Z-tables. December 9, 2016

Size: px
Start display at page:

Download "Z-tables. December 9, 2016"

Transcription

1 Z-tables December 9, 2016 Contents The standard normal distribution Areas above Areas below the mean Areas between two values of Finding -scores from areas Questions This tutorial covers how to find areas under normal distributions using a -table The standard normal distribution Thanks to the central limit theorem distributions of means often fall into a normal bell-shaped distribution Since we ll be dealing with means as dependent measures a lot this quarter and in our research, we ll need to be familiar with the properties of the normal distribution All normal distributions have the same shape They only differ by their means and standar deviations The general equation for the normal probability distribution is: e (x µ)2 2πσ Where µ is the mean and σ is the standard deviation of the distribution (It s kind of remarkable that this ubiquitous function has two famous transcendental numbers in it, e, and π, plus the irrational number 2) We choose one particular normal distribution, the standard normal, as a reference for tables The standard normal distribution, or -distribution has a mean of ero and a standard deviation of 1 The standard normal s probability distribution function simplifies to: e x2 2π It looks like this: 1

2 2

3 Here are some exercises on using the -table to find areas under this standard normal distribution (either in the book, Excel spreadsheet, handout, or one of many websites or statistics programs) We ll start with an easy one: What is the area under the standard normal distribution above =0? The area is shaded in the figure below: area =05 0 The answer is 05 because the normal distribution has a total area of 1 and is symmetric about the mean of 0 Areas above Example: find the area above =1 The area is the shaded region below: area =01587 The area can be found by using table A in the book Find the value in the first column for =1 The third column gives the area under the standard normal above The relevant part of the table should look something like this: 1 3

4 Area between mean and Area beyond On the row where the first column as = 1, the third column shows that the area under the curve above is The middle column is the area between ero and Since right-half of the area is 05, you can see that columns 2 and 3 add up to 05 (for =1, = 05) 4

5 Areas below the mean Example: What is the area under the standard normal distribution below = -2? area = Notice that the -table doesn t show areas for negative values of That s because the -distribution is symmetrical, so for our example, the area below = -2 is the same as the area above = 2: area =00228 The area above = 2 can be found in the table: 2 Area between mean and Area beyond

6 Example: Find the area under the standard normal distribution below = 1: area =08413 There are a couple of ways to do this one One way is to realie that since the total area is 1, the area below = 1 is equal to 1 minus the area above = 1 which we know from before is So the area below 1 is = Another way to do this is to see that the area below 1 is the sum of the area between ero and 1 and the area below ero which is 05 From second column in the table, the area between ero and 1 is So the total area is =

7 Areas between two values of Example: What is the area under the standard normal distribution between 1 and 2? area = The trick is to understand that the area can be computed by subtracting the area above = 2 from the area above = 1: area =

8 area =00228 The difference is =

9 Example: What is the area under the standard normal between = -2 and 1? area = Again, there are a couple of ways to solve this one One way is to use the fact that the total area is 1, so the area between -2 and 1 is equal to 1 minus the areas in the tails The area below = -2 is and the area above 1 is 01587: area =

10 area =01587 So the total area is equal to = Another way to solve this one is to use the second column in table, which is the area between the mean and The area between = -2 and = 0 is the same as the area between = 0 and = 2, which according to the table is The table also tells us that the area between 0 and 1 is 03413: 1 area =

11 area = So the total area is =

12 Finding -scores from areas Example: Find the score for which 5% of the area under the standard normal distribution lies above area = To solve this one we need to find the row in the table for which the third column, the area beyond, is nearest to 005: Area between mean and Area beyond So the answer is =

13 Example: Find the value of for which 10% of the area under the standard normal distribution lies below: area = We ll use the fact that the normal distribution is symmetrical, and find the -value for which 10% lies above: area = Area between mean and Area beyond The closest value of is 128 Using symmetry, we know that 10% of the area under the standard normal distribution lies below =

14 Example: Find the values of that bracket the middle 95% of the area under the standard normal distribution area = The middle 95% of the area leaves (100-95)/2 = 25% in each of the two tails; area =0025 area = So we need to find the -value for which the area above is 0025 Area between mean and Area beyond From the table, = 196 Therefore 95% of the area under the standard normal distribution lies between = -196 and =

