Contents. 13. Graphs of Trigonometric Functions 2 Example Example

Size: px
Start display at page:

Download "Contents. 13. Graphs of Trigonometric Functions 2 Example Example"

Transcription

1 Contents 13. Graphs of Trigonometric Functions 2 Example Example

2 Peterson, Technical Mathematics, 3rd edition 2 Example Use a spreadsheet and the data for the 500 steel rods in Table 13.1 to draw a histogram and box plot, and determine the mean, median, and quartiles. Solution We have reproduced the table below. Diameter Frequency To construct a histogram, enter the data in two columns similar to Table Click on Chart Wizard to begin the process. 2. Choose Column and the sub-type shown below in Figure 13.5a. 3. Press Next and then select the Column radio button since the data is entered in columns. Then select the Series tab to identify the source data for the histogram. 4. Select Add to add a series. Notice there are three dialogue boxes, one for the name, one for the y-values and one for the x-values. 5. In the name dialogue box, type Steel Rods. Move the cursor to the dialogue box identified as Category (X) axis labels and then go to the table and click and drag over Column A to select those values. (See Figure 13.5b.) FIGURE 13.5a FIGURE 13.5b 6. Move the cursor to the dialogue box entitled Values and select the values in Column B as shown in Figure 13.5c. FIGURE 13.5c

3 Peterson, Technical Mathematics, 3rd edition 3 As you can see from the preview, the histogram is just about complete. 7. Complete the process by moving through the remaining steps of the process to arrive at a figure similar to the one shown in Figure 13.5d. Technically, the graph in Figure 13.5d is not a histogram because a histogram does not have any space between the bars. To remove the space, double click on one of the bars in the graph. This should open the Format Data Series window. Click on the Options tab and change the Gap width to 0. The result is shown in Figure 13.5e. FIGURE 13.5d FIGURE 13.5e To find the mean of this data, extend the table one column by adding a column representing the sum of all the entries in that row. For example, since there are 10 rods with a diameter of 9.97, then the sum of the diameters of those ten rods is = The 30 rods with a diameter of 9.98 add up to 299.4, and so on. Adding those products gives us the sum of all the diameters from which we can obtain the mean. (See Figure 13.5f.) The mean is found by first finding the sum of the frequencies in Column B (cell B15: =SUM(B4:B14)) and then dividing the total sum by the number of rods (cell C16: =C15/B15). (See Figure 13.5g.) FIGURE 13.5f FIGURE 13.5g The median is the middle number. A new column is again added to the original table. The third column, cumulative frequency, shows the total of the frequencies to that point. (See Figure 13.5h.) We can see that the median is since the 250th data entry will occur in that row. The mode is obtained by reviewing the data. It is apparent that the diameter that occurs most frequently is Thus is the mode.

4 Peterson, Technical Mathematics, 3rd edition 4 The closest a spreadsheet can come to easily producing a box plot is a scatterplot of the five quartile points used in a box plot: the minimum, the 1st Quartile, the Mean, the 3rd Quartile, and the Maximum. Figure 13.5i shows the result. FIGURE 13.5h FIGURE 13.5i

5 Peterson, Technical Mathematics, 3rd edition 5 Example Use a spreadsheet and the data for the 500 steel rods in Table 13.1 to determine its mean and standard deviation. Solution We have reproduced the table below, as Table Table 13.2 Diameter Frequency In Example we used the spreadsheet determine the mean for this data. We can approximate the standard deviation of grouped data using either of two formulas. Population Variance σ 2 = Σ(x i µ) 2 f i Σf i Sample Variance s 2 = Σ (x i x) 2 f i (Σf i ) 1 FIGURE 13.5j where x i is the midpoint or value of the ith class and f i is the frequency of the ith class. We will treat the 500 rods as a sample of a larger group and thus, we will use the second formula. We must add three columns to the data; one for the difference, another for the squared differences, and a third for the product of the squared differences and the frequency. (see Figure 13.5j). The sum of the products of the differences and the frequencies is shown in cell E15. The variance is calculated in cell B17. The square root of the variance, the standard deviation, is calculated in E18.

Contents. 9. Fractional and Quadratic Equations 2 Example Example Example

Contents. 9. Fractional and Quadratic Equations 2 Example Example Example Contents 9. Fractional and Quadratic Equations 2 Example 9.52................................ 2 Example 9.54................................ 3 Example 9.55................................ 4 1 Peterson,

More information

Richter Scale and Logarithms

Richter Scale and Logarithms activity 7.1 Richter Scale and Logarithms In this activity, you will investigate earthquake data and explore the Richter scale as a measure of the intensity of an earthquake. You will consider how numbers

More information

An area chart emphasizes the trend of each value over time. An area chart also shows the relationship of parts to a whole.

