Source: Fall 2015 Biostats 540 Exam I. BIOSTATS 540 Fall 2016 Practice Test for Unit 1 Summarizing Data Page 1 of 6

Size: px
Start display at page:

Download "Source: Fall 2015 Biostats 540 Exam I. BIOSTATS 540 Fall 2016 Practice Test for Unit 1 Summarizing Data Page 1 of 6"

Transcription

1 BIOSTATS 540 Fall 2016 Practice Test for Unit 1 Summarizing Data Page 1 of 6 Source: Fall 2015 Biostats 540 Exam I. 1. 1a. The U.S. Census Bureau reports the median family income in its summary of census data. Why do you suppose they use the median instead of the mean? What might be the disadvantages of reporting the mean? 1b. You have just bought a new car that claims to get a highway fuel efficiency of 31 miles per gallon. Of course, your mileage will vary. If you had to guess, would you expect the interquartile range (IQR) of gas mileage attained by all cars like yours to be 30 mpg, 3 mpg, or 0.3 mpg? Why? 1c. A company selling a new MP3 player advertises that the player has a mean lifetime of 5 years. If you were in charge of quality control at the factory, would you prefer that the standard deviation of life spans of the players you produce be 2 years or 2 months? Why?

2 BIOSTATS 540 Fall 2016 Practice Test for Unit 1 Summarizing Data Page 2 of 6 2. A survey is taken by the U.S. Bureau of the Census. It reports that the median incomes in the past 12 months were $52,168 for women and $61,975 for men. It is also reported that the mean earnings in the past 12 months were $59,890 for women and $76,724 for men. 2a. Does this data suggest that the distribution of income for each gender is symmetric, positive (right) skewed or negative (left) skewed? In 1-2 sentences at most, explain your reasoning. 2b. 3The results of this survey were obtained from 73.8 million women and 83.4 million men. Calculate the overall sample mean income. Show your work.

3 BIOSTATS 540 Fall 2016 Practice Test for Unit 1 Summarizing Data Page 3 of 6 3. The following are 9 observations of cost ($) of compact refrigerators $150 $150 $160 $180 $150 $140 $120 $130 $120 3a. By hand (no calculator!) calculate the value of the sample mean. Show your work. 3b. By hand (no calculator!) calculate the value of the sample standard deviation. Show your work. 3c. By hand (no calculator!) calculate the value of the sample median. Show your work. 3d. By hand (no calculator!) calculate the values of the 1st (25 th percentile) and 3 rd (75 th percentile) quartiles (Q1 and Q3). Show your work. 3e. By hand (no calculator!) calculate the value of the interquartile range (IQR). Show your work.

4 BIOSTATS 540 Fall 2016 Practice Test for Unit 1 Summarizing Data Page 4 of 6 4. A school system employs teachers at salaries between $40,000 and $70,000. The mean and standard deviation are $44,000 and $3,000 respectively. The teachers union and the school board are negotiating the form of next year s increase in the salary schedule. For Questions #4a #4d ONLY: Suppose that every teacher is given a flat $1000 raise. 4a. By how much will the mean salary increase? 4b. By how much will the median salary increase? 4c. By how much will the interquartile range (IQR) increase? 4d. By how much will the sample variance increase? Tip I said sample variance, not sample standard deviation. For Question #4e ONLY: Now suppose that, instead of a flat raise, every teacher is given a 5% raise. 4e. By how much will the sample variance increase? Again I said sample variance, not sample standard deviation. Tip - Express your answer as a percent (eg The sample variance increases by 25%). Note it is NOT possible to give a number as your answer.

