%!$ Easy Diy Woodworking Bench Plans For You #!@

26-drawer-slides-502 Decorative ABS Leg - 3 products. Draw a bar chart for the survey results. Are there any outliers? We drwaer having trouble finding right size trash cans. Savings are here! The answer and method 26 drawer slides 502 solution are given in Appendix E. What is the probability that a person selected visited either Disney World or Busch Gardens?

After a solid year of research and development, these new portable camping fridges are now for sale at a price that is already shocking the camping industry. Any car fridge is only as good as its compressor, and many cheap fridges use unbranded compressors that are less efficient than good name-brand compressors. At the core of every Adventure Kings 12v fridge is a genuine Secop compressor, the exact same as found in many of the most expensive camping fridges on the market today.

The genuine Secop compressors in the Adventure Kings 12v fridges are powerful, efficient and quiet in operation which makes them perfect for camping! Initially available in three different sizes, the Adventure Kings 12v fridge range covers a wide variety of uses.

The Adventure Kings 45L portable fridge freezer is perfect for a young couple just starting to build their camping gear kit, or for a family on a tight budget. It features clever fold-down handles that sit flush when not in use to conserve valuable space in the back of your vehicle, and features an internal removable food basket for easy packing and unpacking, a separate dairy case and a bright auto-on LED light.

The Adventure Kings 45L camping fridge can hold a solid 67 standard ml cans of drink! The Adventure Kings 60L camping fridge uses the same clever design as the Adventure Kings 45L fridge freezer, but substantially increases the internal compartment size.

It features the same tough, intelligent features as the 45L portable fridge, such as reversable side-opening lid, ultra-strong handles and hinges and extra thick rubber sealing around the lid for maximum efficiency.

This is a true dual-zone fridge-freezer, in that the two completely separate internal compartments can be run as either a fridge, a freezer, or as both. The Adventure Kings 70L dual-zone fridge freezer uses stainless steel hinges and over-centre latches, as well as extra-thick seals on both lids to ensure maximum efficiency.

This massive fridge can hold an incredible cans of drink! Because the Adventure Kings range of portable fridges use genuine Secop compressors, they have more than enough power to freeze anything you want. That makes the Adventure Kings fridge freezers perfect for using as a dedicated freezer on those big adventures.

Adventure Kings portable fridge-freezers have genuinely been designed by campers and 4WDers, for campers and 4WDers! These protect your battery from being drained too low, and allow you to re-charge your battery before it is run completely flat. We recommend an Adventure Kings solar panel as a hassle-free way to continually run your fridge without having to worry about running your batteries flat.

Copper is much better at transferring heat than alloy which makes the fridge run much more efficiently. For this same reason we also use a stainless steel evaporator within the Adventure Kings camping fridges, which also increases longevity. Comment on the distribution of home prices. Develop a scatter diagram with price on the vertical axis and the size of the home on. Is there a relationship between these variables?

Is the relationship direct or indirect? For homes without a pool, develop a scatter diagram with price on the vertical axis and the size of the home on the horizontal. Do the same for homes with a pool. How do the relationships between price and size for homes without a pool and homes with a pool compare? Refer to the Baseball data that report information on the 30 Major League Baseball teams for the season.

In the data set, the year opened, is the first year of operation for that stadium. Develop a box plot with the new variable, age. Are there any outliers? If so, which of the stadiums are outliers? Using the variable, salary, create a box plot. Compute the quartiles using formula 4—1. Write a brief summary of your analysis.

Draw a scatter diagram with the variable, wins, on the vertical axis and salary on the horizontal axis. What are your conclusions? Using the variable, wins, draw a dot plot. What can you conclude from this plot? Refer to the Lincolnville School District bus data. Referring to the maintenance cost variable, develop a box plot. What are the mini- mum, first quartile, median, third quartile, and maximum values? Using the median maintenance cost, develop a contingency table with bus manufac- turer as one variable and whether the maintenance cost was above or below the median as the other variable.

