Practical Data Analysis With JMP 3rd Edition Robert Carver - Solutions

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The Gaia Hypothesis…a. …considers Earth as an imbalanced mother system of environmental, social and economic subsystems.b. …blames missing governmental interventions as the main problem for the Gaia phenomenon to occur.c. …was developed by the ancient Greek philosopher Plato. He referred to
The world’s most severe issues and crises threatening life on planet Earth…a. …are described in many frameworks such as the Sustainable Development Goals (SDGs), Millennium Development Goals (MDG) and the World Development Indicators (WDI).b. …should be solved one-by-one.c. …include
The figure and explanation illustrating the mutual relationship between society, environment, and economy…a. …describes how economy uses natural resources for the production of goods in the intersection between environment and society.b. …is related to the three main dimensions of sustainable
Responsible business…a. …aims at a positive fit, a situation achieving positive social and environmental impact. If necessary for achieving this positive impact, businesses should even accept to become unprofitable.b. …is related to terms such as corporate citizenship and business ethics.c.
How does this change alter the analysis, if at all?
Comment on noteworthy features of the chart.b. Repeat the analysis with a sample size of
Scenario: The data table called Earthquakes contains earthquake measurements across the entire globe for one month of 2009. Although this refers to a natural process of geologic activity, we can use control charts to look for changes in earthquake activity.The key variable is Magnitude, which
Scenario: Let’s look again at some airline delays data from Chicago. This time, we will consider all flights from March 2019 and focus on departure delays for United Airlines flights. We will need to filter the data found in Airline delays 3.Start by using the global Data Filter to include only
Scenario: The World Bank and other international organizations monitor many forms of technological development around the world. Elsewhere, we have looked at other Sustainable Development Indicators. In this exercise, we will study carbon dioxide emissions between 2000 and 2016. The relevant data
To do that, choose your Y variable, click the red triangle in the upper left, and choose Set Sample Size; specify n = 4.a. Create an appropriate control chart for annual solid waste delivered from Bangor(that is, use a sample size of 4 quarterly observations). Comment on important or noteworthy
Scenario: In the United States, the management of solid waste is a substantial challenge. Landfills have closed in many parts of the nation, and efforts have been made to reduce waste, increase recycling, and otherwise control the burgeoning stream of waste materials. Our data table Maine SW
Scenario: Let’s continue our analysis of the Pipeline Safety data.a. Create a Pareto chart for LEAK_TYPE. Report on your findings.b. Create one or more control charts to examine variation in the TOTAL_COST by Year. Then click the red triangle in the upper left, choose Local Data Filter, and
How does this chart compare to the one for primary goods? What might explain the similarities and differences?d. Look at the R chart more closely. What pattern or patterns do you see, and what might account for them?
This chart looks very different from the ones that we have seen earlier. Does this indicate a problem? (Hint: Think about what this variable represents.) Why is this chart so different from the ones in the chapter?b. Look at the R chart more closely. What pattern or patterns do you see, and what
Scenario: Let’s return to our analysis of the Indian Index of Industrial Production and look more closely at some of the sub-indexes for specific types of products. For this exercise, we will treat each three-month quarter as a sample and therefore specify a sample size of 3 observations.a.
In this exercise, we will focus on flight cancellations.a. Create a P chart for the proportion of canceled flights and report on what you see.b. Create an NP chart using the columns NumCancelled and TotFlights and report on what you see.
Scenario: Let’s return to the airline data in Airline delays
Scenario: Let’s continue our analysis of the tubing diameter data (Diameter data table).As before, we will use sample sizes of 6, corresponding to the six daily measurements.a. In Phase 1, we concluded that the process was not in control. Restrict your attention to Phase 1 data once more and
Scenario: A Harvard Business Review article described an email survey conducted by Crayola.com that illustrates DOE in marketing. (Almquist and Wyner, 2001). The response variable was simply whether the email recipient completed the survey questionnaire.5 During a two-week period, surveys were
Scenario: Manufacturers frequently test materials and products to determine how long they will stand up to repeated use or to field conditions. This exercise is inspired by an article (Fernandes-Hachic and Agopyan, 2008) describing the use of a material called unplasticized polyvinyl chloride
Scenario: Social scientists, opinion pollsters, and others engaging in survey research are often concerned with low response rates in household surveys. Some survey researchers offer incentives to encourage responses, and some have investigated the effectiveness of different types of incentives. A
Comment on the advantages and disadvantages of doubling the sample size.