An area chart emphasizes the trend of each value over time. An area chart also shows the relationship of parts to a whole. Excel 2003 Creating a Chart Introduction Page 1 By the end of this lesson, learners should be able to: Identify the parts of a chart Identify different types of charts Create an Embedded Chart Create a

More information

Computer simulation of radioactive decay

Computer simulation of radioactive decay Computer simulation of radioactive decay y now you should have worked your way through the introduction to Maple, as well as the introduction to data analysis using Excel Now we will explore radioactive

More information

1 Introduction to Minitab

1 Introduction to Minitab 1 Introduction to Minitab Minitab is a statistical analysis software package. The software is freely available to all students and is downloadable through the Technology Tab at my.calpoly.edu. When you

More information

Statistics Add Ins.notebook. November 22, Add ins

Statistics Add Ins.notebook. November 22, Add ins Add ins We have LOADS of things we need to know for the IGCSE that you haven't learnt as part of the Bavarian Curriculum. We are now going to shoehorn in some of those topics and ideas. Nov 12 11:50 Main

More information

1.3: Describing Quantitative Data with Numbers

1.3: Describing Quantitative Data with Numbers 1.3: Describing Quantitative Data with Numbers Section 1.3 Describing Quantitative Data with Numbers After this section, you should be able to MEASURE center with the mean and median MEASURE spread with

More information

Chapter 7: Statistics Describing Data. Chapter 7: Statistics Describing Data 1 / 27

Chapter 7: Statistics Describing Data. Chapter 7: Statistics Describing Data 1 / 27 Chapter 7: Statistics Describing Data Chapter 7: Statistics Describing Data 1 / 27 Categorical Data Four ways to display categorical data: 1 Frequency and Relative Frequency Table 2 Bar graph (Pareto chart)

More information

Using Tables and Graphing Calculators in Math 11

Using Tables and Graphing Calculators in Math 11 Using Tables and Graphing Calculators in Math 11 Graphing calculators are not required for Math 11, but they are likely to be helpful, primarily because they allow you to avoid the use of tables in some

More information

Further Mathematics 2018 CORE: Data analysis Chapter 2 Summarising numerical data

Further Mathematics 2018 CORE: Data analysis Chapter 2 Summarising numerical data Chapter 2: Summarising numerical data Further Mathematics 2018 CORE: Data analysis Chapter 2 Summarising numerical data Extract from Study Design Key knowledge Types of data: categorical (nominal and ordinal)

More information

Module 2A Turning Multivariable Models into Interactive Animated Simulations

Module 2A Turning Multivariable Models into Interactive Animated Simulations Module 2A Turning Multivariable Models into Interactive Animated Simulations Using tools available in Excel, we will turn a multivariable model into an interactive animated simulation. Projectile motion,

More information

Free Fall. v gt (Eq. 4) Goals and Introduction

Free Fall. v gt (Eq. 4) Goals and Introduction Free Fall Goals and Introduction When an object is subjected to only a gravitational force, the object is said to be in free fall. This is a special case of a constant-acceleration motion, and one that

More information

Experiment: Oscillations of a Mass on a Spring

Experiment: Oscillations of a Mass on a Spring Physics NYC F17 Objective: Theory: Experiment: Oscillations of a Mass on a Spring A: to verify Hooke s law for a spring and measure its elasticity constant. B: to check the relationship between the period

More information

MEASUREMENT OF THE CHARGE TO MASS RATIO (e/m e ) OF AN ELECTRON

MEASUREMENT OF THE CHARGE TO MASS RATIO (e/m e ) OF AN ELECTRON MEASUREMENT OF THE CHARGE TO MASS RATIO (e/m e ) OF AN ELECTRON Object This experiment will allow you to observe and understand the motion of a charged particle in a magnetic field and to measure the ratio

More information

Lab 1 Uniform Motion - Graphing and Analyzing Motion

Lab 1 Uniform Motion - Graphing and Analyzing Motion Lab 1 Uniform Motion - Graphing and Analyzing Motion Objectives: < To observe the distance-time relation for motion at constant velocity. < To make a straight line fit to the distance-time data. < To interpret

More information

additionalmathematicsstatisticsadditi onalmathematicsstatisticsadditionalm athematicsstatisticsadditionalmathem aticsstatisticsadditionalmathematicsst

additionalmathematicsstatisticsadditi onalmathematicsstatisticsadditionalm athematicsstatisticsadditionalmathem aticsstatisticsadditionalmathematicsst additionalmathematicsstatisticsadditi onalmathematicsstatisticsadditionalm athematicsstatisticsadditionalmathem aticsstatisticsadditionalmathematicsst STATISTICS atisticsadditionalmathematicsstatistic

