PSYC 200 Statistical Methods in Psychology
|
|
- Zoe Thompson
- 6 years ago
- Views:
Transcription
1 1 PSYC 200 Statistical Methods in Psychology Summer Session II Meets 07/13/04-08/19/04 Tu - Th 5:00pm-8:20pm (BPS 1124) Instructor: Walky Rivadeneira TA: Susan Campbell The course will Improve your ability to make choices under uncertainty Provide a foundation in statistical thinking and practice Combination of mathematics, psychology, and logic Study regularly and actively Do all the exercises in the main text Expect to study 4-6 hrs/week or more outside of class Homework is required and must be on time Homework and Answer Sheets will be posted on the web Attendance at lab and lecture is expected Class web page: See Syllabus
2 2 What will happen in Psyc200? You will develop skills and abilities in how to reason effectively with data Topics include: How to describe/summarize data (descriptive statistics) How the process of making statistical inferences works (probability, inferential statistics) How to correctly use and interpret statistical techniques and procedures (depends on research question) Why statistics? Science and practice of psychology is entirely dependent on a probabilistic view of human behavior scientists use statistics as an inferential tool! Information in the media is often presented in quantitative/statistical terms Even if you don t use statistics in your everyday life, (but many of you will!), decision-makers affecting your life will! Learn to be skeptical!
3 3 There are three kind of lies: lies, damned lies, and statistics. -Disraeli STABLE GOVERNMENT PAY ROLLS UP! $20,000, $19,500,000 Millions of Dollars June July Aug Sep Oct Nov Dec 0 June July Aug Sep Oct Nov Dec
4 4 How to lie with statistics LAST YEAR Milk $3.00 Bread $2.00 THIS YEAR Milk $1.50 Bread $ COST OF LIVING UP Last year as base period last year 200 this year COST OF LIVING DOWN This year as base period last year 200 this year COST OF LIVING STABLE Last year as base period AND Use geometric mean last year this year What Would You Do? (Chance, 2002,Vol15, No 15, p. 3) In June, 2002, challenger Eric Perrodin beat Mayor Omar Bradley in Compton, CA, by 281 votes Mistakenly, Perrodin s name had been first on all ballots Bradley called in Prof. John Krosnick, whose research suggests that the first-listed candidate on the ballot receives about 2.5% more votes than the last-listed On that basis, Perrodin got 306 more votes than if his name had appeared last The judge took 306 votes from Perrodin and gave them to Bradley, declaring him the winner Appeal is in process
5 5 Definitions STATISTICS: A method for dealing with data; a tool for organizing and analyzing numerical facts or observations DATA: A collection of measurements or observations (FYI - data is a plural term; datum is the singular) Population POPULATION: The collection of all people, objects, events, or observations sharing one or more specified characteristics The size of the population may be very large or relatively small. The size is dependent on the defining characteristics established by the research Examples All introductory statistics students All registered voters All babies born in 1997
6 6 Sample SAMPLE: A subset of individuals selected from a population, usually intended to reflect or represent the population in a study Used because collecting observations from an entire population is usually time-consuming, costly, impractical and/or unfeasible Sample sizes can vary greatly, just as population sizes do. Examples of samples: All statistics students in your class Registered voters in Montgomery county Babies born at Shady Grove hospital When describing data, it is useful to distinguish whether the data come from a population or a sample -- is it a parameter or a statistic? PARAMETER: A value that describes a characteristic of a population Example: The average height of of the entire UMD student population USE GREEK LETTERS STATISTIC: A value that describes a characteristic of a sample Example: The average height of the members of this class USE ROMAN LETTERS
7 7 SAMPLING ERROR: The discrepancy, or difference, between a sample statistic and the corresponding population parameter Example: The difference that exists between the performance of 300 UMD males and females and the performance of all UMD students. Variables Vs. Constants VARIABLE: A characteristic that takes on different values for different individuals in a population or a sample; something that varies Examples: Height - GPA IQ - hair color CONSTANT: A characteristic that does not change its value in a given context Examples: Days in a week - sample size
8 8 Discrete vs. Continuous Variables DISCRETE VARIABLE: A variable that consists of separate, indivisible categories; can assume only a finite number of values between any two points a.k.a. Categorical or Qualitative variables No values can exist between the categories Examples: Gender, religious affiliation, number of children in a family CONTINUOUS VARIABLE: A variable where there are an infinite number of possible values that fall between any 2 observed values a.k.a. Quantitative or Numeric variables Can be pictured as a number line without gaps between neighboring points Examples: Family income, test scores, weight Independent vs. Dependent Variables INDEPENDENT VARIABLE: a.k.a. I.V. A variable that is examined in order to determine its effects on an outcome of interest Often (but not always) manipulated by the researcher Consists of at least two levels, or categories DEPENDENT VARIABLE: a.k.a. D.V. An outcome of interest that is being observed and measured in order to assess the effects of the independent variable The actual observations or measurements that you record
9 9 Independent vs. Dependent Variables A researcher wants to identify the effects of sleep deprivation test performances in his introductory statistics course. He studies 2 groups of students. One group is instructed to stay awake for 2 nights and days and the other group is told to sleep normally. The exam scores of a test given after the 2-day period are recorded. What is the independent variable? What is the dependent variable? Independent vs. Dependent Variables The independent variable is sleep deprivation (the researcher is interested in the effects of this variable on the dependent variable - this is what the researcher is manipulating). There are two levels of this variable -- 1) the presence of deprivation, 2) the absence of deprivation The dependent variable is test performance. This is what is being measured by the researcher in terms of exam scores. The scores are presumed to have been influenced by the manipulation of the I.V. It may be useful to identify independent and dependent variables using the following phrase: The effects of IV on DV. Thus, in the previous example we could state, The effects of sleep deprivation on test performance.