The simplest way to do this is to delete the factor and add a new, three-level discrete numeric factor. Make the data table and report on the factor values in the first three rows of the table.c. Use the variance prediction profiler to compare the performance of this design to one in which
Scenario: There is a growing body of evidence to suggest that sleep plays an important role in the learning process. Some neuroscientists think that our brains consolidate newly acquired learning during the sleep process so that interrupted or insufficient sleep can prevent us from completing the
Scenario: We will continue our work on sales lift in a customer loyalty program experiment but screen for effects when we want to test a total of five factors. In this problem, we will assume we are still working at the screening stage of the experiment.Use the DOE ► Definitive Design command and
Scenario: We will continue our work on concrete compressive strength.a. Return to our initial full factorial design and add a fourth categorical factor representing the type of stone used as a coarse aggregate. Set the initial values as Granite or Marble. Leave all other settings as they were
Scenario: The data table Global Temperature and CO2 contains annual measures of two variables: the concentration of carbon dioxide in the earth’s atmosphere and the mean global temperature in degrees Fahrenheit.a. Create a time series plot of the Concentration column. Looking at this series,
Scenario: Our data table called Stock Index Weekly contains weekly broad market indexes and trading volumes for six major stock markets around the world. Specifically, we have observations for every week of 2008, a year in which financial markets across the globe shuddered as a consequence of
Scenario: Our data table called MCD contains daily share prices for McDonald’s common stock for the first six months of 2019. The Daily Close column is the price of one share of stock on any given day.a. Create a time series plot of the Daily Close column. Looking at this series, which time
Scenario: The United Nations, World Bank and other international organizations monitor many forms of technological development around the world. Elsewhere we have looked at other Sustainable Development Goals. In this exercise, we will study carbon dioxide emissions between 2000 and 2016. The
Scenario: In the United States, the management of solid waste is a substantial challenge. Landfills have closed in many parts of the nation, and efforts have been made to reduce waste, increase recycling, and otherwise control the burgeoning stream of waste materials. Our data table Maine SW
Scenario: In prior chapters, we examined cross-sectional data about fertility and birth rates. In this exercise, we will look at fertility time series for several countries. The time series are all in the data table Fertility; unlike the other examples in the chapter, these figures are reported
Scenario: The United Nations and other international organizations monitor many forms of technological development around the world. In Chapter 16, we estimated the annual growth of mobile phone subscriptions in Sierra Leone. Let’s apply some of our newer techniques to the data in the Cell
Scenario: Our India Industrial Production data table also contains several other indexes, including one for consumer durable goods. Durables are long-term purchases made by households, including items such as appliances and automobiles. Before building any models, make sure that the last three rows
Scenario: Let’s continue our analysis of the Indian Index of Industrial Production.a. We used Winters’ method with an assumed season of three months. Re-estimate using this approach with a six-month “season” (that is, two different seasons per year). Compare the performance of this model to
Scenario: The data table called Global Temperature and CO2 contains estimates and readings for two important environmental measures: the concentration of carbon dioxide (CO2 parts per million) in the atmosphere and mean global temperature(degrees Fahrenheit).a. Using all available years’ data,
Scenario: The United Nations and other international organizations monitor many forms of technological development around the world. Earlier in the chapter, we examined the growth of mobile phone subscriptions in Sierra Leone. Let’s look at one year and examine the relationships between adoption
Scenario: Occasionally, a historian discovers an unsigned manuscript, musical composition, or work of art. Scholars in these fields have various methods to infer the creator of such an unattributed work, and sometimes turn to statistical methods for assistance. Let’s consider a hypothetical
Scenario: Earlier in the chapter, we estimated a logistic model using the Parkinson’s disease (PD) data. The researchers reported on the development of a new composite measure of phonation, which they called PPE.a. Run a logistic regression using PPE as the only regressor, and Status as the
Scenario: The United Nations and other international organizations monitor many forms of technological development around the world. Earlier in the chapter, we examined the growth of mobile phone subscriptions in Sierra Leone. Let’s repeat the same analysis for two other countries using the Cell
