1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number


 Patricia Hicks
 1 years ago
 Views:
Transcription
1 1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number A. 3(x  x) B. x 3 x C. 3x  x D. x  3x 2) Write the following as an algebraic expression using x as the variable: A number decreased by 25 and multiplied by 4 A. x 25 4 B. 25x 4 C. 4x  25 D. 4(x 25) 3. Write the following as an algebraic expression using x as the variable: The sum of a number and 8 A x B x C. x (8) D. 8x 4) Write the following as an algebraic expression using x as the variable: Twelve less than six times a number A. 12 6x B. 6x C. 12(6x) D. 6x 12 5) Solve: 3 (2 + 4)  5
2 A. 15 B. 10 C. 6 D ) Solve: ( 5)2 (9 17)2 ( 10)2 A. 16 B. 64 C D ) Solve: 3(32) 8(9 2) 2 A B. 55 C D. 1 8) Solve: ( 5)2 (9 17)2 ( 10)2 A. 16 B. 64 C D ) Solve: 3( ) 5 A. 9 B C D ) Solve: ( 6) A. 27 B. 90 C D ) Identify the variable, constant, and coefficient of the expression: 10k 15
3 A. variable: k; constant: 15; coefficient: 10 B. variable: k; constant: 15; coefficient: 10 C. variable: 10; constant: k; coefficient: 15 D. variable: 15; constant: 10; coefficient: k 12) Identify the variable, constant, and coefficient of the expression: x y A. variable: x and y; constant: 0; coefficient: 0 B. variable: x and y; constant: 0; coefficient: 1 C. variable: y; constant: x; coefficient: 0 D. variable: x; constant: y; coefficient: 1 13) Identify the variable, constant, and coefficient of the expression: 3p A. variable: p; constant: 0; coefficient: 3 B. variable: 3; constant: 0; coefficient: C. variable: 3; constant: p; coefficient: 3 D. variable: p; constant: 3; coefficient: 0 14) Solve the system of equations: 4x + 3y = 1 3x + 2y = 2 A. { (1, 1) } B. { (4, 5) } C. { ( 1,2) } D. { ( 2,3) } 15) Solve the system of equations: 3x 5y = 7 2x + 3y = 30 A. { (6,1) } B. { (9,4) } C. { ( 1, 2) } D. { (3,8) } 16) Solve the system of equations:
4 3x + 2y = 18 y = 3x A. { (4,3) } B. { (2,6) } C. { (1,3) } D. { (3,9) } 17) Solve the system of equations: 3x = 7 y 2y = 14 6x A. { (x,y) 3x + y = 7 } B. { (x,y) 3x + y = 7 } C. { (x,y) 2x + y = 3 } D. { (x,y) x + y = 2 } 18) Solve the system of equations: 3x + y = 7 x y = 5 A. { ( 3,2) } B. { ( 4,1) } C. { ( 2, 1) } D. { (1, 8) } 19) The Manager of Engineering reported that the industrial production index was 135. What does this production mean? A. An increase of 35 units B. An increase of 35 percent C. Not enough information given D. A decrease of 35 percent 20) Which of the following is true of a base period for an index number? A. It cannot be less than 100 B. The numerator spears C. It must have occurred after the year 1980 D. It appears in the denominator
5 21) Which of the following is true of an index? A. It shows a percent change from one period to another B. It must be larger than 100 C. It cannot assume negative values D. It can employ qualitative data 22) A man earned $80,000 when the Consumer Price Index was 200. What were his earnings in terms of $2,000 if the base period was 2000? A. $40,000 B. $160,000 C. $60,000 D. $80,000 23) What happens as we increase the number of classes in a histogram? A. Central tendency becomes more obvious B. Class interval width increases C. There would be more classes D. Class intervals become rounder 24) On which axis is time plotted on a simple line chart? A. On the Yaxis B. On the Xaxis C. Time is not plotted D. Either axis 25) The monthly incomes for a group of engineers are: $2,200, $2,400, $2,600, $3,100, $3,400, and $3,700. What are these ungrouped numbers called? A. Class limits B. Histograms C. Raw data D. Class frequencies 26) What is the term for a number of observations in a class in a frequency distribution?