15 Questions Now it s your turn Here are 28 random -distribution problems and answers Draw pictures if it helps 1) Find the area under the standard normal distribution below = 120 Answer: ) Find the value of for which 93 percent of the area under standard normal distribution lies above Answer: = ) Find the area under the standard normal distribution between = 010 and = 060 Answer: ) Find the value of for which 5 percent of the area under standard normal distribution lies below Answer: = ) Find the value of for which 1 percent of the area under standard normal distribution lies above Answer: = 233 6) Find the area under the standard normal distribution below = 040 Answer: ) Find the area under the standard normal distribution above = -070 Answer: ) Find the value of for which 85 percent of the area under standard normal distribution lies above Answer: = ) Find the value of for which 65 percent of the area under standard normal distribution lies below Answer: = ) Find the area under the standard normal distribution above = 170 Answer: ) Find the value of for which 26 percent of the area under standard normal distribution lies above Answer: = ) Find the area under the standard normal distribution above = 010 Answer: ) Find the area under the standard normal distribution between = 030 and = 180 Answer: ) Find the value of for which 37 percent of the area under standard normal distribution lies above Answer: =

16 15) Find the area under the standard normal distribution above = 090 Answer: ) Find the value of for which 65 percent of the area under standard normal distribution lies above Answer: = ) Find the area under the standard normal distribution between = -140 and = -070 Answer: ) Find the value of for which 44 percent of the area under standard normal distribution lies below Answer: = ) Find the range of values which covers the middle 24 percent of the area under the standard normal distribution Answer: Between = -031 and = ) Find the area under the standard normal distribution between = -060 and = 120 Answer: ) Find the area under the standard normal distribution between = -040 and = 060 Answer: ) Find the value of for which 6 percent of the area under standard normal distribution lies above Answer: = ) Find the range of values which covers the middle 52 percent of the area under the standard normal distribution Answer: Between = -071 and = ) Find the area under the standard normal distribution above = -010 Answer: ) Find the area under the standard normal distribution below = -130 Answer: ) Find the area under the standard normal distribution above = -130 Answer: ) Find the area under the standard normal distribution between = -000 and = 100 Answer: ) Find the area under the standard normal distribution below = -080 Answer:

6.4 Normal Distribution

6.4 Normal Distribution Contents 6.4 Normal Distribution....................... 381 6.4.1 Characteristics of the Normal Distribution....... 381 6.4.2 The Standardized Normal Distribution......... 385 6.4.3 Meaning of Areas under

More information

Lesson 7 Z-Scores and Probability

Lesson 7 Z-Scores and Probability Lesson 7 Z-Scores and Probability Outline Introduction Areas Under the Normal Curve Using the Z-table Converting Z-score to area -area less than z/area greater than z/area between two z-values Converting

More information

6 3 The Standard Normal Distribution

6 3 The Standard Normal Distribution 290 Chapter 6 The Normal Distribution Figure 6 5 Areas Under a Normal Distribution Curve 34.13% 34.13% 2.28% 13.59% 13.59% 2.28% 3 2 1 + 1 + 2 + 3 About 68% About 95% About 99.7% 6 3 The Distribution Since

More information

Lesson 4 Measures of Central Tendency

Lesson 4 Measures of Central Tendency Outline Measures of a distribution s shape -modality and skewness -the normal distribution Measures of central tendency -mean, median, and mode Skewness and Central Tendency Lesson 4 Measures of Central

More information

Procedure for Graphing Polynomial Functions

Procedure for Graphing Polynomial Functions Procedure for Graphing Polynomial Functions P(x) = a n x n + a n-1 x n-1 + + a 1 x + a 0 To graph P(x): As an example, we will examine the following polynomial function: P(x) = 2x 3 3x 2 23x + 12 1. Determine

More information

5/31/2013. 6.1 Normal Distributions. Normal Distributions. Chapter 6. Distribution. The Normal Distribution. Outline. Objectives.

5/31/2013. 6.1 Normal Distributions. Normal Distributions. Chapter 6. Distribution. The Normal Distribution. Outline. Objectives. The Normal Distribution C H 6A P T E R The Normal Distribution Outline 6 1 6 2 Applications of the Normal Distribution 6 3 The Central Limit Theorem 6 4 The Normal Approximation to the Binomial Distribution

More information

Multiple regression - Matrices

Multiple regression - Matrices Multiple regression - Matrices This handout will present various matrices which are substantively interesting and/or provide useful means of summarizing the data for analytical purposes. As we will see,

More information

Simple Regression Theory II 2010 Samuel L. Baker

Simple 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 information

The Standard Normal distribution

The Standard Normal distribution The Standard Normal distribution 21.2 Introduction Mass-produced items should conform to a specification. Usually, a mean is aimed for but due to random errors in the production process we set a tolerance

More information

4. Continuous Random Variables, the Pareto and Normal Distributions

4. Continuous Random Variables, the Pareto and Normal Distributions 4. Continuous Random Variables, the Pareto and Normal Distributions A continuous random variable X can take any value in a given range (e.g. height, weight, age). The distribution of a continuous random