Scenario: We will continue to examine the World Development Indicators data in BirthRate 2017. Throughout the exercise, we will use BirthRate as the Y variable. We will broaden our analysis to work with other variables in that file:a. Earlier, we estimated a quadratic model with maternal mortality
Scenario: High blood pressure continues to be a leading health problem in the United States. In this problem, continue to use the NHANES2016 table. For this analysis, we will focus on just the following variables and focus on adolescent respondents between the ages of 12 and 19.a. Perform a
Scenario: Return to the NHANES2016 data table. Exclude and hide respondents under age 18, leaving both female and male adults.a. Perform a regression analysis for adult respondents with BMI as Y and use waist circumference and gender as the independent variables. The relevant columns are BMXBMI,
Scenario: In the United States, the management of solid waste is a substantial challenge. Landfills have closed in many parts of the nation, and efforts have been made to reduce waste, increase recycling, and otherwise control the burgeoning stream of waste materials. Our data table Maine SW
As a result, we can interpret a value of the IIP as a percentage of what industrial output was in the base year. So, for example, if the IIP equals 150, we know that production was 50% higher at that point than it was in the base year. The data table India Industrial Production contains IIPs for
Scenario: Industrial production refers to the manufacture of goods within a country. In this scenario we look at industrial production in India, as measured by India’s Index of Industrial Production (IIP). The IIP is a figure that compares a weighted average of industrial output from different
Scenario: Throughout the animal kingdom, animals require sleep, and there is extensive variation in the number of hours in the days that different animals sleep. The data table called Sleeping Animals contains information for more than 60 mammalian species, including the average number of hours per
Scenario: We will continue to examine the World Development Indicators data in BirthRate 2017. Throughout the exercise, we will use BirthRate as the Y variable. We will broaden our analysis to work with other variables in that file:MortUnder5: Deaths, children under 5 years per 1,000 live births
Scenario: High blood pressure continues to be a leading health problem in the United States. In this problem, continue to use the NHANES 2016 table. For this analysis, we will focus on females between the ages of 12 and 19.a. Create a 3D scatterplot of systolic blood pressure (the “top” number
Scenario: Return to the NHANES 2016 data table. Select, include, and show only female respondents ages 18 and older.a. Perform a regression analysis for adult women with BMI as Y and use waist circumference and height as the independent variables. Discuss the ways in which this model is or is not
Scenario: The data table called USA Counties contains a wide variety of measures for every county in the United States based on the 2010 Censusa. Run a regression casting sales_per_capita (retail sales dollars per person, 2007) as Y and per_capita_income as X. Analyze the residuals and report on
Scenario: We will return to the World Development Indicators data in WDI. In this scenario, we will investigate the relationship between access to improved sanitation(the percent of the population with access to sewers and the like) and life expectancy.The response column is life_exp, and the
Scenario: Many cities in the U.S. have active used-car markets. Typically, the asking price for a used car varies by model, age, mileage, and features. The data table called Used Cars contains asking prices (Price) and mileage (Miles) for three popular budget models; all cars were two years old at
Scenario: Prof. Frank Anscombe of Yale University created an artificial data set to illustrate the hazards of applying linear regression analysis without looking at a scatterplot (Anscombe 1973). His work has been very influential, and JMP includes his illustration among the sample data tables
The response variable is the Compressive Strength column, and we will examine the relationship between that variable and two candidate factor variables.a. Use Cement as the factor, run a regression analysis, and evaluate the residuals.Report on your findings in detail.b. Use Water as the factor,
Scenario: In Chapter 2, our first illustration of experimental data involved a study of the compressive strength of concrete. In this scenario, we look at a set of observations all taken at 28 days (4 weeks) after the concrete was initially formulated; the data table is called Concrete
Scenario: For many years, it has been understood that tobacco use leads to health problems related to the heart and lungs. The Tobacco Use data table contains data about the prevalence of tobacco use and of certain diseases around the world.a. Using Cancer Mortality (CancerMort) as the response
Scenario: Throughout the animal kingdom, animals require sleep, and there is extensive variation in the number of hours in the day that different animals sleep. The data table called Sleeping Animals contains information for more than 60 mammalian species, including the average number of hours per