10 10 Two Basic Areas of Statistics 1) DESCRIPTIVE STATISTICS: used to summarize, organize, and present data in a convenient and communicable form. Example: Summarize exam scores by reporting an average score for the class Summarize age by reporting the range of ages (i.e., The subjects ranged in age from 17-38) 2) INFERENTIAL STATISTICS: techniques that allow us to make inferences or conclusions about a population based on data that are gathered from a sample Example: The academic performance of 150 females and 150 males from UMD are examined. The information provided by these 300 students is then used to draw conclusions about performance for all UMD students. Levels of Measurement MEASUREMENT: The process of assigning numbers to objects or events according to a set of rules There are 4 levels (or scales) of measurement Nominal Ordinal Interval Ratio
11 11 Levels of Measurement NOMINAL SCALE: Classify observations into mutually exclusive and exhaustive categories No attempt is made to measure magnitude or amount; only distinguishes between groups Observations of unordered variables Examples: gender, political affiliation, county of residence Levels of Measurement ORDINAL SCALE: Observations are rank ordered in terms of size or magnitude One group can be greater than or less than another group Does not tell how much difference there is between groups; it only identifies a direction of difference Example: letter grades A, B, C, D, F -- the students are rankordered in terms of class standing, but the magnitude of the difference in grades between students is not identified
12 12 Levels of Measurement INTERVAL SCALE: A quantitative scale that requires a constant unit of measurement; intervals between numbers are equal in size Allows for addition, subtraction and other mathematical operations The 0-point is arbitrary - a value of 0 does not necessarily mean the absence of that quality Example: The Fahrenheit scale of measuring temperature -- the difference between 30 and 31 degrees is 1 degree, as is the difference between 95 and 96 degrees; a temperature of 0 does not indicate a lack of temperature Levels of Measurement RATIO SCALE: Similar to interval scale except that the 0-point is absolute - a zero value reflects an absence of the quality we are measuring Allows the use of ratios when comparing numbers - you can have twice as much of that variable or 1/2 as much (you can t do this with interval scale values) This is the most common level of measurement Example: weight - 0 pounds means that object has no weight; a weight of 160 pounds is twice as much as a weight of 80 pounds
13 13 Organizing and Displaying Data Data by themselves are just numbers Here are the final raw exam scores from 2 classes, 25 students randomly assigned to each, comparing a new and an old method of teaching algebra. How can we make sense of them? New Method Old Method Ranking the data New Method Old Method What features of the data are suggested? Old method yields greater variability Equal performance in old and new group does not indicate equal relative performance Need to look at ranks and percentile scores
14 14 Frequency Distributions FREQUENCY DISTRIBUTION: An organization of data indicating the number of people that obtain a certain score or fell in a certain category Can either be in the form of tables or graphs Help to provide us with a visual picture of how the scores are spread out across a measurement scale FREQUENCY DISTRIBUTION TABLES: The simplest frequency distributions list a column of scores (x s) and then the frequency, or the number of times that score occurs (f), beside it FREQUENCY DISTRIBUTION TABLES New n- Old Method f RMethod f N Scores are listed from lowest to highest Freq = count of observations with same value The sum of the f column should be equal to n (the number of subjects in your sample)
15 15 FREQUENCY DISTRIBUTION TABLES (cont) New Method f Rel f N 25 =1.00 n- Old Method f Rel f =1.00 In addition to x and f, we can add a relative frequency (Rel f) column. This column tells us the score s frequency relative to the total population size (N) Relative Frequency= f/n The sum of the Rel f column should equal 1.00 FREQUENCY DISTRIBUTION TABLES (cont) New Cum n- Old Cum Method f Rel f f Method f Rel f f N Additional columns may be added to a grouped frequency table: CUMULATIVE FREQUENCIES (Cum f): The number of people/scores who are in or below each class interval; represents the accumulation of individuals as you go up the scale The last value in the Cum f column should reflect the number of subjects that you have (n)
16 16 FREQUENCY DISTRIBUTION TABLES (cont) New Cum Cumn- Old Cum Cum Method f Rel f f Rel f Method f Rel f f Rel f N CUMULATIVE RELATIVE FREQUENCIES (Cum Rel f): The relative frequency of people/scores who are in or below each class interval; represents the accumulation of percentages as you go up the scale The last value in the Cum Rel f column should be 1.00 FREQUENCY DISTRIBUTION TABLES (cont) New Cum Cum Percentile Old Cum Cum Method f Rel f f Rel f Method f Rel f f Rel f Percentile N PERCENTILE: The percentage of individuals who are located at or below the upper real limit of each interval Percentile = (cf/n)(100) The last value in the Percentile column should be 100