More information

Chapter 9 Ingredients of Multivariable Change: Models, Graphs, Rates

Chapter 9 Ingredients of Multivariable Change: Models, Graphs, Rates Chapter 9 Ingredients of Multivariable Change: Models, Graphs, Rates 9.1 Multivariable Functions and Contour Graphs Although Excel can easily draw 3-dimensional surfaces, they are often difficult to mathematically

More information

Homework Example Chapter 1 Similar to Problem #14

Homework Example Chapter 1 Similar to Problem #14 Chapter 1 Similar to Problem #14 Given a sample of n = 129 observations of shower-flow-rate, do this: a.) Construct a stem-and-leaf display of the data. b.) What is a typical, or representative flow rate?

More information

α m ! m or v T v T v T α m mass

α m ! m or v T v T v T α m mass FALLING OBJECTS (WHAT TO TURN IN AND HOW TO DO SO) In the real world, because of air resistance, objects do not fall indefinitely with constant acceleration. One way to see this is by comparing the fall

More information

EDEXCEL ANALYTICAL METHODS FOR ENGINEERS H1 UNIT 2 - NQF LEVEL 4 OUTCOME 4 - STATISTICS AND PROBABILITY TUTORIAL 3 LINEAR REGRESSION

EDEXCEL ANALYTICAL METHODS FOR ENGINEERS H1 UNIT 2 - NQF LEVEL 4 OUTCOME 4 - STATISTICS AND PROBABILITY TUTORIAL 3 LINEAR REGRESSION EDEXCEL AALYTICAL METHODS FOR EGIEERS H1 UIT - QF LEVEL 4 OUTCOME 4 - STATISTICS AD PROBABILITY TUTORIAL 3 LIEAR REGRESSIO Tabular and graphical form: data collection methods; histograms; bar charts; line

More information

MEASUREMENT OF THE CHARGE TO MASS RATIO (e/m e ) OF AN ELECTRON

MEASUREMENT OF THE CHARGE TO MASS RATIO (e/m e ) OF AN ELECTRON MEASUREMENT OF THE CHARGE TO MASS RATIO (e/m e ) OF AN ELECTRON Object This experiment will allow you to observe and understand the motion of a charged particle in a magnetic field and to measure the ratio

More information

OECD QSAR Toolbox v.4.1. Tutorial of how to use Automated workflow for ecotoxicological prediction

OECD QSAR Toolbox v.4.1. Tutorial of how to use Automated workflow for ecotoxicological prediction OECD QSAR Toolbox v.4.1 Tutorial of how to use Automated workflow for ecotoxicological prediction Outlook Aim Automated workflow The exercise Report The OECD QSAR Toolbox for Grouping Chemicals into Categories

More information

Electric Fields and Equipotentials

Electric Fields and Equipotentials OBJECTIVE Electric Fields and Equipotentials To study and describe the two-dimensional electric field. To map the location of the equipotential surfaces around charged electrodes. To study the relationship

More information

Density Curves and the Normal Distributions. Histogram: 10 groups

Density Curves and the Normal Distributions. Histogram: 10 groups Density Curves and the Normal Distributions MATH 2300 Chapter 6 Histogram: 10 groups 1 Histogram: 20 groups Histogram: 40 groups 2 Histogram: 80 groups Histogram: 160 groups 3 Density Curve Density Curves

More information

Some hints for the Radioactive Decay lab

Some hints for the Radioactive Decay lab Some hints for the Radioactive Decay lab Edward Stokan, March 7, 2011 Plotting a histogram using Microsoft Excel The way I make histograms in Excel is to put the bounds of the bin on the top row beside

More information

Descriptive Statistics C H A P T E R 5 P P

Descriptive Statistics C H A P T E R 5 P P Descriptive Statistics C H A P T E R 5 P P 1 1 0-130 Graphing data Frequency distributions Bar graphs Qualitative variable (categories) Bars don t touch Histograms Frequency polygons Quantitative variable

More information

1 Introduction to Computational Chemistry (Spartan)

1 Introduction to Computational Chemistry (Spartan) 1 Introduction to Computational Chemistry (Spartan) Start Spartan by clicking Start / Programs / Spartan Then click File / New Exercise 1 Study of H-X-H Bond Angles (Suitable for general chemistry) Structure

More information

1. AN INTRODUCTION TO DESCRIPTIVE STATISTICS. No great deed, private or public, has ever been undertaken in a bliss of certainty.