5 BIOSTATS 540 Fall 2016 Practice Test for Unit 1 Summarizing Data Page 5 of 6 5. A study examining the health risks of smoking measured the cholesterol (mg/dl) levels of people in two independent groups: 1) SMOKERS: those who had smoked for at least 25 years; and 2) NON-SMOKERS: persons of similar ages who had never smoked. The following are the data. Smokers NON-Smokers

6 BIOSTATS 540 Fall 2016 Practice Test for Unit 1 Summarizing Data Page 6 of 6 5a. Complete the following table. Number in group, n = P 25 = Q1 = Lower Quartile = P 50 = Q2 = Median Quartile = P 75 = Q3 = Upper Quartile = Interquartile Range (IQR) = 1.5* IQR= Value of Lower Fence = Value of Upper Fence = Outliers (if any) below lower fence (LIST) = Outliers (if any) above upper fence (LIST) = Smokers NON-Smokers 5b. In 3-8 sentences at most, write a brief report comparing the cholesterol value distributions of smokers and non-smokers.

CHAPTER 2 Describing Data: Numerical

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

More information

The Standard Deviation as a Ruler and the Normal Model. Copyright 2009 Pearson Education, Inc.

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

More information

UNIVERSITY OF TORONTO SCARBOROUGH Department of Computer and Mathematical Sciences. STAB22H3 Statistics I Duration: 1 hour and 45 minutes

UNIVERSITY OF TORONTO SCARBOROUGH Department of Computer and Mathematical Sciences. STAB22H3 Statistics I Duration: 1 hour and 45 minutes UNIVERSITY OF TORONTO SCARBOROUGH Department of Computer and Mathematical Sciences STAB22H3 Statistics I Duration: 1 hour and 45 minutes Last Name: First Name: Student number: Aids allowed: - One handwritten

More information

appstats5.notebook September 07, 2016 Chapter 5

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.

More information

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 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

More information

Mini-Lecture 3.1 Measures of Central Tendency

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

More information

c) Why do you think the two percentages don't agree? d) Create a histogram of these times. What do you see?

c) Why do you think the two percentages don't agree? d) Create a histogram of these times. What do you see? 1. Payroll. Here are the summary statistics for the weekly payroll of a small company: lowest salary = $300, mean salary = $700, median = $500, range = $1200, IQR = $600, first quartile = $350, standard

More information

Lecture 1: Review and Exploratory Data Analysis (EDA)

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

More information

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. 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

More information

1. The data in the following table represent the number of miles per gallon achieved on the highway for compact cars for the model year 2005.

1. The data in the following table represent the number of miles per gallon achieved on the highway for compact cars for the model year 2005. Millersville University Name Answer Key Department of Mathematics MATH 130, Elements of Statistics I, Test 2 March 5, 2010, 10:00AM-10:50AM Please answer the following questions. Your answers will be evaluated

More information

Some estimates of the height of the podium

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

More information

1 Describing Distributions with numbers

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

More information

Applications of Data Dispersions

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

More information

Chapter 2: Descriptive Statistics. Mean (Arithmetic Mean): Found by adding the data values and dividing the total by the number of data.

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

More information

The Central Limit Theorem: Homework

The Central Limit Theorem: Homework The Central Limit Theorem: Homework EXERCISE 1 X N(60, 9). Suppose that you form random samples of 25 from this distribution. Let X be the random variable of averages. Let X be the random variable of sums.

More information

Section3-2: Measures of Center

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

More information

Exploratory Data Analysis

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

More information

Putting Things Together Part 1

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

More information

Percentiles, STATA, Box Plots, Standardizing, and Other Transformations

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

More information

Romero Catholic Academy Gender Pay Reporting Findings

Romero Catholic Academy Gender Pay Reporting Findings Romero Catholic Academy Gender Pay Reporting Findings March 2018 Introduction In light of the recent Government Regulations regarding Mandatory Gender Pay Gap Reporting, Total Reward Group have been tasked

More information

The Central Limit Theorem: Homework

The Central Limit Theorem: Homework The Central Limit Theorem: Homework EXERCISE 1 X N(60, 9). Suppose that you form random samples of 25 from this distribution. Let X be the random variable of averages. Let X be the random variable of sums.

More information

Chapter 5 The Standard Deviation as a Ruler and the Normal Model

Chapter 5 The Standard Deviation as a Ruler and the Normal Model Chapter 5 The Standard Deviation as a Ruler and the Normal Model 55 Chapter 5 The Standard Deviation as a Ruler and the Normal Model 1. Stats test. Nicole scored 65 points on the test. That is one standard

More information

STOR 155 Practice Midterm 1 Fall 2009

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

More information

Math 2200 Fall 2014, Exam 1 You may use any calculator. You may not use any cheat sheet.