Scenario: Franz Joseph Haydn was a successful and well-established composer when the young Mozart burst upon the cultural scene. Haydn wrote more than twice as many piano sonatas as Mozart. Use the data table Haydn to perform an analysis parallel to the one we did for Mozart.a. Evaluate the
Scenario: Stock market analysts are always on the lookout for profitable opportunities and for signs of weakness in publicly traded stocks. Market analysts make extensive use of regression models in their work, and one of the simplest ones is known as the Random, or Drunkard’s, Walk model. Simply
Scenario: How do the prices of used cars vary according to the mileage of the cars? Our data table Used Cars contains observational data about the listed prices of three popular compact car models in three different metropolitan areas in the U.S. All of the cars are two years old.a. Create a
Scenario: We will continue to examine the World Development Indicators data in BirthRate 2017. We will broaden our analysis to work with other variables in that file:o MortUnder5: Deaths, children under 5 years per 1,000 live births o MortInfant: Deaths, infants per 1,000 live birthsa. Create a
Scenario: High blood pressure continues to be a leading health problem in the United States. In this problem, continue to use the NHANES 2016 table. For this analysis, we will focus on just the following variables:o RIAGENDR: Respondent’s gender o RIDAGEYR: Respondent’s age in years o BMXWT:
Scenario: Return to the Bivariate Fit of BMXBMI By BMXWAIST report.a. Using the local data filter again, show and include adult females 18 and older.Perform a regression analysis for BMI and waist circumference for adult women, evaluate the OLS conditions for inference, and report your findings and
Scenario: The data table called USA Counties contains a wide variety of measures for every county in the United States based on the 2010 U.S. Census.a. Run a regression casting sales_per_capita (retail sales dollars per person, 2007) as Y and per_capita_income as X. Write a short paragraph
Scenario: We will return to the World Development Indicators data in WDI. In this scenario, we will investigate the relationship between access to improved sanitation(the percent of the population with access to sewers and the like) and life expectancy.The response column is life_exp and the factor
Scenario: Many cities in the U.S. have active used car markets. Typically, the asking price for a used car varies by model, age, mileage, and features. The data table called Used Cars contains asking prices (Price) and mileage (Miles) for three popular budget models;all cars were two years old at
Scenario: Prof. Frank Anscombe of Yale University created an artificial data set to illustrate the hazards of applying linear regression analysis without looking at a scatterplot (Anscombe 1973). His work has been very influential, and JMP includes his illustration among the sample data tables
Scenario: In Chapter 2, our first illustration of experimental data involved a study of the compressive strength of concrete. In this scenario, we look at a set of observations all taken at 28 days (4 weeks) after the concrete was initially formulated. The data table is Concrete28. The response
Scenario: For many years, it has been understood that tobacco use leads to health problems related to the heart and lungs. The Tobacco Use data table contains recent data about the prevalence of tobacco use and of certain diseases around the world.a. Using cancer mortality (CancerMort) as the
Scenario: Throughout the animal kingdom, animals require sleep, and there is extensive variation in the number of hours in a day that different animals sleep. The data table called Sleeping Animals contains information for more than 60 mammalian species, including the average number of hours per
Scenario: Franz Joseph Haydn was a successful and well-established composer when the young Mozart burst upon the cultural scene. Haydn wrote more than twice as many piano sonatas as Mozart. Use the data table Haydn to perform a parallel analysis to the one we did for Mozart.a. Report fully on your
Scenario: Stock market analysts are always on the lookout for profitable opportunities and for signs of weakness in publicly traded stocks. Market analysts make extensive use of regression models in their work, and one of the simplest ones is known as the random (or drunkard’s) walk model. Simply
Scenario: How do the prices of used cars vary according to the mileage of the cars? Our data table Used Cars contains observational data about the listed prices of three popular compact car models in three different metropolitan areas in the U.S. All of the cars are two years old.a. Create a
Scenario: We will continue to examine the World Development Indicators data in BirthRate 2017. We will broaden our analysis to work with other variables in that file:◦ MortUnder5: Deaths, children under 5 years per 1,000 live births◦ MortInfant: Deaths, infants per 1,000 live birthsa. Create a
Scenario: High blood pressure continues to be a leading health problem in the United States. In this problem, continue to use the NHANES 2016 data table. For this analysis, we will focus on just the following variables:◦ RIAGENDR: Respondent’s gender◦ RIDAGEYR: Respondent’s age in years◦
Summarize your findings.