More information

1.6 The Order of Operations

1.6 The Order of Operations 1.6 The Order of Operations Contents: Operations Grouping Symbols The Order of Operations Exponents and Negative Numbers Negative Square Roots Square Root of a Negative Number Order of Operations and Negative

More information

Normal distributions in SPSS

Normal distributions in SPSS Normal distributions in SPSS Bro. David E. Brown, BYU Idaho Department of Mathematics February 2, 2012 1 Calculating probabilities and percents from measurements: The CDF.NORMAL command 1. Go to the Variable

More information

Biostatistics: DESCRIPTIVE STATISTICS: 2, VARIABILITY

Biostatistics: 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 information

Density Curve. A density curve is the graph of a continuous probability distribution. It must satisfy the following properties:

Density Curve. A density curve is the graph of a continuous probability distribution. It must satisfy the following properties: Density Curve A density curve is the graph of a continuous probability distribution. It must satisfy the following properties: 1. The total area under the curve must equal 1. 2. Every point on the curve

More information

Independent samples t-test. Dr. Tom Pierce Radford University

Independent samples t-test. Dr. Tom Pierce Radford University Independent samples t-test Dr. Tom Pierce Radford University The logic behind drawing causal conclusions from experiments The sampling distribution of the difference between means The standard error of

More information

CALCULATIONS & STATISTICS

CALCULATIONS & STATISTICS CALCULATIONS & STATISTICS CALCULATION OF SCORES Conversion of 1-5 scale to 0-100 scores When you look at your report, you will notice that the scores are reported on a 0-100 scale, even though respondents

More information

2.5 Zeros of a Polynomial Functions

2.5 Zeros of a Polynomial Functions .5 Zeros of a Polynomial Functions Section.5 Notes Page 1 The first rule we will talk about is Descartes Rule of Signs, which can be used to determine the possible times a graph crosses the x-axis and

More information

Probabilistic Strategies: Solutions

Probabilistic Strategies: Solutions Probability Victor Xu Probabilistic Strategies: Solutions Western PA ARML Practice April 3, 2016 1 Problems 1. You roll two 6-sided dice. What s the probability of rolling at least one 6? There is a 1

More information

Spreadsheets Hop-around Cards

Spreadsheets Hop-around Cards Spreadsheets Hop-around Cards Visit us online at HOP-AROUND CARDS Preparation Print the cards out using a high quality colour printer Laminate each sheet and then cut out the individual cards to make a

More information

MEASURES OF VARIATION

MEASURES OF VARIATION NORMAL DISTRIBTIONS MEASURES OF VARIATION In statistics, it is important to measure the spread of data. A simple way to measure spread is to find the range. But statisticians want to know if the data are

More information

Frequency Distributions

Frequency Distributions Descriptive Statistics Dr. Tom Pierce Department of Psychology Radford University Descriptive statistics comprise a collection of techniques for better understanding what the people in a group look like

More information

Week 4: Standard Error and Confidence Intervals

Week 4: Standard Error and Confidence Intervals Health Sciences M.Sc. Programme Applied Biostatistics Week 4: Standard Error and Confidence Intervals Sampling Most research data come from subjects we think of as samples drawn from a larger population.

More information

Chapter 3 RANDOM VARIATE GENERATION

Chapter 3 RANDOM VARIATE GENERATION Chapter 3 RANDOM VARIATE GENERATION In order to do a Monte Carlo simulation either by hand or by computer, techniques must be developed for generating values of random variables having known distributions.

More information

Probability and Statistics Prof. Dr. Somesh Kumar Department of Mathematics Indian Institute of Technology, Kharagpur

Probability and Statistics Prof. Dr. Somesh Kumar Department of Mathematics Indian Institute of Technology, Kharagpur Probability and Statistics Prof. Dr. Somesh Kumar Department of Mathematics Indian Institute of Technology, Kharagpur Module No. #01 Lecture No. #15 Special Distributions-VI Today, I am going to introduce

More information

7. Solving Linear Inequalities and Compound Inequalities

7. Solving Linear Inequalities and Compound Inequalities 7. Solving Linear Inequalities and Compound Inequalities Steps for solving linear inequalities are very similar to the steps for solving linear equations. The big differences are multiplying and dividing

More information

Key Concept. Density Curve

Key Concept. Density Curve MAT 155 Statistical Analysis Dr. Claude Moore Cape Fear Community College Chapter 6 Normal Probability Distributions 6 1 Review and Preview 6 2 The Standard Normal Distribution 6 3 Applications of Normal

More information

Probability Distributions

Probability Distributions Learning Objectives Probability Distributions Section 1: How Can We Summarize Possible Outcomes and Their Probabilities? 1. Random variable 2. Probability distributions for discrete random variables 3.