Math 2200 Fall 2014, Exam 1 You may use any calculator. You may not use any cheat sheet. 1 Math 2200 Fall 2014, Exam 1 You may use any calculator. You may not use any cheat sheet. Warning to the Reader! If you are a student for whom this document is a historical artifact, be aware that the

More information

The Range, the Inter Quartile Range (or IQR), and the Standard Deviation (which we usually denote by a lower case s).

The Range, the Inter Quartile Range (or IQR), and the Standard Deviation (which we usually denote by a lower case s). We will look the three common and useful measures of spread. The Range, the Inter Quartile Range (or IQR), and the Standard Deviation (which we usually denote by a lower case s). 1 Ameasure of the center

More information

NOTES: Chapter 4 Describing Data

NOTES: Chapter 4 Describing Data NOTES: Chapter 4 Describing Data Intro to Statistics COLYER Spring 2017 Student Name: Page 2 Section 4.1 ~ What is Average? Objective: In this section you will understand the difference between the three

More information

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Section 6.1 and 6.2 exercises Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) A normal population has a mean μ = 30 and standard deviation

More information

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 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

More information

Descriptive Statistics

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

More information

Numerical Measurements

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

More information

Putting Things Together Part 2

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

More information

The Central Limit Theorem: Homework

The Central Limit Theorem: Homework EERCISE 1 The Central Limit Theorem: Homework N(60, 9). Suppose that you form random samples of 25 from this distribution. Let be the random variable of averages. Let be the random variable of sums. For

More information

Unit 2 Statistics of One Variable

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

More information

Math Take Home Quiz on Chapter 2

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

More information

Lecture 2 Describing Data

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

More information

STAT Chapter 6 The Standard Deviation (SD) as a Ruler and The Normal Model

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

More information

(a) salary of a bank executive (measured in dollars) quantitative. (c) SAT scores of students at Millersville University quantitative

(a) salary of a bank executive (measured in dollars) quantitative. (c) SAT scores of students at Millersville University quantitative Millersville University Name Answer Key Department of Mathematics MATH 130, Elements of Statistics I, Test 1 February 8, 2010, 10:00AM-10:50AM Please answer the following questions. Your answers will be

More information

Wk 2 Hrs 1 (Tue, Jan 10) Wk 2 - Hr 2 and 3 (Thur, Jan 12)

Wk 2 Hrs 1 (Tue, Jan 10) Wk 2 - Hr 2 and 3 (Thur, Jan 12) Wk 2 Hrs 1 (Tue, Jan 10) Wk 2 - Hr 2 and 3 (Thur, Jan 12) Descriptive statistics: - Measures of centrality (Mean, median, mode, trimmed mean) - Measures of spread (MAD, Standard deviation, variance) -

More information

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 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.

More information

SOLUTIONS TO THE LAB 1 ASSIGNMENT

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

More information

Description of Data I

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

More information

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 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

More information

NOTES TO CONSIDER BEFORE ATTEMPTING EX 2C BOX PLOTS

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

More information

Empirical Rule (P148)

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

More information

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] 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

More information

Top Incorrect Problems

Top Incorrect Problems What is the z-score for scores in the bottom 5%? a) -1.645 b) 1.645 c).4801 d) The score is not listed in the table. A professor grades 120 research papers and reports that the average score was an 80%.

More information

1.2 Describing Distributions with Numbers, Continued

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

More information

MgtOp 215 TEST 1 (Golden) Spring 2016 Dr. Ahn. Read the following instructions very carefully before you start the test.