17 17 FREQUENCY DISTRIBUTION TABLES (cont) New Cum Cum Percentile Old Cum Cum Percen- Method f Rel f f Rel f Method f Rel f f Rel f tile N The data are somewhat grouped Still cannot form visual impressions Divide into larger classes Freq = count of observations Cumulative Rel. frequency = (Cum f)/n with same value Percentile = 100(Cum f)/n Relative frequency = f/n Cumulative freq = sum of accumulated freq GROUPED FREQUENCY DISTRIBUTIONS: We can further simplify data by grouping scores together into intervals and presenting them in a table INTERVALS / CLASS INTERVALS: Groups of scores; Class intervals have real limits, reflecting the continuous nature of the variable these intervals have real limits REAL LIMITS: are used to separate adjacent scores or intervals exactly halfway between the scores; are always halfway between adjacent intervals; neighboring intervals share a real limit
18 18 Grouped Frequency Distribution Example: On an ungrouped continuous scale, a score of 94 has a lower real limit of 93.5 and an upper real limit of 94.5 On grouped frequency distribution, a score of 94 may be in the interval 90-99, which has a lower real limit of 89.5 and an upper real limit of 99.5 Why real limits? The real limits of the intervals should be impossible scores, so that every score falls in exactly one interval Frequency Histograms Form roughly equal intervals of scores Interval New Method Old Method N Real limits Etc. Frequency Frequency Histogram New Method Old Method Score
Statistics and Quantitative Analysis U4320. Segment 8 Prof. Sharyn O Halloran
Statistics and Quantitative Analysis U4320 Segment 8 Prof. Sharyn O Halloran I. Introduction A. Overview 1. Ways to describe, summarize and display data. 2.Summary statements: Mean Standard deviation Variance
More informationWHITE PAPER. Preventing Collisions and Reducing Fleet Costs While Using the Zendrive Dashboard
WHITE PAPER Preventing Collisions and Reducing Fleet Costs While Using the Zendrive Dashboard August 2017 Introduction The term accident, even in a collision sense, often has the connotation of being an
More informationBusy Ant Maths and the Scottish Curriculum for Excellence Foundation Level - Primary 1
Busy Ant Maths and the Scottish Curriculum for Excellence Foundation Level - Primary 1 Number, money and measure Estimation and rounding Number and number processes Fractions, decimal fractions and percentages
More informationDescriptive Statistics
Chapter 2 Descriptive Statistics 2-1 Overview 2-2 Summarizing Data 2-3 Pictures of Data 2-4 Measures of Central Tendency 2-5 Measures of Variation 2-6 Measures of Position 2-7 Exploratory Data Analysis
More informationHoughton Mifflin MATHEMATICS. Level 1 correlated to Chicago Academic Standards and Framework Grade 1
State Goal 6: Demonstrate and apply a knowledge and sense of numbers, including basic arithmetic operations, number patterns, ratios and proportions. CAS A. Relate counting, grouping, and place-value concepts
More informationLinking the Alaska AMP Assessments to NWEA MAP Tests
Linking the Alaska AMP Assessments to NWEA MAP Tests February 2016 Introduction Northwest Evaluation Association (NWEA ) is committed to providing partners with useful tools to help make inferences from
More informationCorrelation to the Common Core State Standards
Correlation to the Common Core State Standards Go Math! 2011 Grade 3 Common Core is a trademark of the National Governors Association Center for Best Practices and the Council of Chief State School Officers.
More informationLinking the New York State NYSTP Assessments to NWEA MAP Growth Tests *
Linking the New York State NYSTP Assessments to NWEA MAP Growth Tests * *As of June 2017 Measures of Academic Progress (MAP ) is known as MAP Growth. March 2016 Introduction Northwest Evaluation Association
More information2018 Linking Study: Predicting Performance on the NSCAS Summative ELA and Mathematics Assessments based on MAP Growth Scores
2018 Linking Study: Predicting Performance on the NSCAS Summative ELA and Mathematics Assessments based on MAP Growth Scores November 2018 Revised December 19, 2018 NWEA Psychometric Solutions 2018 NWEA.
More informationLinking the Kansas KAP Assessments to NWEA MAP Growth Tests *
Linking the Kansas KAP Assessments to NWEA MAP Growth Tests * *As of June 2017 Measures of Academic Progress (MAP ) is known as MAP Growth. February 2016 Introduction Northwest Evaluation Association (NWEA
More informationInstitutional Research and Planning 440 Day Hall Ithaca, New York PULSE Survey
Institutional Research and Planning 440 Day Hall Ithaca, New York 14853 2009 PULSE Survey The Cornell PULSE (Perceptions of Undergraduate Life and Student Experiences) Survey asks currently enrolled undergraduate
More informationLinking the North Carolina EOG Assessments to NWEA MAP Growth Tests *
Linking the North Carolina EOG Assessments to NWEA MAP Growth Tests * *As of June 2017 Measures of Academic Progress (MAP ) is known as MAP Growth. March 2016 Introduction Northwest Evaluation Association
More informationLinking the Georgia Milestones Assessments to NWEA MAP Growth Tests *
Linking the Georgia Milestones Assessments to NWEA MAP Growth Tests * *As of June 2017 Measures of Academic Progress (MAP ) is known as MAP Growth. February 2016 Introduction Northwest Evaluation Association
More informationAcademic Course Description
BEE305- ELECTRICAL MACHINES Academic Course Description BHARATH UNIVERSITY Faculty of Engineering and Technology Department of Electrical and Electronics Engineering BEE305- ELECTRICAL MACHINES Third Semester,
More informationLinking the Virginia SOL Assessments to NWEA MAP Growth Tests *