More information

How to Make a Paper Cut-Out Luther Rose by Kelly Klages

How to Make a Paper Cut-Out Luther Rose by Kelly Klages How to Make a Paper Cut-Out Luther Rose by Kelly Klages This tutorial will teach you how to cut a traditional, 5-petal Luther rose out of paper, using the paper-folding technique for making a 5-point snowflake

More information

Question 2: How do you solve a matrix equation using the matrix inverse?

Question 2: How do you solve a matrix equation using the matrix inverse? Question : How do you solve a matrix equation using the matrix inverse? In the previous question, we wrote systems of equations as a matrix equation AX B. In this format, the matrix A contains the coefficients

More information

Quick Reference ebook

Quick Reference ebook This file is distributed FREE OF CHARGE by the publisher Quick Reference Handbooks and the author. Quick Reference ebook Click on Contents or Index in the left panel to locate a topic. The math facts listed

More information

Chapter 6: Probability

Chapter 6: Probability Chapter 6: Probability In a more mathematically oriented statistics course, you would spend a lot of time talking about colored balls in urns. We will skip over such detailed examinations of probability,

More information

Coins, Presidents, and Justices: Normal Distributions and z-scores

Coins, Presidents, and Justices: Normal Distributions and z-scores activity 17.1 Coins, Presidents, and Justices: Normal Distributions and z-scores In the first part of this activity, you will generate some data that should have an approximately normal (or bell-shaped)

More information

CURVE FITTING LEAST SQUARES APPROXIMATION

CURVE FITTING LEAST SQUARES APPROXIMATION CURVE FITTING LEAST SQUARES APPROXIMATION Data analysis and curve fitting: Imagine that we are studying a physical system involving two quantities: x and y Also suppose that we expect a linear relationship

More information

Constructing and Interpreting Confidence Intervals

Constructing and Interpreting Confidence Intervals Constructing and Interpreting Confidence Intervals Confidence Intervals In this power point, you will learn: Why confidence intervals are important in evaluation research How to interpret a confidence

More information

Week 3&4: Z tables and the Sampling Distribution of X

Week 3&4: Z tables and the Sampling Distribution of X Week 3&4: Z tables and the Sampling Distribution of X 2 / 36 The Standard Normal Distribution, or Z Distribution, is the distribution of a random variable, Z N(0, 1 2 ). The distribution of any other normal

More information

HISTOGRAMS, CUMULATIVE FREQUENCY AND BOX PLOTS

HISTOGRAMS, 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 information

25 Integers: Addition and Subtraction

25 Integers: Addition and Subtraction 25 Integers: Addition and Subtraction Whole numbers and their operations were developed as a direct result of people s need to count. But nowadays many quantitative needs aside from counting require numbers

More information

Progressing toward the standard

Progressing toward the standard Report Card Language: The student can add and subtract fluently within 20. CCSS: 2.OA.2 Fluently add and subtract within 20 using mental strategies, by end of grade, know from memory all sums of two one-digit

More information

The Normal Distribution

The Normal Distribution Chapter 6 The Normal Distribution 6.1 The Normal Distribution 1 6.1.1 Student Learning Objectives By the end of this chapter, the student should be able to: Recognize the normal probability distribution

More information

The Normal distribution

The Normal distribution The Normal distribution The normal probability distribution is the most common model for relative frequencies of a quantitative variable. Bell-shaped and described by the function f(y) = 1 2σ π e{ 1 2σ

More information

WISE Sampling Distribution of the Mean Tutorial

WISE Sampling Distribution of the Mean Tutorial Name Date Class WISE Sampling Distribution of the Mean Tutorial Exercise 1: How accurate is a sample mean? Overview A friend of yours developed a scale to measure Life Satisfaction. For the population

More information

Pre-Algebra Lecture 6

Pre-Algebra Lecture 6 Pre-Algebra Lecture 6 Today we will discuss Decimals and Percentages. Outline: 1. Decimals 2. Ordering Decimals 3. Rounding Decimals 4. Adding and subtracting Decimals 5. Multiplying and Dividing Decimals

More information

Notes on Orthogonal and Symmetric Matrices MENU, Winter 2013

Notes on Orthogonal and Symmetric Matrices MENU, Winter 2013 Notes on Orthogonal and Symmetric Matrices MENU, Winter 201 These notes summarize the main properties and uses of orthogonal and symmetric matrices. We covered quite a bit of material regarding these topics,

More information

CHAPTER 7 INTRODUCTION TO SAMPLING DISTRIBUTIONS

CHAPTER 7 INTRODUCTION TO SAMPLING DISTRIBUTIONS CHAPTER 7 INTRODUCTION TO SAMPLING DISTRIBUTIONS CENTRAL LIMIT THEOREM (SECTION 7.2 OF UNDERSTANDABLE STATISTICS) The Central Limit Theorem says that if x is a random variable with any distribution having

More information

MATHS ACTIVITIES FOR REGISTRATION TIME

MATHS ACTIVITIES FOR REGISTRATION TIME MATHS ACTIVITIES FOR REGISTRATION TIME At the beginning of the year, pair children as partners. You could match different ability children for support. Target Number Write a target number on the board.