Scenario: Return to the NHANES 2016 data table.a. Using the Data Filter, show and include female respondents ages 18 and older.Perform a regression analysis for BMI and waist circumference for adult women and report your findings and conclusions.b. Is waist measurement a better predictor (in other
Scenario: JMP ships illustrative data tables with the software. One of these is the Popcorn data table. It is one of the few realistic but artificial examples that we will use in this book, but because it is based on the work of three highly influential statisticians,5 it appears here.a. Perform a
Use the data filter to analyze just the Phase 1 data.a. Perform a one-way ANOVA to see how the tubing diameters vary by Operator. If you find differences, perform an appropriate multiple comparison and explain where the differences are.b. Perform a one-way ANOVA to see how the tubing diameters vary
Scenario: A company manufactures catheters, blood transfusion tubes, and other tubing for medical applications. In this particular instance, we have diameter measurements from a newly designed process to produce tubing that is designed to be 4.4 millimeters in diameter. These measurements are
Scenario: In this scenario, we return to the Pipeline Safety data table to examine the consequences of pipeline disruptions. Clear row states in case you have saved row states in a previous analysis.a. Perform a one-way ANOVA to see how the dollar amount of property damage caused by a disruption
Scenario: Does a person’s employment situation influence the amount that he or she sleeps? Our TimeUse data table can provide a foundation for analysis of this question.Initially, show and include only observations from 2017 for parts a and b.a. Perform a one-way ANOVA to see how hours of sleep
Scenario: How do prices of used cars differ, if at all, in different areas of the United States? Our data table Used Cars contains observational data about the listed prices of three popular compact car models in three different metropolitan areas in the U.S. The cities are Phoenix, AZ; Portland,
Scenario: A company that manufactures insulating materials wants to evaluate the effectiveness of three different additives to one material in their product line. The company performs an industrial experiment to evaluate the additives. For the sake of this example, these additives are called
Scenario: We will continue to examine the World Development Indicators data in the data table BirthRate 2017. We will broaden our analysis to work with other columns in that table:◦ Region: Country’s geographic region◦ Fertil: Number of births per woman◦ MortMaternal2016: Maternal
Scenario: This question looks at the NC Births data. For each of the following questions, evaluate the extent to which conditions for inference have been met, and then report on what you find when you use an appropriate technique.a. Do babies born to mothers who smoke weigh less than those born to
Scenario: Let’s look again at the TimeUse data. For each of the following questions, evaluate the extent to which conditions for inference have been met, and then report on what you find when you use an appropriate technique.a. Estimate the mean difference in the amount of time men and women
Scenario: The data table Airline Delays contains a sample of flights for four airlines destined for three busy airports. Our goal is to analyze the delay times, expressed in minutes, and compare two of the airports. First, use the Data Filter to show and include only those flights destined for
Scenario: Parkinson’s disease (PD) is a neurological disorder affecting millions of older adults around the world. Among the common symptoms are tremors, loss of balance, and difficulty in initiating movement. Other symptoms include vocal impairment. We have a data table, Parkinsons (Little,
Scenario: Go back to the full Pipeline Safety data table. Clear row states to show and include all states and years. We will compare the age of pipelines in locations controlled by the operator and those that are public rights of way.a. Use the Distribution platform to inspect the distributions of
Scenario: We will continue our analysis of the pipeline disruption data in Oklahoma and Texas. The column EST_COST_PROP_DAMAGE contains the dollar value of property damage as a consequence of the disruption.a. Report and interpret a 95% confidence interval for the difference in mean property value
Scenario: Let’s continue analyzing the data for adults in the NHANES 2016 data table.For each of the following columns, estimate the difference between the male and female respondents using a 95% confidence level.a. What is the estimated difference in Body Mass Index (BMI)?b. What is the
Scenario: Open the FAA Bird Strikes CA data table, which contains data from three airports in California: Los Angeles, Sacramento, and San Francisco. For each question below, we want to know if the attributes in question varied by location (that is, is the response variable independent of
Scenario: Open the NC Births data table. Recall that this data table contains a simple random sample of 1,000 births in North Carolina in 2004.a. Use a chi-square test of goodness of fit to test the hypothesis that a woman is as likely to give birth to a girl as to a boy. Explain what you did and
Scenario: For these questions, we return to the TimeUse data table. Use the data filter to confine the analysis to the responses from 2017.a. Are employment status and sex independent? Explain.b. Are full/part-time working status and marital status independent? Explain.c. Are employment status and
Scenario: Let us once again look at the Sleeping Animals data table.a. Are mammalian species equally likely to be classified across the five categories of the exposure index?b. Are all mammalian species equally likely to be classified across the five categories of the predation index?c. Are the
Scenario: The following questions were inspired by a 2009 article on alcohol consumption and risky behaviors (Hingson et al. 2009) based on responses to a large national survey. The data table BINGE contains summary frequency data calculated from tables provided in the article. We’ll focus on the
Scenario: In this scenario, we return to the NHANES 2016 data table containing survey data from a large number of people in the U.S. in 2016. For this analysis, we will focus on just the following variables:◦ RIDRETH1: Respondent’s racial or ethnic background◦ DMDMARTL: Respondent’s
Scenario: We will continue to examine the World Development Indicators data in BirthRate 2017. We will focus on three categorical variables in the data table.◦ Region: Global region of the country in question◦ Provider: Source of maternity leave benefits (public, private, or a combination of

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Practical Data Analysis With JMP 3rd Edition Robert Carver - Solutions

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