1. AN INTRODUCTION TO DESCRIPTIVE STATISTICS. No great deed, private or public, has ever been undertaken in a bliss of certainty. CIVL 3103 Approximation and Uncertainty J.W. Hurley, R.W. Meier 1. AN INTRODUCTION TO DESCRIPTIVE STATISTICS No great deed, private or public, has ever been undertaken in a bliss of certainty. - Leon Wieseltier

More information

LAB 5 INSTRUCTIONS LINEAR REGRESSION AND CORRELATION

LAB 5 INSTRUCTIONS LINEAR REGRESSION AND CORRELATION LAB 5 INSTRUCTIONS LINEAR REGRESSION AND CORRELATION In this lab you will learn how to use Excel to display the relationship between two quantitative variables, measure the strength and direction of the

More information

UNIVERSITY OF MASSACHUSETTS Department of Biostatistics and Epidemiology BioEpi 540W - Introduction to Biostatistics Fall 2004

UNIVERSITY OF MASSACHUSETTS Department of Biostatistics and Epidemiology BioEpi 540W - Introduction to Biostatistics Fall 2004 UNIVERSITY OF MASSACHUSETTS Department of Biostatistics and Epidemiology BioEpi 50W - Introduction to Biostatistics Fall 00 Exercises with Solutions Topic Summarizing Data Due: Monday September 7, 00 READINGS.

More information

How spread out is the data? Are all the numbers fairly close to General Education Statistics

How spread out is the data? Are all the numbers fairly close to General Education Statistics How spread out is the data? Are all the numbers fairly close to General Education Statistics each other or not? So what? Class Notes Measures of Dispersion: Range, Standard Deviation, and Variance (Section

More information

Tests for Two Coefficient Alphas

Tests for Two Coefficient Alphas Chapter 80 Tests for Two Coefficient Alphas Introduction Coefficient alpha, or Cronbach s alpha, is a popular measure of the reliability of a scale consisting of k parts. The k parts often represent k

More information

How many states. Record high temperature

How many states. Record high temperature Record high temperature How many states Class Midpoint Label 94.5 99.5 94.5-99.5 0 97 99.5 104.5 99.5-104.5 2 102 102 104.5 109.5 104.5-109.5 8 107 107 109.5 114.5 109.5-114.5 18 112 112 114.5 119.5 114.5-119.5

More information

Review for Exam #1. Chapter 1. The Nature of Data. Definitions. Population. Sample. Quantitative data. Qualitative (attribute) data

Review for Exam #1. Chapter 1. The Nature of Data. Definitions. Population. Sample. Quantitative data. Qualitative (attribute) data Review for Exam #1 1 Chapter 1 Population the complete collection of elements (scores, people, measurements, etc.) to be studied Sample a subcollection of elements drawn from a population 11 The Nature

More information

Using SPSS for One Way Analysis of Variance

Using SPSS for One Way Analysis of Variance Using SPSS for One Way Analysis of Variance This tutorial will show you how to use SPSS version 12 to perform a one-way, between- subjects analysis of variance and related post-hoc tests. This tutorial

More information

Computational Study of Chemical Kinetics (GIDES)

Computational Study of Chemical Kinetics (GIDES) Computational Study of Chemical Kinetics (GIDES) Software Introduction Berkeley Madonna (http://www.berkeleymadonna.com) is a dynamic modeling program in which relational diagrams are created using a graphical

More information

Introduction to Statistics

Introduction to Statistics Introduction to Statistics Data and Statistics Data consists of information coming from observations, counts, measurements, or responses. Statistics is the science of collecting, organizing, analyzing,

More information

Using the Budget Features in Quicken 2008

Using the Budget Features in Quicken 2008 Using the Budget Features in Quicken 2008 Quicken budgets can be used to summarize expected income and expenses for planning purposes. The budget can later be used in comparisons to actual income and expenses

More information

Newton's 2 nd Law. . Your end results should only be interms of m

Newton's 2 nd Law. . Your end results should only be interms of m Newton's nd Law Introduction: In today's lab you will demonstrate the validity of Newton's Laws in predicting the motion of a simple mechanical system. The system that you will investigate consists of

More information

Describing distributions with numbers

Describing distributions with numbers Describing distributions with numbers A large number or numerical methods are available for describing quantitative data sets. Most of these methods measure one of two data characteristics: The central

More information

Harvard Life Science Outreach December 7, 2017 Measuring ecosystem carbon fluxes using eddy covariance data ACTIVITIES I. NAME THAT ECOSYSTEM!