More information

Chapter 4. Probability and Probability Distributions

Chapter 4. Probability and Probability Distributions Chapter 4. robability and robability Distributions Importance of Knowing robability To know whether a sample is not identical to the population from which it was selected, it is necessary to assess the

More information

Chapter 1: Looking at Data Section 1.1: Displaying Distributions with Graphs

Chapter 1: Looking at Data Section 1.1: Displaying Distributions with Graphs Types of Variables Chapter 1: Looking at Data Section 1.1: Displaying Distributions with Graphs Quantitative (numerical)variables: take numerical values for which arithmetic operations make sense (addition/averaging)

More information

Sta 309 (Statistics And Probability for Engineers)

Sta 309 (Statistics And Probability for Engineers) Instructor: Prof. Mike Nasab Sta 309 (Statistics And Probability for Engineers) Chapter 2 Organizing and Summarizing Data Raw Data: When data are collected in original form, they are called raw data. The

More information

ALGEBRA. sequence, term, nth term, consecutive, rule, relationship, generate, predict, continue increase, decrease finite, infinite

ALGEBRA. sequence, term, nth term, consecutive, rule, relationship, generate, predict, continue increase, decrease finite, infinite ALGEBRA Pupils should be taught to: Generate and describe sequences As outcomes, Year 7 pupils should, for example: Use, read and write, spelling correctly: sequence, term, nth term, consecutive, rule,

More information

Integers are positive and negative whole numbers, that is they are; {... 3, 2, 1,0,1,2,3...}. The dots mean they continue in that pattern.

Integers are positive and negative whole numbers, that is they are; {... 3, 2, 1,0,1,2,3...}. The dots mean they continue in that pattern. INTEGERS Integers are positive and negative whole numbers, that is they are; {... 3, 2, 1,0,1,2,3...}. The dots mean they continue in that pattern. Like all number sets, integers were invented to describe

More information

Algebra 1 Course Title

Algebra 1 Course Title Algebra 1 Course Title Course- wide 1. What patterns and methods are being used? Course- wide 1. Students will be adept at solving and graphing linear and quadratic equations 2. Students will be adept

More information

Year 9 set 1 Mathematics notes, to accompany the 9H book.

Year 9 set 1 Mathematics notes, to accompany the 9H book. Part 1: Year 9 set 1 Mathematics notes, to accompany the 9H book. equations 1. (p.1), 1.6 (p. 44), 4.6 (p.196) sequences 3. (p.115) Pupils use the Elmwood Press Essential Maths book by David Raymer (9H

More information

Maths methods Key Stage 2: Year 3 and Year 4

Maths methods Key Stage 2: Year 3 and Year 4 Maths methods Key Stage 2: Year 3 and Year 4 Maths methods and strategies taught in school now are very different from those that many parents learned at school. This can often cause confusion when parents

More information

MATH 140 Lab 4: Probability and the Standard Normal Distribution

MATH 140 Lab 4: Probability and the Standard Normal Distribution MATH 140 Lab 4: Probability and the Standard Normal Distribution Problem 1. Flipping a Coin Problem In this problem, we want to simualte the process of flipping a fair coin 1000 times. Note that the outcomes

More information

Probability. Distribution. Outline

Probability. Distribution. Outline 7 The Normal Probability Distribution Outline 7.1 Properties of the Normal Distribution 7.2 The Standard Normal Distribution 7.3 Applications of the Normal Distribution 7.4 Assessing Normality 7.5 The

More information

SKEWNESS. Measure of Dispersion tells us about the variation of the data set. Skewness tells us about the direction of variation of the data set.

SKEWNESS. Measure of Dispersion tells us about the variation of the data set. Skewness tells us about the direction of variation of the data set. SKEWNESS All about Skewness: Aim Definition Types of Skewness Measure of Skewness Example A fundamental task in many statistical analyses is to characterize the location and variability of a data set.