Linking the Virginia SOL Assessments to NWEA MAP Growth Tests * *As of June 2017 Measures of Academic Progress (MAP ) is known as MAP Growth. March 2016 Introduction Northwest Evaluation Association (NWEA
More informationLinking the Mississippi Assessment Program to NWEA MAP Tests
Linking the Mississippi Assessment Program to NWEA MAP Tests February 2017 Introduction Northwest Evaluation Association (NWEA ) is committed to providing partners with useful tools to help make inferences
More informationLinking the Florida Standards Assessments (FSA) to NWEA MAP
Linking the Florida Standards Assessments (FSA) to NWEA MAP October 2016 Introduction Northwest Evaluation Association (NWEA ) is committed to providing partners with useful tools to help make inferences
More informationBusy Ant Maths and the Scottish Curriculum for Excellence Year 6: Primary 7
Busy Ant Maths and the Scottish Curriculum for Excellence Year 6: Primary 7 Number, money and measure Estimation and rounding Number and number processes Including addition, subtraction, multiplication
More informationFourth Grade. Multiplication Review. Slide 1 / 146 Slide 2 / 146. Slide 3 / 146. Slide 4 / 146. Slide 5 / 146. Slide 6 / 146
Slide 1 / 146 Slide 2 / 146 Fourth Grade Multiplication and Division Relationship 2015-11-23 www.njctl.org Multiplication Review Slide 3 / 146 Table of Contents Properties of Multiplication Factors Prime
More informationYour web browser (Safari 7) is out of date. For more security, comfort and. the best experience on this site: Update your browser Ignore
Your web browser (Safari 7) is out of date. For more security, comfort and Activitydevelop the best experience on this site: Update your browser Ignore Circuits with Friends What is a circuit, and what
More informationCourse Syllabus
John D. Rockefeller Truck Driver Training Program Course Syllabus 2013-14 INSTRUCTOR: John Barber, Tim Egyud CLASSROOM: JDRCC DOOR 6 OFFICE HRS: 7:00-2:00 M-F OFFICE PH: 304-564-3337 extension 118 MOBILE
More informationNSSE 2017 U.S. Summary Frequencies
1. During the current school year, about how often have you done the following? a. Asked questions or askquest Never 187 2 495 4 310 4 348 3 529 3 98 3 191 2 413 4 572 3 188 3 3,702 3 contributed to course
More informationPassenger seat belt use in Durham Region
Facts on Passenger seat belt use in Durham Region June 2017 Highlights In 2013/2014, 85 per cent of Durham Region residents 12 and older always wore their seat belt when riding as a passenger in a car,
More informationComparing Percentages of Iditarod Finishers
Comparing Percentages of Iditarod Finishers Developed by: Brian Hickox, 2019 Iditarod Teacher on the Trail Discipline / Subject: Math Topic: Analyze and Solve Percent Problems Grade Level: 6, 7, 8 Resources
More informationUnderstanding Traffic Data: How To Avoid Making the Wrong Turn
Traffic Records Forum 2011 Understanding Traffic Data: How To Avoid Making the Wrong Turn Presenter: Marc Starnes (202) 366-2186 marc.starnes@dot.gov August 3rd, 2011 1 Summary of Topics Police Crash Reports
More information9.3 Tests About a Population Mean (Day 1)
Bellwork In a recent year, 73% of first year college students responding to a national survey identified being very well off financially as an important personal goal. A state university finds that 132
More informationMissouri Learning Standards Grade-Level Expectations - Mathematics
A Correlation of 2017 To the Missouri Learning Standards - Mathematics Kindergarten Grade 5 Introduction This document demonstrates how Investigations 3 in Number, Data, and Space, 2017, aligns to, Grades
More informationFourth Grade. Slide 1 / 146. Slide 2 / 146. Slide 3 / 146. Multiplication and Division Relationship. Table of Contents. Multiplication Review
Slide 1 / 146 Slide 2 / 146 Fourth Grade Multiplication and Division Relationship 2015-11-23 www.njctl.org Table of Contents Slide 3 / 146 Click on a topic to go to that section. Multiplication Review
More informationUniversity Of California, Berkeley Department of Mechanical Engineering. ME 131 Vehicle Dynamics & Control (4 units)
CATALOG DESCRIPTION University Of California, Berkeley Department of Mechanical Engineering ME 131 Vehicle Dynamics & Control (4 units) Undergraduate Elective Syllabus Physical understanding of automotive
More informationGains in Written Communication Among Learning Habits Students: A Report on an Initial Assessment Exercise
Gains in Written Communication Among Learning Habits Students: A Report on an Initial Assessment Exercise The following pages provide a brief overview of an assessment exercise focusing on a small set
More information2018 Linking Study: Predicting Performance on the Performance Evaluation for Alaska s Schools (PEAKS) based on MAP Growth Scores
2018 Linking Study: Predicting Performance on the Performance Evaluation for Alaska s Schools (PEAKS) based on MAP Growth Scores June 2018 NWEA Psychometric Solutions 2018 NWEA. MAP Growth is a registered
More informationMissouri Seat Belt Usage Survey for 2017
Missouri Seat Belt Usage Survey for 2017 Conducted for the Highway Safety & Traffic Division of the Missouri Department of Transportation by The Missouri Safety Center University of Central Missouri Final
More informationResidential Load Profiles
Residential Load Profiles TABLE OF CONTENTS PAGE 1 BACKGROUND... 1 2 DATA COLLECTION AND ASSUMPTIONS... 1 3 ANALYSIS AND RESULTS... 2 3.1 Load Profiles... 2 3.2 Calculation of Monthly Electricity Bills...