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

More information

Central Limit Theorem: Homework

Central Limit Theorem: Homework Connexions module: m16952 1 Central Limit Theorem: Homework Susan Dean Barbara Illowsky, Ph.D. This work is produced by The Connexions Project and licensed under the Creative Commons Attribution License

More information

STAB22 section 1.3 and Chapter 1 exercises

STAB22 section 1.3 and Chapter 1 exercises STAB22 section 1.3 and Chapter 1 exercises 1.101 Go up and down two times the standard deviation from the mean. So 95% of scores will be between 572 (2)(51) = 470 and 572 + (2)(51) = 674. 1.102 Same idea

More information

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. 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

More information

Unit 2 Measures of Variation

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,

More information

Chapter 3. Lecture 3 Sections

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

More information

4. DESCRIPTIVE STATISTICS

4. DESCRIPTIVE STATISTICS 4. DESCRIPTIVE STATISTICS Descriptive Statistics is a body of techniques for summarizing and presenting the essential information in a data set. Eg: Here are daily high temperatures for Jan 16, 2009 in

More information

MSM Course 1 Flashcards. Associative Property. base (in numeration) Commutative Property. Distributive Property. Chapter 1 (p.

MSM Course 1 Flashcards. Associative Property. base (in numeration) Commutative Property. Distributive Property. Chapter 1 (p. 1 Chapter 1 (p. 26, 1-5) Associative Property Associative Property: The property that states that for three or more numbers, their sum or product is always the same, regardless of their grouping. 2 3 8

More information

1. State whether the following groups are populations or samples. You are encouraged to justify your answers.

1. State whether the following groups are populations or samples. You are encouraged to justify your answers. MATH 2210 Exam 1 Review Solution Note: This review is NOT comprehensive, so do not limit your study to it. 1. State whether the following groups are populations or samples. You are encouraged to justify

More information

Section 6-1 : Numerical Summaries

Section 6-1 : Numerical Summaries MAT 2377 (Winter 2012) Section 6-1 : Numerical Summaries With a random experiment comes data. In these notes, we learn techniques to describe the data. Data : We will denote the n observations of the random

More information

STAT Chapter 6 The Standard Deviation (SD) as a Ruler and The Normal Model

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

More information

Chapter Seven. The Normal Distribution

Chapter Seven. The Normal Distribution Chapter Seven The Normal Distribution 7-1 Introduction Many continuous variables have distributions that are bellshaped and are called approximately normally distributed variables, such as the heights

More information

Terms & Characteristics

Terms & Characteristics NORMAL CURVE Knowledge that a variable is distributed normally can be helpful in drawing inferences as to how frequently certain observations are likely to occur. NORMAL CURVE A Normal distribution: Distribution

More information

Chapter 2. Section 2.1

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

More information

Measures of Center. Mean. 1. Mean 2. Median 3. Mode 4. Midrange (rarely used) Measure of Center. Notation. Mean

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

More information

3) Marital status of each member of a randomly selected group of adults is an example of what type of variable?

3) Marital status of each member of a randomly selected group of adults is an example of what type of variable? MATH112 STATISTICS; REVIEW1 CH1,2,&3 Name CH1 Vocabulary 1) A statistics student wants to find some information about all college students who ride a bike. She collected data from other students in her

More information

STAT 113 Variability

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

More information

Stat 101 Exam 1 - Embers Important Formulas and Concepts 1

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.

More information

POLI 300 PROBLEM SET #7 due 11/08/10 MEASURES OF DISPERSION AND THE NORMAL DISTRIBUTION

POLI 300 PROBLEM SET #7 due 11/08/10 MEASURES OF DISPERSION AND THE NORMAL DISTRIBUTION POLI 300 PROBLEM SET #7 due 11/08/10 MEASURES OF DISPERSION AND THE NORMAL DISTRIBUTION NAME Put all your answers directly on these pages 1. Refer to the continuous frequency density provided with Problem

More information

DATA ANALYSIS EXAM QUESTIONS

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

More information

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 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

More information

Honors Statistics. 3. Discuss homework C2# Discuss standard scores and percentiles. Chapter 2 Section Review day 2016s Notes.

