ : 4 = 9.75 10 th value so UQ = 45 IQR = 0 f.t. d) Median is closer to upper quartile Hence negative skew [] Page 1 . a) Orders
Distributions and their Characteristics
Distributions and their Characteristics 1. A distribution of a variable is merely a list of all values the variable can take, and the corresponding frequencies. Distributions may be represented or displayed
Standard Deviation. Lecture 18 Section Robb T. Koether. Hampden-Sydney College. Mon, Sep 26, 2011
Standard Deviation Lecture 18 Section 5.3.4 Robb T. Koether Hampden-Sydney College Mon, Sep 26, 2011 Robb T. Koether (Hampden-Sydney College) Standard Deviation Mon, Sep 26, 2011 1 / 42 Outline 1 Variability
Lesson 12: Describing Distributions: Shape, Center, and Spread
: Shape, Center, and Spread Opening Exercise Distributions - Data are often summarized by graphs. We often refer to the group of data presented in the graph as a distribution. Below are examples of the
The Not-So-Geeky World of Statistics
FEBRUARY 3 5, 2015 / THE HILTON NEW YORK The Not-So-Geeky World of Statistics Chris Emerson Chris Sweet (a/k/a Chris 2 ) 2 Who We Are Chris Sweet JPMorgan Chase VP, Outside Counsel & Engagement Management
Putting Things Together Part 1
Putting Things Together Part 1 These exercise blend ideas from various graphs (histograms and boxplots), differing shapes of distributions, and values summarizing the data. Data for 1, 5, and 6 are in
9/17/2015. Basic Statistics for the Healthcare Professional. Relax.it won t be that bad! Purpose of Statistic. Objectives
Basic Statistics for the Healthcare Professional 1 F R A N K C O H E N, M B B, M P A D I R E C T O R O F A N A L Y T I C S D O C T O R S M A N A G E M E N T, LLC Purpose of Statistic 2 Provide a numerical
Measures of Central Tendency: Ungrouped Data. Mode. Median. Mode -- Example. Median: Example with an Odd Number of Terms
Measures of Central Tendency: Ungrouped Data Measures of central tendency yield information about particular places or locations in a group of numbers. Common Measures of Location Mode Median Percentiles
Section 7.4 Transforming and Combining Random Variables (DAY 1)
Section 7.4 Learning Objectives (DAY 1) After this section, you should be able to DESCRIBE the effect of performing a linear transformation on a random variable (DAY 1) COMBINE random variables and CALCULATE
Name: Algebra & 9.4 Midterm Review Sheet January 2019
Name: Algebra 1 9.3 & 9.4 Midterm Review Sheet January 2019 The Midterm format will include 35 Part I multiple choice questions that will be worth 1 point each, 10 Part II short answer questions that will
Applications of Data Dispersions
1 Applications of Data Dispersions Key Definitions Standard Deviation: The standard deviation shows how far away each value is from the mean on average. Z-Scores: The distance between the mean and a given
Numerical Measurements
El-Shorouk Academy Acad. Year : 2013 / 2014 Higher Institute for Computer & Information Technology Term : Second Year : Second Department of Computer Science Statistics & Probabilities Section # 3 umerical
Chapter 2. Section 2.1
Chapter 2 Section 2.1 Check Your Understanding, page 89: 1. c 2. Her daughter weighs more than 87% of girls her age and she is taller than 67% of girls her age. 3. About 65% of calls lasted less than 30
STAT Chapter 6 The Standard Deviation (SD) as a Ruler and The Normal Model
STAT 203 - Chapter 6 The Standard Deviation (SD) as a Ruler and The Normal Model In Chapter 5, we introduced a few measures of center and spread, and discussed how the mean and standard deviation are good
Much of what appears here comes from ideas presented in the book:
Chapter 11 Robust statistical methods Much of what appears here comes from ideas presented in the book: Huber, Peter J. (1981), Robust statistics, John Wiley & Sons (New York; Chichester). There are many
STAT Chapter 6 The Standard Deviation (SD) as a Ruler and The Normal Model
STAT 203 - Chapter 6 The Standard Deviation (SD) as a Ruler and The Normal Model In Chapter 5, we introduced a few measures of center and spread, and discussed how the mean and standard deviation are good
Some Characteristics of Data
Some Characteristics of Data Not all data is the same, and depending on some characteristics of a particular dataset, there are some limitations as to what can and cannot be done with that data. Some key
Key: 18 5 = 1.85 cm. 5 a Stem Leaf. Key: 2 0 = 20 points. b Stem Leaf. Key: 2 0 = 20 cm. 6 a Stem Leaf. Key: 4 3 = 43 cm.