6 A. Class interval B. Class midpoint C. Class array D. Class frequency 27) Why are unequal class intervals sometimes used in a frequency distribution? A. To avoid a large number of empty classes B. To create variety in presenting the data C. To avoid the need for midpoints D. To make the class frequencies smaller 28) What is the slope of the line: 14y 2x = 28 A. 2 B. 1/7 C. 7 D. 2 29) What is the slope of the line: 5y x = 10 A. 2 B. 1/5 C. 1/2 D ) What is the slope of the line: 36x 9y = 15 A. 4 B. 36 C. 3 D. 5/3 31) What is the slope of the line: 2y + 8x = 26 A. 8 B. 4 C. 2 D. 1/4 32) What is the slope of the line: 3x y = 6
7 A. 3 B. 2 C. 1 D. ½ 33) Which statement is true regarding the estimated slope of a linear regression line? A. It is chosen so as to minimize the sum of squared errors. B. It shows the change in x for a unit change in y. C. It could curve up or down as it moves to the right. D. It is always positive. 34) Which statement is true of a regression line that is superimposed on the scatter plot? A. It guarantees the largest possible sample variance. B. It is computed using the Ordinary Least Squares method. C. It guarantees that the slope and intercept are minimized. D. It is computed using the maximum and minimum values. 35) Which of the following is observed in a scatter plot when there is an inverse relationship between x and y? A. Points are mostly in the lower left and upper right quadrants. B. Points create a horizontal line. C. Points slope down as it moves to the right. D. Points curve up as it moves to the right. 36) What happens to the future value of money when the inflation rate exceeds the interest rate? A. Decreases B. Increases C. Stays the same D. Not enough information
8 37) Since money has the ability to earn interest, its value increases with time. What affects the future value of an investment more, the interest rate or the time the investment is held? A. The interest rate has a larger impact on the future value of the investment. B. The length of time has more of an impact on the future value of the investment. C. It depends on the interest rate and the time the investment is held. D. Both interest and length of time have the same impact on the future value of the investment 38) The number of hours spent studying appears to be highly correlated with the grade students earn in a class. Which variable would be the dependent variable in a linear regression analysis? A. Hours spent studying B. Either variable could be the dependent variable C. The class average D. The grade earned 39) When interest is compounded, the total time period is subdivided into several interest periods, for example 1 year, 3 months, 1 month. How does compound interest affect the future value of an investment? A. Stays the same B. Increases C. Decreases D. Not enough information 40) When the interest rate is positive, what happens to the value of money as we move from the future to the present? A. Stays the same B. Decreases C. Increases D. Not enough information 41) What is the principal balance if the principal plus interest at the end of 1.5 years is $3,360 at an annual interest rate of 8%?
9 A. $2,000 B. $2,800 C. $3,000 D. $2,200 42) How is the class midpoint calculated? A. Find the difference between consecutive lower limits. B. Count the number of observations in the class. C. Divide the class interval in half and add the result to the lower limit. D. frequency by the number of observations 43) How is a frequency distribution converted to a relative frequency distribution? A. Find the difference between consecutive lower class limits. B. Divide the lower limit of the first class by the class interval C. Multiply the class frequency by 100 D. Divide the class frequency by the total number of observations 44) What does the horizontal axis of a line chart represent? A. Dollars B. Variable quantity C. Percent D. Time 45) Which measures of central tendency are not affected by extremely low or extremely high values? A. Mean and median B. Mode and median C. Only the mean D. Mean and mode 46) For which measure of central tendency will the sum of the deviations always be zero?
10 A. Mode B. Median C. Mode and Median D. Mean 47) Which measure of dispersion represents variation from the mean? A. Range B. Spread C. Outliers D. Standard deviation 48) Which of the following is true regarding the normal distribution? A. Mean, median and mode are all equal B. It is not always symmetrical C. The total area under the curve is greater than 1 D. It can have more than one peak 49) Which of the following is a characteristic of a normal distribution? A. Positively skewed B. Can be either positively or negatively skewed C. Has a total zscore of 1000 D. Symmetrical 50) What is the proportion of the total area under the normal curve within plus or minus 2 standard deviations? A. 68% B. 95% C. 100% D. 99.7%
DESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses.