Harvard Life Science Outreach December 7, 2017 Measuring ecosystem carbon fluxes using eddy covariance data ACTIVITIES I. NAME THAT ECOSYSTEM! Harvard Life Science Outreach December 7, 2017 Measuring ecosystem carbon fluxes using eddy covariance data ACTIVITIES I. NAME THAT ECOSYSTEM! Objective: Distinguish ecosystems (tropical forest vs. temperate

More information

Comparing whole genomes

Comparing whole genomes BioNumerics Tutorial: Comparing whole genomes 1 Aim The Chromosome Comparison window in BioNumerics has been designed for large-scale comparison of sequences of unlimited length. In this tutorial you will

More information

Review: Central Measures

Review: Central Measures Review: Central Measures Mean, Median and Mode When do we use mean or median? If there is (are) outliers, use Median If there is no outlier, use Mean. Example: For a data 1, 1.2, 1.5, 1.7, 1.8, 1.9, 2.3,

More information

EXCELLING WITH BIOLOGICAL MODELS FROM THE CLASSROOM T0 RESEARCH

EXCELLING WITH BIOLOGICAL MODELS FROM THE CLASSROOM T0 RESEARCH EXCELLING WITH BIOLOGICAL MODELS FROM THE CLASSROOM T0 RESEARCH Timothy D. Comar Benedictine University Department of Mathematics 5700 College Road Lisle, IL 60532 tcomar@ben.edu Introduction Computer

More information

1. Exploratory Data Analysis

1. Exploratory Data Analysis 1. Exploratory Data Analysis 1.1 Methods of Displaying Data A visual display aids understanding and can highlight features which may be worth exploring more formally. Displays should have impact and be

More information

LAB 3 INSTRUCTIONS SIMPLE LINEAR REGRESSION

LAB 3 INSTRUCTIONS SIMPLE LINEAR REGRESSION LAB 3 INSTRUCTIONS SIMPLE LINEAR REGRESSION In this lab you will first learn how to display the relationship between two quantitative variables with a scatterplot and also how to measure the strength of

More information

Intermediate Algebra Summary - Part I

Intermediate Algebra Summary - Part I Intermediate Algebra Summary - Part I This is an overview of the key ideas we have discussed during the first part of this course. You may find this summary useful as a study aid, but remember that the

More information

Sets and Set notation. Algebra 2 Unit 8 Notes

Sets and Set notation. Algebra 2 Unit 8 Notes Sets and Set notation Section 11-2 Probability Experimental Probability experimental probability of an event: Theoretical Probability number of time the event occurs P(event) = number of trials Sample

More information

Experiment 0 ~ Introduction to Statistics and Excel Tutorial. Introduction to Statistics, Error and Measurement

Experiment 0 ~ Introduction to Statistics and Excel Tutorial. Introduction to Statistics, Error and Measurement Experiment 0 ~ Introduction to Statistics and Excel Tutorial Many of you already went through the introduction to laboratory practice and excel tutorial in Physics 1011. For that reason, we aren t going

More information

Polynomial Functions and Their Graphs. Definition of a Polynomial Function: numbers, with a n 0. The function defined by

Polynomial Functions and Their Graphs. Definition of a Polynomial Function: numbers, with a n 0. The function defined by Polynomial Functions and Their Graphs Definition of a Polynomial Function: Let n be a nonnegative number and let a n, a n 1, a 2, a 1, a 0 be real numbers, with a n 0. The function defined by f(x) = a

More information

OECD QSAR Toolbox v.4.1. Step-by-step example for building QSAR model

OECD QSAR Toolbox v.4.1. Step-by-step example for building QSAR model OECD QSAR Toolbox v.4.1 Step-by-step example for building QSAR model Background Objectives The exercise Workflow of the exercise Outlook 2 Background This is a step-by-step presentation designed to take

More information

Falling Bodies (last

Falling Bodies (last Dr. Larry Bortner Purpose Falling Bodies (last edited ) To investigate the motion of a body under constant acceleration, specifically the motion of a mass falling freely to Earth. To verify the parabolic

More information

PubHlth 540 Fall Summarizing Data Page 1 of 18. Unit 1 - Summarizing Data Practice Problems. Solutions

PubHlth 540 Fall Summarizing Data Page 1 of 18. Unit 1 - Summarizing Data Practice Problems. Solutions PubHlth 50 Fall 0. Summarizing Data Page of 8 Unit - Summarizing Data Practice Problems Solutions #. a. Qualitative - ordinal b. Qualitative - nominal c. Quantitative continuous, ratio d. Qualitative -

More information

1. The Basic X-Y Scatter Plot

1. The Basic X-Y Scatter Plot 1. The Basic X-Y Scatter Plot EXCEL offers a wide range of plots; however, this discussion will be restricted to generating XY scatter plots in various formats. The easiest way to begin is to highlight

More information

Chapter 1:Descriptive statistics

Chapter 1:Descriptive statistics Slide 1.1 Chapter 1:Descriptive statistics Descriptive statistics summarises a mass of information. We may use graphical and/or numerical methods Examples of the former are the bar chart and XY chart,