More informationNetLogo and Multi-Agent Simulation (in Introductory Computer Science)
NetLogo and Multi-Agent Simulation (in Introductory Computer Science) Matthew Dickerson Middlebury College, Vermont dickerso@middlebury.edu Supported by the National Science Foundation DUE-1044806 http://ccl.northwestern.edu/netlogo/
More informationLinking the Indiana ISTEP+ Assessments to NWEA MAP Tests
Linking the Indiana ISTEP+ Assessments to NWEA MAP Tests February 2017 Introduction Northwest Evaluation Association (NWEA ) is committed to providing partners with useful tools to help make inferences
More informationWho has trouble reporting prior day events?
Vol. 10, Issue 1, 2017 Who has trouble reporting prior day events? Tim Triplett 1, Rob Santos 2, Brian Tefft 3 Survey Practice 10.29115/SP-2017-0003 Jan 01, 2017 Tags: missing data, recall data, measurement
More informationGrade 3: Houghton Mifflin Math correlated to Riverdeep Destination Math
1 : correlated to Unit 1 Chapter 1 Uses of Numbers 4A 4B, 4 5 Place Value: Ones, Tens, and Hundreds 6A 6B, 6 7 How Big is One Thousand? 8A 8B, 8 9 Place Value Through Thousands 10A 10B, 10 11, 12 13 Problem-Solving
More informationLiberals Lead in Ontario
FOR IMMEDIATE RELEASE Liberals Lead in Ontario Headed for majority government MAY 13 th, 2014 In a random sampling of public opinion taken by the Forum Poll among 996 Ontario voters, close to 4 in 10 will
More informationProfessor Dr. Gholamreza Nakhaeizadeh. Professor Dr. Gholamreza Nakhaeizadeh
Statistic Methods in in Data Mining Business Understanding Data Understanding Data Preparation Deployment Modelling Evaluation Data Mining Process (Part 2) 2) Professor Dr. Gholamreza Nakhaeizadeh Professor
More informationGENERAL CHEMISTRY. Sub-disciplines of Chemistry. Course Organization. Course Organization: People. What You Need for Lecture
GENERAL CHEMISTRY Welcome! Sub-disciplines of Chemistry Physical Q: What is chemistry? Organic Inorganic The study of the composition, properties, and reactions of all types of matter Analytical Biochemistry
More informationLecture 3: Measure of Central Tendency
Lecture 3: Measure of Central Tendency Donglei Du (ddu@unb.edu) Faculty of Business Administration, University of New Brunswick, NB Canada Fredericton E3B 9Y2 Donglei Du (UNB) ADM 2623: Business Statistics
More informationAbstract. Executive Summary. Emily Rogers Jean Wang ORF 467 Final Report-Middlesex County
Emily Rogers Jean Wang ORF 467 Final Report-Middlesex County Abstract The purpose of this investigation is to model the demand for an ataxi system in Middlesex County. Given transportation statistics for
More informationAlgebra 2 Plus, Unit 10: Making Conclusions from Data Objectives: S- CP.A.1,2,3,4,5,B.6,7,8,9; S- MD.B.6,7
Algebra 2 Plus, Unit 10: Making Conclusions from Data Objectives: S- CP.A.1,2,3,4,5,B.6,7,8,9; S- MD.B.6,7 Learner Levels Level 1: I can simulate an experiment. Level 2: I can interpret two- way tables.
More informationUNIVERSITY STUDY PROGRAMME: PROMET. Syllabus. Academic Year 2018/2019. Lectures (L): 30 hours
UNIVRSITY STUDY PROGRAMM: PROMT Syllabus Academic Year 018/019 Title of the Course: Railway Traffic Technology The course is conducted in nglish. Co-ordinator: prof.dr.sc. Associate teachers: asst. prof.,
More informationPros and cons of hybrid cars
GRADE 7 Hybrid cars are increasingly popular. In this lesson, students investigate the costs and benefits of using hybrid cars over gasoline-powered cars by comparing the cost and environmental impact
More informationGRADE 7 TEKS ALIGNMENT CHART
GRADE 7 TEKS ALIGNMENT CHART TEKS 7.2 extend previous knowledge of sets and subsets using a visual representation to describe relationships between sets of rational numbers. 7.3.A add, subtract, multiply,
More information2018 Linking Study: Predicting Performance on the TNReady Assessments based on MAP Growth Scores
2018 Linking Study: Predicting Performance on the TNReady Assessments based on MAP Growth Scores May 2018 NWEA Psychometric Solutions 2018 NWEA. MAP Growth is a registered trademark of NWEA. Disclaimer:
More informationSafety and Preventitive Cautions for Teenage Drivers
Safety and Preventitive Cautions for Teenage Drivers 1. Review the basic safety rules of driving 2. Learn and comprehend the safety issues involved in driving 3. Understand what factors affect safe driving
More informationInvestigating the Concordance Relationship Between the HSA Cut Scores and the PARCC Cut Scores Using the 2016 PARCC Test Data
Investigating the Concordance Relationship Between the HSA Cut Scores and the PARCC Cut Scores Using the 2016 PARCC Test Data A Research Report Submitted to the Maryland State Department of Education (MSDE)
More information2009 Community College of Student Engagement (CCSSE) College Results: Frequency Distributions
2009 Community College of Student Engagement (CCSSE) College Results: Frequency Distributions Institutional Research & Effectiveness Frequency Distributions This report summarizes the observed frequencies
More informationTransportation Issues Poll New York City Speed Safety Cameras in School Zones
2016-17 Transportation Issues Poll New York City Speed Safety Cameras in School Zones Summary Near universal support for more speed safety cameras. New Yorker City voters overwhelmingly support more speed