Answers EXERCISE. D D C B Numerical: a, b, c Categorical: c, d, e, f, g Discrete: c Continuous: a, b C C Categorical B A Categorical and ordinal Discrete Ordinal D EXERCISE. Stem Key: = Stem Key: = $ The
Name: 9/21/2017 General Math Test 1 1) Simplify the following and write your answer in scientific notation. a)
Name: 9/21/2017 General Math Test 1 1) Simplify the following and write your answer in scientific notation. a) 7.65 10 2 b) (42.3 10 4 )(6.23 10 14 ) 5.67 10 4 c) (10 5 10 4 ) 2 d) (7.54 10 2 )(3.45 10
Descriptive Statistics
Chapter 3 Descriptive Statistics Chapter 2 presented graphical techniques for organizing and displaying data. Even though such graphical techniques allow the researcher to make some general observations
S3 (3.2) N5 Mean & Standard Deviation.notebook October 31, 2014
Daily Practice 29.9.2014 Q1. 60.98 + 22.13-30 Q2. 4-3 x 5 Q3. Factorise 6x - 15-45 Today we will be marking the check-up on percentages and then starting mean and standard deviation. Homework Due! Q4.
Edexcel past paper questions
Edexcel past paper questions Statistics 1 Chapters 2-4 (Discrete) Statistics 1 Chapters 2-4 (Discrete) Page 1 Stem and leaf diagram Stem-and-leaf diagrams are used to represent data in its original form.
IMPORTING & MANAGING FINANCIAL DATA IN PYTHON. Summarize your data with descriptive stats
IMPORTING & MANAGING FINANCIAL DATA IN PYTHON Summarize your data with descriptive stats Be on top of your data Goal: Capture key quantitative characteristics Important angles to look at: Central tendency:
22.2 Shape, Center, and Spread
Name Class Date 22.2 Shape, Center, and Spread Essential Question: Which measures of center and spread are appropriate for a normal distribution, and which are appropriate for a skewed distribution? Eplore
Introduction to Computational Finance and Financial Econometrics Descriptive Statistics
You can t see this text! Introduction to Computational Finance and Financial Econometrics Descriptive Statistics Eric Zivot Summer 2015 Eric Zivot (Copyright 2015) Descriptive Statistics 1 / 28 Outline
Chapter 3 Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2013 John Wiley & Sons, Inc.
1 3.1 Describing Variation Stem-and-Leaf Display Easy to find percentiles of the data; see page 69 2 Plot of Data in Time Order Marginal plot produced by MINITAB Also called a run chart 3 Histograms Useful
Both the quizzes and exams are closed book. However, For quizzes: Formulas will be provided with quiz papers if there is any need.
Both the quizzes and exams are closed book. However, For quizzes: Formulas will be provided with quiz papers if there is any need. For exams (MD1, MD2, and Final): You may bring one 8.5 by 11 sheet of
Chapter 3: Displaying and Describing Quantitative Data Quiz A Name
Chapter 3: Displaying and Describing Quantitative Data Quiz A Name 3.1.1 Find summary statistics; create displays; describe distributions; determine 1. Following is a histogram of salaries (in $) for a
Name Date. Key Math Concepts
5-1 Classified Ads Sales tax = price of item sales tax rate Key Math Concepts A piecewise function gives a set of rules for each set of the function. The domain is defined by the inequalities that follow
8. From FRED, search for Canada unemployment and download the unemployment rate for all persons 15 and over, monthly,
Economics 250 Introductory Statistics Exercise 1 Due Tuesday 29 January 2019 in class and on paper Instructions: There is no drop box and this exercise can be submitted only in class. No late submissions
Exam 1 Review. 1) Identify the population being studied. The heights of 14 out of the 31 cucumber plants at Mr. Lonardo's greenhouse.
Exam 1 Review 1) Identify the population being studied. The heights of 14 out of the 31 cucumber plants at Mr. Lonardo's greenhouse. 2) Identify the population being studied and the sample chosen. The