DESCRIPTIVE STATISTICS The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses. DESCRIPTIVE VS. INFERENTIAL STATISTICS Descriptive To organize,
More informationGCSE HIGHER Statistics Key Facts
GCSE HIGHER Statistics Key Facts Collecting Data When writing questions for questionnaires, always ensure that: 1. the question is worded so that it will allow the recipient to give you the information
More informationA frequency distribution is a table used to describe a data set. A frequency table lists intervals or ranges of data values called data classes
A frequency distribution is a table used to describe a data set. A frequency table lists intervals or ranges of data values called data classes together with the number of data values from the set that
More informationModule 3: Correlation and Covariance
Using Statistical Data to Make Decisions Module 3: Correlation and Covariance Tom Ilvento Dr. Mugdim Pašiƒ University of Delaware Sarajevo Graduate School of Business O ften our interest in data analysis
More informationAlgebra 1 Chapter 3 Vocabulary. equivalent  Equations with the same solutions as the original equation are called.
Chapter 3 Vocabulary equivalent  Equations with the same solutions as the original equation are called. formula  An algebraic equation that relates two or more reallife quantities. unit rate  A rate
More informationnot to be republished NCERT Measures of Central Tendency
You have learnt in previous chapter that organising and presenting data makes them comprehensible. It facilitates data processing. A number of statistical techniques are used to analyse the data. In this
More informationMCQ S OF MEASURES OF CENTRAL TENDENCY
MCQ S OF MEASURES OF CENTRAL TENDENCY MCQ No 3.1 Any measure indicating the centre of a set of data, arranged in an increasing or decreasing order of magnitude, is called a measure of: (a) Skewness (b)
More informationMeasures of Central Tendency and Variability: Summarizing your Data for Others
Measures of Central Tendency and Variability: Summarizing your Data for Others 1 I. Measures of Central Tendency: Allow us to summarize an entire data set with a single value (the midpoint). 1. Mode :
More informationChapter 3 Descriptive Statistics: Numerical Measures. Learning objectives
Chapter 3 Descriptive Statistics: Numerical Measures Slide 1 Learning objectives 1. Single variable Part I (Basic) 1.1. How to calculate and use the measures of location 1.. How to calculate and use the
More informationF. Farrokhyar, MPhil, PhD, PDoc
Learning objectives Descriptive Statistics F. Farrokhyar, MPhil, PhD, PDoc To recognize different types of variables To learn how to appropriately explore your data How to display data using graphs How
More informationExercise 1.12 (Pg. 2223)
Individuals: The objects that are described by a set of data. They may be people, animals, things, etc. (Also referred to as Cases or Records) Variables: The characteristics recorded about each individual.
More informationNumerical Summarization of Data OPRE 6301
Numerical Summarization of Data OPRE 6301 Motivation... In the previous session, we used graphical techniques to describe data. For example: While this histogram provides useful insight, other interesting
More information103 Measures of Central Tendency and Variation
103 Measures of Central Tendency and Variation So far, we have discussed some graphical methods of data description. Now, we will investigate how statements of central tendency and variation can be used.
More informationALGEBRA I A PLUS COURSE OUTLINE
ALGEBRA I A PLUS COURSE OUTLINE OVERVIEW: 1. Operations with Real Numbers 2. Equation Solving 3. Word Problems 4. Inequalities 5. Graphs of Functions 6. Linear Functions 7. Scatterplots and Lines of Best
More informationDescriptive Statistics. Frequency Distributions and Their Graphs 2.1. Frequency Distributions. Chapter 2
Chapter Descriptive Statistics.1 Frequency Distributions and Their Graphs Frequency Distributions A frequency distribution is a table that shows classes or intervals of data with a count of the number
More informationChapter 3: Central Tendency
Chapter 3: Central Tendency Central Tendency In general terms, central tendency is a statistical measure that determines a single value that accurately describes the center of the distribution and represents
More informationData Analysis: Describing Data  Descriptive Statistics
WHAT IT IS Return to Table of ontents Descriptive statistics include the numbers, tables, charts, and graphs used to describe, organize, summarize, and present raw data. Descriptive statistics are most
More informationChapter 3: Data Description Numerical Methods
Chapter 3: Data Description Numerical Methods Learning Objectives Upon successful completion of Chapter 3, you will be able to: Summarize data using measures of central tendency, such as the mean, median,
More informationCHAPTER 3 CENTRAL TENDENCY ANALYSES
CHAPTER 3 CENTRAL TENDENCY ANALYSES The next concept in the sequential statistical steps approach is calculating measures of central tendency. Measures of central tendency represent some of the most simple