More informationIndustrial Maintenance Technology Student Learning Outcomes
Industrial Maintenance Technology Student Learning Outcomes February, 2017 ~ f ) FDTC Curriculum Map Program: Industrial Maintenance Technology Course# Course Title Credits Hours Lecture Lab Program Outcomes
More informationRelating your PIRA and PUMA test marks to the national standard
Relating your PIRA and PUMA test marks to the national standard We have carried out a detailed statistical analysis between the results from the PIRA and PUMA tests for Year 2 and Year 6 and the scaled
More informationRelating your PIRA and PUMA test marks to the national standard
Relating your PIRA and PUMA test marks to the national standard We have carried out a detailed statistical analysis between the results from the PIRA and PUMA tests for Year 2 and Year 6 and the scaled
More informationKEY STAGE. Level threshold tables and age standardised scores for key stage 2 tests in English, mathematics and science KEY STAGE KEY STAGE KEY STAGE
KEY STAGE 2 2003 2003 Level threshold tables and age standardised scores for key stage 2 tests in English, mathematics and science This booklet provides: tables for converting test marks into national
More informationMath 135 S18 Exam 1 Review. The Environmental Protection Agency records data on the fuel economy of many different makes of cars.
Math 135 S18 Exam 1 Review Name *note: In addition to this Review, study the material from Take Home Assignments, Classwork sheets and class notes. ALL are represented in the exam. The Environmental Protection
More informationVehicle Scrappage and Gasoline Policy. Online Appendix. Alternative First Stage and Reduced Form Specifications
Vehicle Scrappage and Gasoline Policy By Mark R. Jacobsen and Arthur A. van Benthem Online Appendix Appendix A Alternative First Stage and Reduced Form Specifications Reduced Form Using MPG Quartiles The
More informationObjectives. Materials TI-73 CBL 2
. Objectives To understand the relationship between dry cell size and voltage Activity 4 Materials TI-73 Unit-to-unit cable Voltage from Dry Cells CBL 2 Voltage sensor New AAA, AA, C, and D dry cells Battery
More informationModule: Mathematical Reasoning
Module: Mathematical Reasoning Lesson Title: Speeding Along Objectives and Standards Students will: Determine whether a relationship is a function Calculate the value of a function through a real-world
More informationWIM #41 CSAH 14, MP 14.9 CROOKSTON, MINNESOTA APRIL 2014 MONTHLY REPORT
WIM #41 CSAH 14, MP 14.9 CROOKSTON, MINNESOTA APRIL 2014 MONTHLY REPORT In order to understand the vehicle classes and groupings, the MnDOT Vehicle Classification Scheme and the Vehicle Classification
More informationBCSSE Institutional Report Frequency Distributions. St. Olaf College
BCSSE Institutional Report Frequency Distributions BCSSE Frequency Distributions Interpreting Frequency Results 5 6 1 3 2 4 7 8 1. Variables : The items from the BCSSE survey appear in the left column
More informationELEC 585/462 MOTOR DRIVE DYNAMICS COURSE OUTLINE & ASSESSMENT TECHNIQUES SEPT- DEC / FALL 2013 CRN 11254/11246
ELEC 585/462 MOTOR DRIVE DYNAMICS COURSE OUTLINE & ASSESSMENT TECHNIQUES SEPT- DEC / FALL 2013 CRN 11254/11246 Instructor: Office Hours: Dr. S. Nandi Days: Any time by appointment Phone: 721-8679 Location:
More informationScholastic s Early Childhood Program correlated to the Kentucky Primary English/Language Arts Standards
Primary English/Language Arts Reading (1.2) Arts and Humanities (2.24, 2.25) Students develop abilities to apply appropriate reading strategies to make sense of a variety of print and nonprint texts (literary,
More informationPREPARING YOUR PITCH. Arnold Chen, Managing Director Burton D. Morgan Center for Entrepreneurship
PREPARING YOUR PITCH Arnold Chen, Managing Director Burton D. Morgan Center for Entrepreneurship OUTLINE Before your pitch The Pitch After your pitch Fun real examples WHAT IS YOUR GOAL? WHY ARE YOU MEETING?
More informationCertificate in a vocational program
N 3,328 5,148 2,928 3,219 3,546 2,004 3,730 3,982 2,327 30,212 GOALS AND PLANS 2. What is your educational goal at this college? High school diploma or GED 1.9 1.3 2.2 1.4 2.2 2.2 1.9 2.0 1.7 1.8 Certificate
More informationWe trust that these data are helpful to you. If you have any questions, feel free to contact Dr. Joe Ludlum at or
September 21, 216 Dear Colleague: The Office of Assessment has processed the 2-216 Course/Instructor Opinion Survey (CIOS) results for the Institute. For 69 academic terms (39 quarters and 3 semesters
More informationMore Now Disapprove of Trudeau Than Approve
FOR IMMEDIATE RELEASE More Now Disapprove of Trudeau Than Approve Liberals and Conservatives tied, but Liberals still edge out a minority Toronto, April 26 th In a random sampling of public opinion taken
More informationDIBELSnet Preliminary System-Wide Percentile Ranks for DIBELS Math Early Release
DYNAMIC MEASUREMENT GROUP 2014-2015 DIBELSnet Preliminary System-Wide Percentile Ranks for DIBELS Math Early Release Elizabeth N Dewey, M.Sc. Douglas P Rice, B.A. Courtney E Wheeler, Ph.D. Ruth A aminski,
More informationMaterial World How Does the USA Compare?