Honors Statistics. 3. Discuss homework C2# Discuss standard scores and percentiles. Chapter 2 Section Review day 2016s Notes. Honors Statistics Aug 23-8:26 PM 3. Discuss homework C2#11 4. Discuss standard scores and percentiles Aug 23-8:31 PM 1 Feb 8-7:44 AM Sep 6-2:27 PM 2 Sep 18-12:51 PM Chapter 2 Modeling Distributions of

More information

SOLUTIONS: DESCRIPTIVE STATISTICS

SOLUTIONS: DESCRIPTIVE STATISTICS SOLUTIONS: DESCRIPTIVE STATISTICS Please note that the data is ordered from lowest value to highest value. This is necessary if you wish to compute the medians and quartiles by hand. You do not have to

More information

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/ /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

More information

Describing Data: One Quantitative Variable

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

More information

Variance, Standard Deviation Counting Techniques

Variance, Standard Deviation Counting Techniques Variance, Standard Deviation Counting Techniques Section 1.3 & 2.1 Cathy Poliak, Ph.D. cathy@math.uh.edu Department of Mathematics University of Houston 1 / 52 Outline 1 Quartiles 2 The 1.5IQR Rule 3 Understanding

More information

Test Bank Elementary Statistics 2nd Edition William Navidi

Test Bank Elementary Statistics 2nd Edition William Navidi Test Bank Elementary Statistics 2nd Edition William Navidi Completed downloadable package TEST BANK for Elementary Statistics 2nd Edition by William Navidi, Barry Monk: https://testbankreal.com/download/elementary-statistics-2nd-edition-test-banknavidi-monk/

More information

Statistics I Final Exam, 24 June Degrees in ADE, DER-ADE, ADE-INF, FICO, ECO, ECO-DER.

Statistics I Final Exam, 24 June Degrees in ADE, DER-ADE, ADE-INF, FICO, ECO, ECO-DER. Statistics I Final Exam, June. Degrees in ADE, DER-ADE, ADE-INF, FICO, ECO, ECO-DER. EXAM RULES: Use separate booklets for each problem. Perform the calculations with at least two significant decimal places.

More information

Week 1 Variables: Exploration, Familiarisation and Description. Descriptive Statistics.

Week 1 Variables: Exploration, Familiarisation and Description. Descriptive Statistics. Week 1 Variables: Exploration, Familiarisation and Description. Descriptive Statistics. Convergent validity: the degree to which results/evidence from different tests/sources, converge on the same conclusion.

More information

Distributions and their Characteristics

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

More information

Numerical Descriptions of Data

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 =

More information

Lecture Week 4 Inspecting Data: Distributions

Lecture Week 4 Inspecting Data: Distributions Lecture Week 4 Inspecting Data: Distributions Introduction to Research Methods & Statistics 2013 2014 Hemmo Smit So next week No lecture & workgroups But Practice Test on-line (BB) Enter data for your

More information

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Exam Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) Use the Central Limit Theorem to find the indicated probability. The sample size is n,

More information

Random variables The binomial distribution The normal distribution Other distributions. Distributions. Patrick Breheny.

Random variables The binomial distribution The normal distribution Other distributions. Distributions. Patrick Breheny. Distributions February 11 Random variables Anything that can be measured or categorized is called a variable If the value that a variable takes on is subject to variability, then it the variable is a random

More information

SMAM 345 Exam 1 Name. 1. The following data represent the number of miles per gallon achieved on the highway for small cars for the model year 2008.

SMAM 345 Exam 1 Name. 1. The following data represent the number of miles per gallon achieved on the highway for small cars for the model year 2008. SMAM 34 Exam 1 Name 1. The following data represent the number of miles per gallon achieved on the highway for small cars for the model year 2008. 33 26 33 32 31 3 33 3 32 32 3 30 36 31 23 29 29 34 28

More information

MATH 217 Test 2 Version A

MATH 217 Test 2 Version A MATH 217 Test 2 Version A Name: KEY Sec Number: Answer all questions to the best of your ability. Note you should show as much work as is possible. For questions answered using Excel be sure to include

More information

Center and Spread. Measures of Center and Spread. Example: Mean. Mean: the balance point 2/22/2009. Describing Distributions with Numbers.