More informationBiostatistics: DESCRIPTIVE STATISTICS: 2, VARIABILITY
Biostatistics: DESCRIPTIVE STATISTICS: 2, VARIABILITY 1. Introduction Besides arriving at an appropriate expression of an average or consensus value for observations of a population, it is important to
More informationAlgebra I Vocabulary Cards
Algebra I Vocabulary Cards Table of Contents Expressions and Operations Natural Numbers Whole Numbers Integers Rational Numbers Irrational Numbers Real Numbers Absolute Value Order of Operations Expression
More informationTechnology StepbyStep Using StatCrunch
Technology StepbyStep Using StatCrunch Section 1.3 Simple Random Sampling 1. Select Data, highlight Simulate Data, then highlight Discrete Uniform. 2. Fill in the following window with the appropriate
More informationElementary Statistics. Scatter Plot, Regression Line, Linear Correlation Coefficient, and Coefficient of Determination
Scatter Plot, Regression Line, Linear Correlation Coefficient, and Coefficient of Determination What is a Scatter Plot? A Scatter Plot is a plot of ordered pairs (x, y) where the horizontal axis is used
More informationSimple Regression Theory II 2010 Samuel L. Baker
SIMPLE REGRESSION THEORY II 1 Simple Regression Theory II 2010 Samuel L. Baker Assessing how good the regression equation is likely to be Assignment 1A gets into drawing inferences about how close the
More informationHomework 3. Part 1. Name: Score: / null
Name: Score: / Homework 3 Part 1 null 1 For the following sample of scores, the standard deviation is. Scores: 7, 2, 4, 6, 4, 7, 3, 7 Answer Key: 2 2 For any set of data, the sum of the deviation scores
More informationStats Review Chapters 34
Stats Review Chapters 34 Created by Teri Johnson Math Coordinator, Mary Stangler Center for Academic Success Examples are taken from Statistics 4 E by Michael Sullivan, III And the corresponding Test
More informationChapter 2: Systems of Linear Equations and Matrices:
At the end of the lesson, you should be able to: Chapter 2: Systems of Linear Equations and Matrices: 2.1: Solutions of Linear Systems by the Echelon Method Define linear systems, unique solution, inconsistent,
More informationSTATS8: Introduction to Biostatistics. Data Exploration. Babak Shahbaba Department of Statistics, UCI
STATS8: Introduction to Biostatistics Data Exploration Babak Shahbaba Department of Statistics, UCI Introduction After clearly defining the scientific problem, selecting a set of representative members
More informationTable 21. Sucrose concentration (% fresh wt.) of 100 sugar beet roots. Beet No. % Sucrose. Beet No.
Chapter 2. DATA EXPLORATION AND SUMMARIZATION 2.1 Frequency Distributions Commonly, people refer to a population as the number of individuals in a city or county, for example, all the people in California.
More informationGCSE Statistics Revision notes
GCSE Statistics Revision notes Collecting data Sample This is when data is collected from part of the population. There are different methods for sampling Random sampling, Stratified sampling, Systematic
More informationDescribe what is meant by a placebo Contrast the doubleblind procedure with the singleblind procedure Review the structure for organizing a memo
Readings: Ha and Ha Textbook  Chapters 1 8 Appendix D & E (online) Plous  Chapters 10, 11, 12 and 14 Chapter 10: The Representativeness Heuristic Chapter 11: The Availability Heuristic Chapter 12: Probability
More informationWe will use the following data sets to illustrate measures of center. DATA SET 1 The following are test scores from a class of 20 students:
MODE The mode of the sample is the value of the variable having the greatest frequency. Example: Obtain the mode for Data Set 1 77 For a grouped frequency distribution, the modal class is the class having
More informationMATH BOOK OF PROBLEMS SERIES. New from Pearson Custom Publishing!
MATH BOOK OF PROBLEMS SERIES New from Pearson Custom Publishing! The Math Book of Problems Series is a database of math problems for the following courses: Prealgebra Algebra Precalculus Calculus Statistics
More information2.0 Lesson Plan. Answer Questions. Summary Statistics. Histograms. The Normal Distribution. Using the Standard Normal Table
2.0 Lesson Plan Answer Questions 1 Summary Statistics Histograms The Normal Distribution Using the Standard Normal Table 2. Summary Statistics Given a collection of data, one needs to find representations
More informationChapter 10. Key Ideas Correlation, Correlation Coefficient (r),
Chapter 0 Key Ideas Correlation, Correlation Coefficient (r), Section 0: Overview We have already explored the basics of describing single variable data sets. However, when two quantitative variables
More informationALGEBRA I / ALGEBRA I SUPPORT
Suggested Sequence: CONCEPT MAP ALGEBRA I / ALGEBRA I SUPPORT August 2011 1. Foundations for Algebra 2. Solving Equations 3. Solving Inequalities 4. An Introduction to Functions 5. Linear Functions 6.