More information

Lecture #19 MINEQL: Intro & Tutorial Benjamin; Chapter 6

Lecture #19 MINEQL: Intro & Tutorial Benjamin; Chapter 6 Updated: 6 October 2013 Print version Lecture #19 MINEQL: Intro & Tutorial Benjamin; Chapter 6 David Reckhow CEE 680 #19 1 MINEQL today MINEQL is available from Environmental Research Software: http://www.mineql.com/

More information

Stochastic Modelling

Stochastic Modelling Stochastic Modelling Simulating Random Walks and Markov Chains This lab sheets is available for downloading from www.staff.city.ac.uk/r.j.gerrard/courses/dam/, as is the spreadsheet mentioned in section

More information

MATH 1150 Chapter 2 Notation and Terminology

MATH 1150 Chapter 2 Notation and Terminology MATH 1150 Chapter 2 Notation and Terminology Categorical Data The following is a dataset for 30 randomly selected adults in the U.S., showing the values of two categorical variables: whether or not the

More information

Fog Monitor 100 (FM 100) Extinction Module. Operator Manual

Fog Monitor 100 (FM 100) Extinction Module. Operator Manual Particle Analysis and Display System (PADS): Fog Monitor 100 (FM 100) Extinction Module Operator Manual DOC-0217 Rev A-1 PADS 2.7.3, FM 100 Extinction Module 2.7.0 5710 Flatiron Parkway, Unit B Boulder,

More information

Shifting Reactions B

Shifting Reactions B Shifting Reactions B Name Lab Section Log on to the Internet. Type the following address into the location-input line of your browser: http://introchem.chem.okstate.edu/dcicla/ergbn.htm This will load

More information

Dose-Response Analysis Report

Dose-Response Analysis Report Contents Introduction... 1 Step 1 - Treatment Selection... 2 Step 2 - Data Column Selection... 2 Step 3 - Chemical Selection... 2 Step 4 - Rate Verification... 3 Step 5 - Sample Verification... 4 Step

More information

Simple Linear Regression

Simple Linear Regression CHAPTER 13 Simple Linear Regression CHAPTER OUTLINE 13.1 Simple Linear Regression Analysis 13.2 Using Excel s built-in Regression tool 13.3 Linear Correlation 13.4 Hypothesis Tests about the Linear Correlation

More information

Astron 104 Laboratory #4 Orbital Motion of a Planet

Astron 104 Laboratory #4 Orbital Motion of a Planet Name: Date: Section: Astron 104 Laboratory #4 Orbital Motion of a Planet Introduction The nature of the Solar System was first derived from careful measurements of the positions of the planets in the night

More information

CHAPTER 2: Describing Distributions with Numbers

CHAPTER 2: Describing Distributions with Numbers CHAPTER 2: Describing Distributions with Numbers The Basic Practice of Statistics 6 th Edition Moore / Notz / Fligner Lecture PowerPoint Slides Chapter 2 Concepts 2 Measuring Center: Mean and Median Measuring

More information

Last Lecture. Distinguish Populations from Samples. Knowing different Sampling Techniques. Distinguish Parameters from Statistics

Last Lecture. Distinguish Populations from Samples. Knowing different Sampling Techniques. Distinguish Parameters from Statistics Last Lecture Distinguish Populations from Samples Importance of identifying a population and well chosen sample Knowing different Sampling Techniques Distinguish Parameters from Statistics Knowing different

More information

ICM-Chemist How-To Guide. Version 3.6-1g Last Updated 12/01/2009

ICM-Chemist How-To Guide. Version 3.6-1g Last Updated 12/01/2009 ICM-Chemist How-To Guide Version 3.6-1g Last Updated 12/01/2009 ICM-Chemist HOW TO IMPORT, SKETCH AND EDIT CHEMICALS How to access the ICM Molecular Editor. 1. Click here 2. Start sketching How to sketch

More information

Frequency and Histograms

Frequency and Histograms Warm Up Lesson Presentation Lesson Quiz Algebra 1 Create stem-and-leaf plots. Objectives Create frequency tables and histograms. Vocabulary stem-and-leaf plot frequency frequency table histogram cumulative

More information

Build An Atom Simulation Build Ions and Isotopes

Build An Atom Simulation Build Ions and Isotopes Build An Atom Simulation Build Ions and Isotopes Introduction: Atoms are the smallest things that make up all matters. Atoms are made of three subatomic particles; protons, neutrons, and electrons. In

More information

Name: Period: Date: Luquillo CZO Data Analysis Activities

Name: Period: Date: Luquillo CZO Data Analysis Activities Name: Period: Date: Luquillo CZO Data Analysis Activities What is the Relationship Between Water Hardness and Conductivity? Introduction: Scientists often learn about the quality of stream water and how

More information

Passing-Bablok Regression for Method Comparison

Passing-Bablok Regression for Method Comparison Chapter 313 Passing-Bablok Regression for Method Comparison Introduction Passing-Bablok regression for method comparison is a robust, nonparametric method for fitting a straight line to two-dimensional

More information

Using a graphic display calculator

Using a graphic display calculator 12 Using a graphic display calculator CHAPTER OBJECTIVES: This chapter shows you how to use your graphic display calculator (GDC) to solve the different types of problems that you will meet in your course.