Material World How Does the USA Compare? Center for Energy and Environmental Education, University of Northern Iowa WR teacher training 24-25/Website/Lessons/Material World How Does the USA Compare? Written
More informationLinking the PARCC Assessments to NWEA MAP Growth Tests
Linking the PARCC Assessments to NWEA MAP Growth Tests November 2016 Introduction Northwest Evaluation Association (NWEA ) is committed to providing partners with useful tools to help make inferences from
More informationNEW CAR TIPS. Teaching Guidelines
NEW CAR TIPS Teaching Guidelines Subject: Algebra Topics: Patterns and Functions Grades: 7-12 Concepts: Independent and dependent variables Slope Direct variation (optional) Knowledge and Skills: Can relate
More informationInteractive Text Mining of Service Calls to Improve Customer Support Michael Schuh & Ron Zhang Advanced Product Engineering Oshkosh Corporation
Interactive Text Mining of Service Calls to Improve Customer Support Michael Schuh & Ron Zhang Advanced Product Engineering Oshkosh Corporation Outline Oshkosh Corporation Classification: Restricted Company
More informationCost-Efficiency by Arash Method in DEA
Applied Mathematical Sciences, Vol. 6, 2012, no. 104, 5179-5184 Cost-Efficiency by Arash Method in DEA Dariush Khezrimotlagh*, Zahra Mohsenpour and Shaharuddin Salleh Department of Mathematics, Faculty
More informationKANSAS Occupant Protection Observational Survey Supplementary Analyses Summer Study
KANSAS Occupant Protection Observational Survey Supplementary Analyses 2018 Summer Study Submitted To: Kansas Department of Transportation Bureau of Transportation Safety and Technology Prepared by: DCCCA
More informationLinking the Indiana ISTEP+ Assessments to the NWEA MAP Growth Tests. February 2017 Updated November 2017
Linking the Indiana ISTEP+ Assessments to the NWEA MAP Growth Tests February 2017 Updated November 2017 2017 NWEA. All rights reserved. No part of this document may be modified or further distributed without
More informationUSC Aiken 2004 Freshman Orientation Survey Results Selected questions have been made parallel to those on the CIRP Freshman Survey
Note: In 2004, USC Aiken administered a custom survey at Freshman Orientation. Many questions are parallel to questions asked on the CIRP Freshman Survey. It is important to note that issues such as question
More informationDIBELSnet System- Wide Percentile Ranks for. DIBELS Next. Elizabeth N Dewey, M.Sc. Ruth A. Kaminski, Ph.D. Roland H. Good, III, Ph.D.
2011-2012 DIBELSnet System- Wide Ranks for Introduction DIBELS Next Elizabeth N Dewey, M.Sc. Ruth A. Kaminski, Ph.D. Roland H. Good, III, Ph.D. The following report presents the system- wide percentile
More informationDepartment of Technology Fall 2004
Department of Technology Fall 2004 EET 352 ELECTRICAL POWER TECHNOLOGY Instructor: Prof. Vigs Chandra, Ph.D. Telephone: 859-622-1187 E-mail: vigs.chandra@eku.edu Web: http://www.technology.eku.edu/facstaff/chandra/
More informationCity University of New York Faculty Survey of Student Experience (FSSE), Spring 2010
City University of New York Faculty Survey of Student Experience (FSSE), Spring 2010 CUNY administered the Faculty Survey of Student Experience (FSSE) in the Spring of 2010 at the 11 senior colleges, one
More informationLIFT Power Math Camp LIFT Math Camp 2016
Number of Students Summary & Results At a Glance: LIFT Power Math Camp 2016 77 students 12 days 74 classes skipped $24,864 saved in tuition This year s LIFT Power Math Camp produced solid results. It involved
More informationScientific Notation. Slide 1 / 106. Slide 2 / 106. Slide 3 / th Grade. Table of Contents. New Jersey Center for Teaching and Learning
New Jersey Center for Teaching and Learning Slide 1 / 106 Progressive Mathematics Initiative This material is made freely available at www.njctl.org and is intended for the non-commercial use of students
More informationBarrie D. Fitzgerald Senior Research Analyst, Valdosta State University Sarah E. Hough Research Analyst, Valdosta State University Tiffany S.
You re Hired Now What? Barrie D. Fitzgerald Senior Research Analyst, Valdosta State University Sarah E. Hough Research Analyst, Valdosta State University Tiffany S. Soma Research Analyst, Valdosta State
More informationSomatic Cell Count Benchmarks
Table of Contents Introduction... 3 Methods... 3 Mastitis and Somatic Cell Counts... 3 Methods of Evaluating Somatic Cell Counts... 4 Table 1: Relationship between SCC Scores and Somatic Cell Counts...