More information

Biggar High School Mathematics Department. National 5 Learning Intentions & Success Criteria: Assessing My Progress

Biggar High School Mathematics Department. National 5 Learning Intentions & Success Criteria: Assessing My Progress Biggar High School Mathematics Department National 5 Learning Intentions & Success Criteria: Assessing My Progress Expressions & Formulae Topic Learning Intention Success Criteria I understand this Approximation

More information

DDBA 8438: The t Test for Independent Samples Video Podcast Transcript

DDBA 8438: The t Test for Independent Samples Video Podcast Transcript DDBA 8438: The t Test for Independent Samples Video Podcast Transcript JENNIFER ANN MORROW: Welcome to The t Test for Independent Samples. My name is Dr. Jennifer Ann Morrow. In today's demonstration,

More information

No Solution Equations Let s look at the following equation: 2 +3=2 +7

No Solution Equations Let s look at the following equation: 2 +3=2 +7 5.4 Solving Equations with Infinite or No Solutions So far we have looked at equations where there is exactly one solution. It is possible to have more than solution in other types of equations that are

More information

Binary Adders: Half Adders and Full Adders

Binary Adders: Half Adders and Full Adders Binary Adders: Half Adders and Full Adders In this set of slides, we present the two basic types of adders: 1. Half adders, and 2. Full adders. Each type of adder functions to add two binary bits. In order

More information

The Big Picture. Describing Data: Categorical and Quantitative Variables Population. Descriptive Statistics. Community Coalitions (n = 175)

The Big Picture. Describing Data: Categorical and Quantitative Variables Population. Descriptive Statistics. Community Coalitions (n = 175) Describing Data: Categorical and Quantitative Variables Population The Big Picture Sampling Statistical Inference Sample Exploratory Data Analysis Descriptive Statistics In order to make sense of data,

More information

5 Homogeneous systems

5 Homogeneous systems 5 Homogeneous systems Definition: A homogeneous (ho-mo-jeen -i-us) system of linear algebraic equations is one in which all the numbers on the right hand side are equal to : a x +... + a n x n =.. a m

More information

Section 1.5 Exponents, Square Roots, and the Order of Operations

Section 1.5 Exponents, Square Roots, and the Order of Operations Section 1.5 Exponents, Square Roots, and the Order of Operations Objectives In this section, you will learn to: To successfully complete this section, you need to understand: Identify perfect squares.

More information

2x + y = 3. Since the second equation is precisely the same as the first equation, it is enough to find x and y satisfying the system

2x + y = 3. Since the second equation is precisely the same as the first equation, it is enough to find x and y satisfying the system 1. Systems of linear equations We are interested in the solutions to systems of linear equations. A linear equation is of the form 3x 5y + 2z + w = 3. The key thing is that we don t multiply the variables

More information

Creating A Grade Sheet With Microsoft Excel

Creating A Grade Sheet With Microsoft Excel Creating A Grade Sheet With Microsoft Excel Microsoft Excel serves as an excellent tool for tracking grades in your course. But its power is not limited to its ability to organize information in rows and

More information

Multiplying and Dividing Signed Numbers. Finding the Product of Two Signed Numbers. (a) (3)( 4) ( 4) ( 4) ( 4) 12 (b) (4)( 5) ( 5) ( 5) ( 5) ( 5) 20

Multiplying and Dividing Signed Numbers. Finding the Product of Two Signed Numbers. (a) (3)( 4) ( 4) ( 4) ( 4) 12 (b) (4)( 5) ( 5) ( 5) ( 5) ( 5) 20 SECTION.4 Multiplying and Dividing Signed Numbers.4 OBJECTIVES 1. Multiply signed numbers 2. Use the commutative property of multiplication 3. Use the associative property of multiplication 4. Divide signed

More information

Solving systems by elimination

Solving systems by elimination December 1, 2008 Solving systems by elimination page 1 Solving systems by elimination Here is another method for solving a system of two equations. Sometimes this method is easier than either the graphing

More information

3 Some Integer Functions

3 Some Integer Functions 3 Some Integer Functions A Pair of Fundamental Integer Functions The integer function that is the heart of this section is the modulo function. However, before getting to it, let us look at some very simple

More information

STT315 Chapter 4 Random Variables & Probability Distributions KM. Chapter 4.5, 6, 8 Probability Distributions for Continuous Random Variables

STT315 Chapter 4 Random Variables & Probability Distributions KM. Chapter 4.5, 6, 8 Probability Distributions for Continuous Random Variables Chapter 4.5, 6, 8 Probability Distributions for Continuous Random Variables Discrete vs. continuous random variables Examples of continuous distributions o Uniform o Exponential o Normal Recall: A random

More information

AP CALCULUS AB 2009 SCORING GUIDELINES

AP CALCULUS AB 2009 SCORING GUIDELINES AP CALCULUS AB 2009 SCORING GUIDELINES Question 5 x 2 5 8 f ( x ) 1 4 2 6 Let f be a function that is twice differentiable for all real numbers. The table above gives values of f for selected points in

More information

Def: The standard normal distribution is a normal probability distribution that has a mean of 0 and a standard deviation of 1.