More information

1. Download the comma separated(.csv) file at: Or go to the opendata homepage and

1. Download the comma separated(.csv) file at:  Or go to the opendata homepage and These are instructions for creating an invariant mass histogram using EXCEL and CERN s open data. The data is from dimuon decay and will peak at around 90 GeV for the Z boson. This is actual data from

More information

SCI 550: AP Physics C

SCI 550: AP Physics C 2017 Summer Assignment SCI 550: AP Physics C King School SCI 550: AP Physics C Summer Assignment, Part 1 Welcome to AP Physics at King! Both AP Physics 1 and C (mechanics) are college level courses that

More information

Boyle s Law and Charles Law Activity

Boyle s Law and Charles Law Activity Boyle s Law and Charles Law Activity Introduction: This simulation helps you to help you fully understand 2 Gas Laws: Boyle s Law and Charles Law. These laws are very simple to understand, but are also

More information

Chapter 1: Exploring Data

Chapter 1: Exploring Data Chapter 1: Exploring Data Section 1.3 with Numbers The Practice of Statistics, 4 th edition - For AP* STARNES, YATES, MOORE Chapter 1 Exploring Data Introduction: Data Analysis: Making Sense of Data 1.1

More information

Rutherford s Scattering Explanation

Rutherford s Scattering Explanation Exploration: Rutherford s Scattering Explanation The purpose of this exploration is to become familiar with Rutherford s analysis that formed a crucial part of his idea of a nuclear atom. To assist you

More information

Chapter 3. Measuring data

Chapter 3. Measuring data Chapter 3 Measuring data 1 Measuring data versus presenting data We present data to help us draw meaning from it But pictures of data are subjective They re also not susceptible to rigorous inference Measuring

More information

Wikipedia - Stellar classification:

Wikipedia - Stellar classification: Stars and Hertzprung-Russell Diagram Introductory Astronomy laboratory exercise with Stellarium Mike Chu Name Stellarium is an open source and cross-platform application from www.stellarium.org. A star

More information

Statistics 1. Edexcel Notes S1. Mathematical Model. A mathematical model is a simplification of a real world problem.

Statistics 1. Edexcel Notes S1. Mathematical Model. A mathematical model is a simplification of a real world problem. Statistics 1 Mathematical Model A mathematical model is a simplification of a real world problem. 1. A real world problem is observed. 2. A mathematical model is thought up. 3. The model is used to make

More information

In this activity, students will compare weather data from to determine if there is a warming trend in their community.

In this activity, students will compare weather data from to determine if there is a warming trend in their community. Overview: In this activity, students will compare weather data from 1910-2000 to determine if there is a warming trend in their community. Objectives: The student will: use the Internet to locate scientific

More information

Using Microsoft Excel

Using Microsoft Excel Using Microsoft Excel Objective: Students will gain familiarity with using Excel to record data, display data properly, use built-in formulae to do calculations, and plot and fit data with linear functions.

More information

How to Make or Plot a Graph or Chart in Excel

How to Make or Plot a Graph or Chart in Excel This is a complete video tutorial on How to Make or Plot a Graph or Chart in Excel. To make complex chart like Gantt Chart, you have know the basic principles of making a chart. Though I have used Excel

More information

Describing distributions with numbers

Describing distributions with numbers Describing distributions with numbers A large number or numerical methods are available for describing quantitative data sets. Most of these methods measure one of two data characteristics: The central

More information

Regression Using an Excel Spreadsheet Using Technology to Determine Regression

Regression Using an Excel Spreadsheet Using Technology to Determine Regression Regression Using an Excel Spreadsheet Enter your data in columns A and B for the x and y variable respectively Highlight the entire data series by selecting it with the mouse From the Insert menu select

More information

Introduction to statistical modelling

Introduction to statistical modelling M249 Practical modern statistics Introductory Unit Introduction to statistical modelling About this module M249 Practical modern statistics uses the software packages IBM SPSS Statistics (SPSS Inc.) and

More information

The Rain in Spain - Tableau Public Workbook

The Rain in Spain - Tableau Public Workbook The Rain in Spain - Tableau Public Workbook This guide will take you through the steps required to visualize how the rain falls in Spain with Tableau public. (All pics from Mac version of Tableau) Workbook