More informationCan Gas Prices be Predicted?
Can Gas Prices be Predicted? Chris Vaughan, Reynolds High School A Statistical Analysis of Annual Gas Prices from 19762005 Level/Course: This lesson can be used and modified for teaching High School Math,
More informationDescriptive Statistics
Y520 Robert S Michael Goal: Learn to calculate indicators and construct graphs that summarize and describe a large quantity of values. Using the textbook readings and other resources listed on the web
More informationChapter 7 What to do when you have the data
Chapter 7 What to do when you have the data We saw in the previous chapters how to collect data. We will spend the rest of this course looking at how to analyse the data that we have collected. Stem and
More informationChapter 2: Frequency Distributions and Graphs (or making pretty tables and pretty pictures)
Chapter 2: Frequency Distributions and Graphs (or making pretty tables and pretty pictures) Example: Titanic passenger data is available for 1310 individuals for 14 variables, though not all variables
More information32 Measures of Central Tendency and Dispersion
32 Measures of Central Tendency and Dispersion In this section we discuss two important aspects of data which are its center and its spread. The mean, median, and the mode are measures of central tendency
More information430 Statistics and Financial Mathematics for Business
Prescription: 430 Statistics and Financial Mathematics for Business Elective prescription Level 4 Credit 20 Version 2 Aim Students will be able to summarise, analyse, interpret and present data, make predictions
More informationSimple linear regression
Simple linear regression Introduction Simple linear regression is a statistical method for obtaining a formula to predict values of one variable from another where there is a causal relationship between
More informationMeans, standard deviations and. and standard errors
CHAPTER 4 Means, standard deviations and standard errors 4.1 Introduction Change of units 4.2 Mean, median and mode Coefficient of variation 4.3 Measures of variation 4.4 Calculating the mean and standard
More informationDiagrams and Graphs of Statistical Data
Diagrams and Graphs of Statistical Data One of the most effective and interesting alternative way in which a statistical data may be presented is through diagrams and graphs. There are several ways in
More information2. Simple Linear Regression
Research methods  II 3 2. Simple Linear Regression Simple linear regression is a technique in parametric statistics that is commonly used for analyzing mean response of a variable Y which changes according
More informationDATA HANDLING (3) Overview. Measures of dispersion (or spread) about the mean (ungrouped data) Lesson. Learning Outcomes and Assessment Standards
42 DATA HANDLING (3) Learning Outcomes and Assessment Standards Learning Outcome 4: Data handling and probability Assessment Standard AS 1(a) Calculate and represent measures of central tendency and dispersion
More informationSan Jose State University Engineering 10 1
KY San Jose State University Engineering 10 1 Select Insert from the main menu Plotting in Excel Select All Chart Types San Jose State University Engineering 10 2 Definition: A chart that consists of multiple
More informationChapter 2 Summarizing and Graphing Data
Chapter 2 Summarizing and Graphing Data 21 Review and Preview 22 Frequency Distributions 23 Histograms 24 Graphs that Enlighten and Graphs that Deceive Preview Characteristics of Data 1. Center: A
More informationChapter 2: Frequency Distributions and Graphs
Chapter 2: Frequency Distributions and Graphs Learning Objectives Upon completion of Chapter 2, you will be able to: Organize the data into a table or chart (called a frequency distribution) Construct
More informationAlgebra 2 Chapter 1 Vocabulary. identity  A statement that equates two equivalent expressions.
Chapter 1 Vocabulary identity  A statement that equates two equivalent expressions. verbal model A word equation that represents a reallife problem. algebraic expression  An expression with variables.
More informationBusiness Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics.
Business Course Text Bowerman, Bruce L., Richard T. O'Connell, J. B. Orris, and Dawn C. Porter. Essentials of Business, 2nd edition, McGrawHill/Irwin, 2008, ISBN: 9780073319889. Required Computing
More informationChapter 2. The Normal Distribution
Chapter 2 The Normal Distribution Lesson 21 Density Curve Review Graph the data Calculate a numerical summary of the data Describe the shape, center, spread and outliers of the data Histogram with Curve
More informationStatistical Analysis Using Gnumeric
Statistical Analysis Using Gnumeric There are many software packages that will analyse data. For casual analysis, a spreadsheet may be an appropriate tool. Popular spreadsheets include Microsoft Excel,
More informationSTA201TE. 5. Measures of relationship: correlation (5%) Correlation coefficient; Pearson r; correlation and causation; proportion of common variance
Principles of Statistics STA201TE This TECEP is an introduction to descriptive and inferential statistics. Topics include: measures of central tendency, variability, correlation, regression, hypothesis
More informationChapter 15 Multiple Choice Questions (The answers are provided after the last question.)