More informationInquiry-Based Physics in Middle School. David E. Meltzer
Inquiry-Based Physics in Middle School David E. Meltzer Mary Lou Fulton Teachers College Arizona State University Mesa, Arizona U.S.A. Supported in part by a grant from Mary Lou Fulton Teachers College
More informationBCSSE Institutional Report Frequency Distributions. Baccalaureate
BCSSE Institutional Report Frequency Distributions BCSSE Frequency Distributions Interpreting Frequency Results 1 3 5 6 2 4 7 8 1. Variables : The items from the BCSSE survey appear in the left column
More informationOptimal Policy for Plug-In Hybrid Electric Vehicles Adoption IAEE 2014
Optimal Policy for Plug-In Hybrid Electric Vehicles Adoption IAEE 2014 June 17, 2014 OUTLINE Problem Statement Methodology Results Conclusion & Future Work Motivation Consumers adoption of energy-efficient
More informationAUTO 140A: VEHICLE MAINTENANCE
AUTO 140A: Vehicle Maintenance 1 AUTO 140A: VEHICLE MAINTENANCE Discipline AUTO - Automotive Technology Course Number 140A Course Title Vehicle Maintenance Catalog Course Description Intended for the incumbent
More informationSolar Kit Lesson #13 Solarize a Toy
UCSD TIES adapted from NYSERDA Energy Smart www.schoolpowernaturally.org Solar Kit Lesson #13 Solarize a Toy TEACHER INFORMATION LEARNING OUTCOME After designing and constructing solar electric power sources
More informationExtract from the 4 Corners program transcript from Jonathan Holmes' report into energy efficiency in Australian households, "The Home Front".
Extract from the 4 Corners program transcript from Jonathan Holmes' report into energy efficiency in Australian households, "The Home Front". JONATHAN HOLMES: But thousands of cheap air conditioners are
More informationAUTO 121 Auto Electrical I Fall Section J01 3 credits
UAS Automotive Technology Course Syllabus AUTO 121 Auto Electrical I Fall 2012 - Section J01 3 credits Instructor: Tony Martin Phone: 796-6126 (office) or 796-2034 (home) Email: tony.martin@uas.alaska.edu
More informationPVP Field Calibration and Accuracy of Torque Wrenches. Proceedings of ASME PVP ASME Pressure Vessel and Piping Conference PVP2011-
Proceedings of ASME PVP2011 2011 ASME Pressure Vessel and Piping Conference Proceedings of the ASME 2011 Pressure Vessels July 17-21, & Piping 2011, Division Baltimore, Conference Maryland PVP2011 July
More informationDynamics of Machines. Prof. Amitabha Ghosh. Department of Mechanical Engineering. Indian Institute of Technology, Kanpur. Module No.
Dynamics of Machines Prof. Amitabha Ghosh Department of Mechanical Engineering Indian Institute of Technology, Kanpur Module No. # 04 Lecture No. # 03 In-Line Engine Balancing In the last session, you
More informationCHANGE IN DRIVERS PARKING PREFERENCE AFTER THE INTRODUCTION OF STRENGTHENED PARKING REGULATIONS
CHANGE IN DRIVERS PARKING PREFERENCE AFTER THE INTRODUCTION OF STRENGTHENED PARKING REGULATIONS Kazuyuki TAKADA, Tokyo Denki University, takada@g.dendai.ac.jp Norio TAJIMA, Tokyo Denki University, 09rmk19@dendai.ac.jp
More informationAcademic Course Description
BME 503 FLUID POWER SYSTEMS Academic Course Description BHARATH UNIVERSITY Faculty of Engineering and Technology Department of Mechanical Engineering BME 503 FLUID POWER SYSTEMS Fifth Semester, 2015-16
More informationAn Introduction to R 2.5 A few data manipulation tricks!
An Introduction to R 2.5 A few data manipulation tricks! Dan Navarro (daniel.navarro@adelaide.edu.au) School of Psychology, University of Adelaide ua.edu.au/ccs/people/dan DSTO R Workshop, 29-Apr-2015
More informationLRT Preferred to Subway in Scarborough
FOR IMMEDIATE RELEASE LRT Preferred to Subway in Scarborough Most want to cancel subway and build something else In a random sampling of public opinion taken by the Forum Poll among 667 Toronto voters,
More informationInvestigation of Relationship between Fuel Economy and Owner Satisfaction
Investigation of Relationship between Fuel Economy and Owner Satisfaction June 2016 Malcolm Hazel, Consultant Michael S. Saccucci, Keith Newsom-Stewart, Martin Romm, Consumer Reports Introduction This
More informationENERGY STAR Program Requirements for Single Voltage External Ac-Dc and Ac-Ac Power Supplies. Eligibility Criteria.
ENERGY STAR Program Requirements for Single Voltage External Ac-Dc and Ac-Ac Power Supplies Eligibility Criteria Table of Contents Section 1: Definitions 2 Section 2: Qualifying Products 3 Section 3: Energy-Efficiency
More informationUK Weighing Federation Technical Articles
GLOSSARY The source of each definition is identified by the superscript number and listed out in full at the end of this glossary. Accuracy classification (1) classification as a Class I, Class II, Class
More informationSyllabus: Heavy Truck & Heavy Equipment Technician
Syllabus: Heavy Truck & Heavy Equipment Technician Subject Code: 171200 Course Numbers: HT 2201and HE 2202 CIP Code: 47.0605 SOC Code: 49-3000 C-TEC of Licking County 150 Price Road Newark, Ohio 43055
More information