More information

Pre-Calculus I. For example, the system. x y 2 z. may be represented by the augmented matrix

Pre-Calculus I. For example, the system. x y 2 z. may be represented by the augmented matrix Pre-Calculus I 8.1 Matrix Solutions to Linear Systems A matrix is a rectangular array of elements. o An array is a systematic arrangement of numbers or symbols in rows and columns. Matrices (the plural

More information

through any three given points if and only if these points are not collinear.

through any three given points if and only if these points are not collinear. Discover Parabola Time required 45 minutes Teaching Goals: 1. Students verify that a unique parabola with the equation y = ax + bx+ c, a 0, exists through any three given points if and only if these points

More information

Independent Samples ANOVA

Independent Samples ANOVA Independent Samples ANOVA In this example students were randomly assigned to one of three mnemonics (techniques for improving memory) rehearsal (the control group; simply repeat the words), visual imagery

More information

Esterification in a PFR with Aspen Plus V8.0

Esterification in a PFR with Aspen Plus V8.0 Esterification in a PFR with Aspen Plus V8.0 1. Lesson Objectives Use Aspen Plus to determine whether a given reaction is technically feasible using a plug flow reactor. 2. Prerequisites Aspen Plus V8.0

More information

OECD QSAR Toolbox v.4.1. Tutorial illustrating new options for grouping with metabolism

OECD QSAR Toolbox v.4.1. Tutorial illustrating new options for grouping with metabolism OECD QSAR Toolbox v.4.1 Tutorial illustrating new options for grouping with metabolism Outlook Background Objectives Specific Aims The exercise Workflow 2 Background Grouping with metabolism is a procedure

More information

Applying Newton s Second Law. 8.01T Sept 22, 2004

Applying Newton s Second Law. 8.01T Sept 22, 2004 Applying Newton s Second Law 8.01T Sept 22, 2004 Reference Frame Coordinate system with an observer placed at origin is a reference frame in which the position, velocity, and acceleration of objects are

More information

Student Exploration: Cell Division

Student Exploration: Cell Division Name: Date: Student Exploration: Cell Division Prior Knowledge Questions (Do these BEFORE using the Gizmo.) 1. What is the purpose of this activity? 2. Cells reproduce by splitting in half, a process called

More information

Purpose: Materials: WARNING! Section: Partner 2: Partner 1:

Purpose: Materials: WARNING! Section: Partner 2: Partner 1: Partner 1: Partner 2: Section: PLEASE NOTE: You will need this particular lab report later in the semester again for the homework of the Rolling Motion Experiment. When you get back this graded report,

More information

Chapter 3. Data Description

Chapter 3. Data Description Chapter 3. Data Description Graphical Methods Pie chart It is used to display the percentage of the total number of measurements falling into each of the categories of the variable by partition a circle.

More information

The purpose of this lab is to investigate phases of matter, temperature, and heat energy.

The purpose of this lab is to investigate phases of matter, temperature, and heat energy. 9460218_CH07_p081-090.qxd 1/20/10 9:46 PM Page 81 7 TEMPERATURE AND HEAT PURPOSE The purpose of this lab is to investigate phases of matter, temperature, and heat energy. SIMULATIONS States of Matter Figure

More information

COMPUTING AND DATA ANALYSIS WITH EXCEL. Numerical Methods of Solving Equations

COMPUTING AND DATA ANALYSIS WITH EXCEL. Numerical Methods of Solving Equations COMPUTING AND DATA ANALYSIS WITH EXCEL Numerical Methods of Solving Equations Estimating Roots of Equations 1 By graphing and inspection Important iterativemethods Bisection method Newton-Raphsonmethod

More information

Data Mining with the PDF-4 Databases. FeO Non-stoichiometric Oxides

Data Mining with the PDF-4 Databases. FeO Non-stoichiometric Oxides Data Mining with the PDF-4 Databases FeO Non-stoichiometric Oxides This is one of three example-based tutorials for using the data mining capabilities of the PDF-4+ database and it covers the following

More information

EXPERIMENT 2 Reaction Time Objectives Theory

EXPERIMENT 2 Reaction Time Objectives Theory EXPERIMENT Reaction Time Objectives to make a series of measurements of your reaction time to make a histogram, or distribution curve, of your measured reaction times to calculate the "average" or mean

More information

H. Diagnostic plots of residuals

H. Diagnostic plots of residuals H. Diagnostic plots of residuals 1. Plot residuals versus fitted values almost always a. or simple reg. this is about the same as residuals vs. x b. Look for outliers, curvature, increasing spread (funnel

More information