Chapter 15 Multiple Choice Questions (The answers are provided after the last question.) 1. What is the median of the following set of scores? 18, 6, 12, 10, 14? a. 10 b. 14 c. 18 d. 12 2. Approximately
More informationExpression. Variable Equation Polynomial Monomial Add. Area. Volume Surface Space Length Width. Probability. Chance Random Likely Possibility Odds
Isosceles Triangle Congruent Leg Side Expression Equation Polynomial Monomial Radical Square Root Check Times Itself Function Relation One Domain Range Area Volume Surface Space Length Width Quantitative
More informationThis unit will lay the groundwork for later units where the students will extend this knowledge to quadratic and exponential functions.
Algebra I Overview View unit yearlong overview here Many of the concepts presented in Algebra I are progressions of concepts that were introduced in grades 6 through 8. The content presented in this course
More informationAlgebra 1 Course Objectives
Course Objectives The Duke TIP course corresponds to a high school course and is designed for gifted students in grades seven through nine who want to build their algebra skills before taking algebra in
More informationSTAT 155 Introductory Statistics. Lecture 5: Density Curves and Normal Distributions (I)
The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL STAT 155 Introductory Statistics Lecture 5: Density Curves and Normal Distributions (I) 9/12/06 Lecture 5 1 A problem about Standard Deviation A variable
More informationSummarizing and Displaying Categorical Data
Summarizing and Displaying Categorical Data Categorical data can be summarized in a frequency distribution which counts the number of cases, or frequency, that fall into each category, or a relative frequency
More informationbusiness statistics using Excel OXFORD UNIVERSITY PRESS Glyn Davis & Branko Pecar
business statistics using Excel Glyn Davis & Branko Pecar OXFORD UNIVERSITY PRESS Detailed contents Introduction to Microsoft Excel 2003 Overview Learning Objectives 1.1 Introduction to Microsoft Excel
More information03 The full syllabus. 03 The full syllabus continued. For more information visit www.cimaglobal.com PAPER C03 FUNDAMENTALS OF BUSINESS MATHEMATICS
0 The full syllabus 0 The full syllabus continued PAPER C0 FUNDAMENTALS OF BUSINESS MATHEMATICS Syllabus overview This paper primarily deals with the tools and techniques to understand the mathematics
More informationMasconomet Regional High School Curriculum Guide
Masconomet Regional High School Curriculum Guide COURSE TITLE: Algebra 2 COURSE NUMBER: 1322 DEPARTMENT: Mathematics GRADE LEVEL(S) & PHASE: 10 12, CP LENGTH OF COURSE: Full Year Course Description: This
More informationDescriptive Statistics. Understanding Data: Categorical Variables. Descriptive Statistics. Dataset: Shellfish Contamination
Descriptive Statistics Understanding Data: Dataset: Shellfish Contamination Location Year Species Species2 Method Metals Cadmium (mg kg  ) Chromium (mg kg  ) Copper (mg kg  ) Lead (mg kg  ) Mercury
More informationReport of for Chapter 2 pretest
Report of for Chapter 2 pretest Exam: Chapter 2 pretest Category: Organizing and Graphing Data 1. "For our study of driving habits, we recorded the speed of every fifth vehicle on Drury Lane. Nearly every
More informationMIDTERM EXAMINATION Spring 2009 STA301 Statistics and Probability (Session  2)
MIDTERM EXAMINATION Spring 2009 STA301 Statistics and Probability (Session  2) Question No: 1 Median can be found only when: Data is Discrete Data is Attributed Data is continuous Data is continuous
More informationHigh School Algebra 1 Common Core Standards & Learning Targets
High School Algebra 1 Common Core Standards & Learning Targets Unit 1: Relationships between Quantities and Reasoning with Equations CCS Standards: Quantities NQ.1. Use units as a way to understand problems
More informationDefinition 8.1 Two inequalities are equivalent if they have the same solution set. Add or Subtract the same value on both sides of the inequality.