Def: The standard normal distribution is a normal probability distribution that has a mean of 0 and a standard deviation of 1. Lecture 6: Chapter 6: Normal Probability Distributions A normal distribution is a continuous probability distribution for a random variable x. The graph of a normal distribution is called the normal curve.

More information

5.1 Simple and Compound Interest

5.1 Simple and Compound Interest 5.1 Simple and Compound Interest Question 1: What is simple interest? Question 2: What is compound interest? Question 3: What is an effective interest rate? Question 4: What is continuous compound interest?

More information

Using Formulas, Functions, and Data Analysis Tools Excel 2010 Tutorial

Using Formulas, Functions, and Data Analysis Tools Excel 2010 Tutorial Using Formulas, Functions, and Data Analysis Tools Excel 2010 Tutorial Excel file for use with this tutorial Tutor1Data.xlsx File Location http://faculty.ung.edu/kmelton/data/tutor1data.xlsx Introduction:

More information

47 Numerator Denominator

47 Numerator Denominator JH WEEKLIES ISSUE #22 2012-2013 Mathematics Fractions Mathematicians often have to deal with numbers that are not whole numbers (1, 2, 3 etc.). The preferred way to represent these partial numbers (rational

More information

Chapter 7 Section 7.1: Inference for the Mean of a Population

Chapter 7 Section 7.1: Inference for the Mean of a Population Chapter 7 Section 7.1: Inference for the Mean of a Population Now let s look at a similar situation Take an SRS of size n Normal Population : N(, ). Both and are unknown parameters. Unlike what we used

More information

Session 7 Fractions and Decimals

Session 7 Fractions and Decimals Key Terms in This Session Session 7 Fractions and Decimals Previously Introduced prime number rational numbers New in This Session period repeating decimal terminating decimal Introduction In this session,

More information

Lecture 8: More Continuous Random Variables

Lecture 8: More Continuous Random Variables Lecture 8: More Continuous Random Variables 26 September 2005 Last time: the eponential. Going from saying the density e λ, to f() λe λ, to the CDF F () e λ. Pictures of the pdf and CDF. Today: the Gaussian

More information

REPEATED TRIALS. The probability of winning those k chosen times and losing the other times is then p k q n k.

REPEATED TRIALS. The probability of winning those k chosen times and losing the other times is then p k q n k. REPEATED TRIALS Suppose you toss a fair coin one time. Let E be the event that the coin lands heads. We know from basic counting that p(e) = 1 since n(e) = 1 and 2 n(s) = 2. Now suppose we play a game

More information

Section 1.3 Exercises (Solutions)

Section 1.3 Exercises (Solutions) Section 1.3 Exercises (s) 1.109, 1.110, 1.111, 1.114*, 1.115, 1.119*, 1.122, 1.125, 1.127*, 1.128*, 1.131*, 1.133*, 1.135*, 1.137*, 1.139*, 1.145*, 1.146-148. 1.109 Sketch some normal curves. (a) Sketch

More information

7. Normal Distributions

7. Normal Distributions 7. Normal Distributions A. Introduction B. History C. Areas of Normal Distributions D. Standard Normal E. Exercises Most of the statistical analyses presented in this book are based on the bell-shaped

More information

In This Issue: Excel Sorting with Text and Numbers

In This Issue: Excel Sorting with Text and Numbers In This Issue: Sorting with Text and Numbers Microsoft allows you to manipulate the data you have in your spreadsheet by using the sort and filter feature. Sorting is performed on a list that contains

More information

If A is divided by B the result is 2/3. If B is divided by C the result is 4/7. What is the result if A is divided by C?