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

More information

Standardized Data Percentiles, Quartiles and Box Plots Grouped Data Skewness and Kurtosis

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

More information

Example - Let X be the number of boys in a 4 child family. Find the probability distribution table:

Example - Let X be the number of boys in a 4 child family. Find the probability distribution table: Chapter8 Probability Distributions and Statistics Section 8.1 Distributions of Random Variables tthe value of the result of the probability experiment is a RANDOM VARIABLE. Example - Let X be the number

More information

2CORE. Summarising numerical data: the median, range, IQR and box plots

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

More information

DATA SUMMARIZATION AND VISUALIZATION

DATA SUMMARIZATION AND VISUALIZATION APPENDIX DATA SUMMARIZATION AND VISUALIZATION PART 1 SUMMARIZATION 1: BUILDING BLOCKS OF DATA ANALYSIS 294 PART 2 PART 3 PART 4 VISUALIZATION: GRAPHS AND TABLES FOR SUMMARIZING AND ORGANIZING DATA 296

More information

Solutions for practice questions: Chapter 9, Statistics

Solutions for practice questions: Chapter 9, Statistics Solutions for practice questions: Chapter 9, Statistics If you find any errors, please let me know at mailto:msfrisbie@pfrisbie.com. 1. We know that µ is the mean of 30 values of y, 30 30 i= 1 2 ( y i

More information

2 Exploring Univariate Data

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

More information

Simple Descriptive Statistics

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

More information

Name PID Section # (enrolled)

Name PID Section # (enrolled) STT 315 - Lecture 3 Instructor: Aylin ALIN 02/19/2014 Midterm # 1 A Name PID Section # (enrolled) * The exam is closed book and 80 minutes. * You may use a calculator and the formula sheet that you brought

More information

Dot Plot: A graph for displaying a set of data. Each numerical value is represented by a dot placed above a horizontal number line.

Dot Plot: A graph for displaying a set of data. Each numerical value is represented by a dot placed above a horizontal number line. Introduction We continue our study of descriptive statistics with measures of dispersion, such as dot plots, stem and leaf displays, quartiles, percentiles, and box plots. Dot plots, a stem-and-leaf display,

More information

Monte Carlo Simulation (Random Number Generation)

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...

More information

Frequency Distribution and Summary Statistics

Frequency Distribution and Summary Statistics Frequency Distribution and Summary Statistics Dongmei Li Department of Public Health Sciences Office of Public Health Studies University of Hawai i at Mānoa Outline 1. Stemplot 2. Frequency table 3. Summary

More information

Chapter 4 and Chapter 5 Test Review Worksheet

Chapter 4 and Chapter 5 Test Review Worksheet Name: Date: Hour: Chapter 4 and Chapter 5 Test Review Worksheet You must shade all provided graphs, you must round all z-scores to 2 places after the decimal, you must round all probabilities to at least

More information

Measures of Central Tendency Lecture 5 22 February 2006 R. Ryznar

Measures of Central Tendency Lecture 5 22 February 2006 R. Ryznar Measures of Central Tendency 11.220 Lecture 5 22 February 2006 R. Ryznar Today s Content Wrap-up from yesterday Frequency Distributions The Mean, Median and Mode Levels of Measurement and Measures of Central

More information

Math146 - Chapter 3 Handouts. The Greek Alphabet. Source: Page 1 of 39

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

More information

Chapter 6. y y. Standardizing with z-scores. Standardizing with z-scores (cont.)

Chapter 6. y y. Standardizing with z-scores. Standardizing with z-scores (cont.) Starter Ch. 6: A z-score Analysis Starter Ch. 6 Your Statistics teacher has announced that the lower of your two tests will be dropped. You got a 90 on test 1 and an 85 on test 2. You re all set to drop

More information

The Central Limit Theorem for Sample Means (Averages)

The Central Limit Theorem for Sample Means (Averages) The Central Limit Theorem for Sample Means (Averages) By: OpenStaxCollege Suppose X is a random variable with a distribution that may be known or unknown (it can be any distribution). Using a subscript

More information