8 Inequalities Concepts: Equivalent Inequalities Linear and Nonlinear Inequalities Absolute Value Inequalities (Sections 4.6 and 1.1) 8.1 Equivalent Inequalities Definition 8.1 Two inequalities are equivalent
More informationContent DESCRIPTIVE STATISTICS. Data & Statistic. Statistics. Example: DATA VS. STATISTIC VS. STATISTICS
Content DESCRIPTIVE STATISTICS Dr Najib Majdi bin Yaacob MD, MPH, DrPH (Epidemiology) USM Unit of Biostatistics & Research Methodology School of Medical Sciences Universiti Sains Malaysia. Introduction
More informationMeasures of Central Tendency. There are different types of averages, each has its own advantages and disadvantages.
Measures of Central Tendency According to Prof Bowley Measures of central tendency (averages) are statistical constants which enable us to comprehend in a single effort the significance of the whole. The
More informationThe aspect of the data that we want to describe/measure is the degree of linear relationship between and The statistic r describes/measures the degree
PS 511: Advanced Statistics for Psychological and Behavioral Research 1 Both examine linear (straight line) relationships Correlation works with a pair of scores One score on each of two variables ( and
More informationThe correlation coefficient
The correlation coefficient Clinical Biostatistics The correlation coefficient Martin Bland Correlation coefficients are used to measure the of the relationship or association between two quantitative
More informationof surface, 569571, 576577, 578581 of triangle, 548 Associative Property of addition, 12, 331 of multiplication, 18, 433
Absolute Value and arithmetic, 730733 defined, 730 Acute angle, 477 Acute triangle, 497 Addend, 12 Addition associative property of, (see Commutative Property) carrying in, 11, 92 commutative property
More informationUse your TI84 graphing calculator to check as many problems as possible.
Name: Date: Period: Dear Future Algebra Honors student, We hope that you enjoy your summer vacation to the fullest. We look forward to working with you next year. As you enter your new math class, you
More informationHISTOGRAMS, CUMULATIVE FREQUENCY AND BOX PLOTS
Mathematics Revision Guides Histograms, Cumulative Frequency and Box Plots Page 1 of 25 M.K. HOME TUITION Mathematics Revision Guides Level: GCSE Higher Tier HISTOGRAMS, CUMULATIVE FREQUENCY AND BOX PLOTS
More informationSession 1.6 Measures of Central Tendency
Session 1.6 Measures of Central Tendency Measures of location (Indices of central tendency) These indices locate the center of the frequency distribution curve. The mode, median, and mean are three indices
More informationChapter 2 Statistical Foundations: Descriptive Statistics
Chapter 2 Statistical Foundations: Descriptive Statistics 20 Chapter 2 Statistical Foundations: Descriptive Statistics Presented in this chapter is a discussion of the types of data and the use of frequency
More information100 Math Facts 6 th Grade
100 Math Facts 6 th Grade Name 1. SUM: What is the answer to an addition problem called? (N. 2.1) 2. DIFFERENCE: What is the answer to a subtraction problem called? (N. 2.1) 3. PRODUCT: What is the answer
More informationCourse Text. Required Computing Software. Course Description. Course Objectives. StraighterLine. Business Statistics
Course Text Business Statistics Lind, Douglas A., Marchal, William A. and Samuel A. Wathen. Basic Statistics for Business and Economics, 7th edition, McGrawHill/Irwin, 2010, ISBN: 9780077384470 [This
More information, has mean A) 0.3. B) the smaller of 0.8 and 0.5. C) 0.15. D) which cannot be determined without knowing the sample results.
BA 275 Review Problems  Week 9 (11/20/0611/24/06) CD Lessons: 69, 70, 1620 Textbook: pp. 520528, 111124, 133141 An SRS of size 100 is taken from a population having proportion 0.8 of successes. An
More informationMario Guarracino. Regression
Regression Introduction In the last lesson, we saw how to aggregate data from different sources, identify measures and dimensions, to build data marts for business analysis. Some techniques were introduced
More informationExam 2 Review. 3. How to tell if an equation is linear? An equation is linear if it can be written, through simplification, in the form.
Exam 2 Review Chapter 1 Section1 Do You Know: 1. What does it mean to solve an equation? To solve an equation is to find the solution set, that is, to find the set of all elements in the domain of the
More informationUnit 3 Sample Test. Name: Class: Date: True/False Indicate whether the statement is true or false.