If A is divided by B the result is 2/3. If B is divided by C the result is 4/7. What is the result if A is divided by C? Problem 3 If A is divided by B the result is 2/3. If B is divided by C the result is 4/7. What is the result if A is divided by C? Suggested Questions to ask students about Problem 3 The key to this question

More information

0.8 Rational Expressions and Equations

0.8 Rational Expressions and Equations 96 Prerequisites 0.8 Rational Expressions and Equations We now turn our attention to rational expressions - that is, algebraic fractions - and equations which contain them. The reader is encouraged to

More information

Data Transforms: Natural Logarithms and Square Roots

Data Transforms: Natural Logarithms and Square Roots Data Transforms: atural Log and Square Roots 1 Data Transforms: atural Logarithms and Square Roots Parametric statistics in general are more powerful than non-parametric statistics as the former are based

More information

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS 1. SYSTEMS OF EQUATIONS AND MATRICES 1.1. Representation of a linear system. The general system of m equations in n unknowns can be written a 11 x 1 + a 12 x 2 +

More information

Pigeonhole Principle Solutions

Pigeonhole Principle Solutions Pigeonhole Principle Solutions 1. Show that if we take n + 1 numbers from the set {1, 2,..., 2n}, then some pair of numbers will have no factors in common. Solution: Note that consecutive numbers (such

More information

Grade 6 Math Circles. Binary and Beyond

Grade 6 Math Circles. Binary and Beyond Faculty of Mathematics Waterloo, Ontario N2L 3G1 The Decimal System Grade 6 Math Circles October 15/16, 2013 Binary and Beyond The cool reality is that we learn to count in only one of many possible number

More information

north seattle community college

north seattle community college INTRODUCTION TO FRACTIONS If we divide a whole number into equal parts we get a fraction: For example, this circle is divided into quarters. Three quarters, or, of the circle is shaded. DEFINITIONS: The

More information

OA3-10 Patterns in Addition Tables

OA3-10 Patterns in Addition Tables OA3-10 Patterns in Addition Tables Pages 60 63 Standards: 3.OA.D.9 Goals: Students will identify and describe various patterns in addition tables. Prior Knowledge Required: Can add two numbers within 20

More information

The Australian Curriculum Mathematics

The Australian Curriculum Mathematics The Australian Curriculum Mathematics Mathematics ACARA The Australian Curriculum Number Algebra Number place value Fractions decimals Real numbers Foundation Year Year 1 Year 2 Year 3 Year 4 Year 5 Year

More information

Hypothesis Testing for Beginners

Hypothesis Testing for Beginners Hypothesis Testing for Beginners Michele Piffer LSE August, 2011 Michele Piffer (LSE) Hypothesis Testing for Beginners August, 2011 1 / 53 One year ago a friend asked me to put down some easy-to-read notes

More information

One-Way ANOVA using SPSS 11.0. SPSS ANOVA procedures found in the Compare Means analyses. Specifically, we demonstrate

One-Way ANOVA using SPSS 11.0. SPSS ANOVA procedures found in the Compare Means analyses. Specifically, we demonstrate 1 One-Way ANOVA using SPSS 11.0 This section covers steps for testing the difference between three or more group means using the SPSS ANOVA procedures found in the Compare Means analyses. Specifically,

More information

Normal distribution. ) 2 /2σ. 2π σ

Normal distribution. ) 2 /2σ. 2π σ Normal distribution The normal distribution is the most widely known and used of all distributions. Because the normal distribution approximates many natural phenomena so well, it has developed into a

More information

What Does the Normal Distribution Sound Like?

What Does the Normal Distribution Sound Like? What Does the Normal Distribution Sound Like? Ananda Jayawardhana Pittsburg State University ananda@pittstate.edu Published: June 2013 Overview of Lesson In this activity, students conduct an investigation

More information

Descriptive Statistics

Descriptive 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 information

In this this review we turn our attention to the square root function, the function defined by the equation. f(x) = x. (5.1)

In this this review we turn our attention to the square root function, the function defined by the equation. f(x) = x. (5.1) Section 5.2 The Square Root 1 5.2 The Square Root In this this review we turn our attention to the square root function, the function defined b the equation f() =. (5.1) We can determine the domain and

More information

Lesson 1: Comparison of Population Means Part c: Comparison of Two- Means

Lesson 1: Comparison of Population Means Part c: Comparison of Two- Means Lesson : Comparison of Population Means Part c: Comparison of Two- Means Welcome to lesson c. This third lesson of lesson will discuss hypothesis testing for two independent means. Steps in Hypothesis

More information

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

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

More information

How do you compare numbers? On a number line, larger numbers are to the right and smaller numbers are to the left.

How do you compare numbers? On a number line, larger numbers are to the right and smaller numbers are to the left. The verbal answers to all of the following questions should be memorized before completion of pre-algebra. Answers that are not memorized will hinder your ability to succeed in algebra 1. Number Basics

More information

DERIVATIVES AS MATRICES; CHAIN RULE

DERIVATIVES AS MATRICES; CHAIN RULE DERIVATIVES AS MATRICES; CHAIN RULE 1. Derivatives of Real-valued Functions Let s first consider functions f : R 2 R. Recall that if the partial derivatives of f exist at the point (x 0, y 0 ), then we

More information