Name: Class: Date: Unit 3 Sample Test True/False Indicate whether the statement is true or false. 1. An example of qualitative data is the colour of a person s eyes. 2. When a researcher conducts an experiment,
More informationRegression. In this class we will:
AMS 5 REGRESSION Regression The idea behind the calculation of the coefficient of correlation is that the scatter plot of the data corresponds to a cloud that follows a straight line. This idea can be
More informationCommon Core Unit Summary Grades 6 to 8
Common Core Unit Summary Grades 6 to 8 Grade 8: Unit 1: Congruence and Similarity 8G18G5 rotations reflections and translations,( RRT=congruence) understand congruence of 2 d figures after RRT Dilations
More informationCHINHOYI UNIVERSITY OF TECHNOLOGY
CHINHOYI UNIVERSITY OF TECHNOLOGY SCHOOL OF NATURAL SCIENCES AND MATHEMATICS DEPARTMENT OF MATHEMATICS MEASURES OF CENTRAL TENDENCY AND DISPERSION INTRODUCTION From the previous unit, the Graphical displays
More informationAlgebra 1 Course Information
Course Information Course Description: Students will study patterns, relations, and functions, and focus on the use of mathematical models to understand and analyze quantitative relationships. Through
More informationStatistical Concepts and Market Return
Statistical Concepts and Market Return 2014 Level I Quantitative Methods IFT Notes for the CFA exam Contents 1. Introduction... 2 2. Some Fundamental Concepts... 2 3. Summarizing Data Using Frequency Distributions...
More informationEach exam covers lectures from since the previous exam and up to the exam date.
Sociology 301 Exam Review Liying Luo 03.22 Exam Review: Logistics Exams must be taken at the scheduled date and time unless 1. You provide verifiable documents of unforeseen illness or family emergency,
More informationCALCULATIONS & STATISTICS
CALCULATIONS & STATISTICS CALCULATION OF SCORES Conversion of 15 scale to 0100 scores When you look at your report, you will notice that the scores are reported on a 0100 scale, even though respondents
More informationSession 7 Bivariate Data and Analysis
Session 7 Bivariate Data and Analysis Key Terms for This Session Previously Introduced mean standard deviation New in This Session association bivariate analysis contingency table covariation least squares
More informationIn this course, we will consider the various possible types of presentation of data and justification for their use in given situations.
PRESENTATION OF DATA 1.1 INTRODUCTION Once data has been collected, it has to be classified and organised in such a way that it becomes easily readable and interpretable, that is, converted to information.
More informatione = random error, assumed to be normally distributed with mean 0 and standard deviation σ
1 Linear Regression 1.1 Simple Linear Regression Model The linear regression model is applied if we want to model a numeric response variable and its dependency on at least one numeric factor variable.
More informationCOMPARISON MEASURES OF CENTRAL TENDENCY & VARIABILITY EXERCISE 8/5/2013. MEASURE OF CENTRAL TENDENCY: MODE (Mo) MEASURE OF CENTRAL TENDENCY: MODE (Mo)
COMPARISON MEASURES OF CENTRAL TENDENCY & VARIABILITY Prepared by: Jess Roel Q. Pesole CENTRAL TENDENCY what is average or typical in a distribution Commonly Measures: 1. Mode. Median 3. Mean quantified
More informationDomain Essential Question Common Core Standards Resources
Middle School Math 20162017 Domain Essential Question Common Core Standards First Ratios and Proportional Relationships How can you use mathematics to describe change and model real world solutions? How
More informationIn this chapter, you will learn to use descriptive statistics to organize, summarize, analyze, and interpret data for contract pricing.
3.0  Chapter Introduction In this chapter, you will learn to use descriptive statistics to organize, summarize, analyze, and interpret data for contract pricing. Categories of Statistics. Statistics is
More informationGraphing Linear Equations
Graphing Linear Equations I. Graphing Linear Equations a. The graphs of first degree (linear) equations will always be straight lines. b. Graphs of lines can have Positive Slope Negative Slope Zero slope
More informationSimple Regression and Correlation
Simple Regression and Correlation Today, we are going to discuss a powerful statistical technique for examining whether or not two variables are related. Specifically, we are going to talk about the ideas
More information4. Describing Bivariate Data
4. Describing Bivariate Data A. Introduction to Bivariate Data B. Values of the Pearson Correlation C. Properties of Pearson's r D. Computing Pearson's r E. Variance Sum Law II F. Exercises A dataset with
More information