Chapter 1 began by describing the meaning and purpose of statistics. Next we described the different types of variables and the four levels of measurement. Chapter 2 was concerned with describing a set of observations by organizing it into a frequency distribution and then portraying the frequency distribution as a histogram or a frequency polygon. Chapter 3 began by describing measures of location, such as the mean, weighted mean, median, geometric mean, and mode.

This chapter also included measures of dispersion, or spread. Discussed in this section were the range, variance, and standard deviation. Chapter 4 included several graphing techniques such as dot plots, box plots, and scatter diagrams. We also discussed the coefficient of Wooden Side Drawer Slides You skew- ness, which reports the lack of symmetry in a set of data. Throughout this section we stressed the importance of statistical software, such as Excel and Minitab.

Many computer outputs in these chapters demonstrated how quickly and effectively a large data set can be organized into a frequency distribution, several of the measures of location or measures of variation calculated, and the information presented in graphical form. Cases The review also includes continuing cases and several small cases that let students make decisions using tools and techniques from a variety of chapters.

What is the graph called? What are the median, and first and third quartile values? Is the distribution positively skewed? Tell how you know. If yes, estimate these values. Can you determine the number of observations in the study? Century National Bank The following case will appear in subsequent review sec- tions. You will need to do some data analysis and prepare a short writ- ten report.

Remember, Mr. Selig is the president of the bank, so you will want to ensure that your report is complete and accurate. A copy of the data appears in Appendix A. Century National Bank has offices in several cities in the Midwest and the southeastern part Bottom Side Drawer Slides Yoga of the United States.

Dan Selig, president and CEO, would like to know the characteristics of his checking account custom- ers. What is the balance of a typical customer? How many other bank services do the checking ac- count customers use?

Do the customers use the ATM ser- vice and, if so, how often? What about debit cards? Who uses them, and how often are they used? To better understand the customers, Mr. Selig asked Ms.

Wendy Lamberg, director of planning, to select a sam- ple of customers and prepare a report. To begin, she has appointed a team from her staff. You are the head of the team and responsible for preparing the report. You select a random sample of 60 customers. In addition to the balance in each account at the end of last month, you determine 1 the number of ATM automatic teller machine transac- tions in the last month; 2 the number of other bank ser- vices a savings account, a certificate of deposit, etc.

Develop a graph or table that portrays the checking balances. Does it appear that there is a difference in the distribution of the accounts among the four branches? Around what value do the account bal- ances tend to cluster? Determine the mean and median of the checking ac- count balances.

Compare the mean and the median balances for the four branches. Is there a difference among the branches? Be sure to explain the difference between the mean and the median in your report. Determine the range and the standard deviation of the checking account balances. What do the first and third quartiles show? Determine the coefficient of skewness and indicate what it shows.

Because Mr. Selig does not deal with statistics daily, include a brief description and interpretation of the standard deviation and other measures. Wildcat Plumbing Supply has served the plumbing needs of Southwest Arizona for more than 40 years.

The company was founded by Mr. Terrence St. Julian and is run today by his son Cory. The company has grown from a handful of employees to more than today. Cory is concerned about several positions within the company where he has men and women doing es- sentially the same job but at different pay. To investi- gate, he collected the information below.

Suppose you are a student intern in the Accounting Department and have been given the task to write a report summarizing the situation. To kick off the project, Mr. Cory St. Julian held a meeting with his staff and you were invited. At this meeting, it was suggested that you calculate several measures of.

Practice Test The Practice Test is intended to give students an idea of content that might appear on a test and how the test might be structured.

The Practice Test includes both objective questions and problems covering the material studied in the section. Develop the charts and write the report summarizing the yearly salaries of employees at Wildcat Plumbing Supply. Does it appear that there are pay differences based on gender? At the January national sales meeting, the CEO of Kimble Products was questioned extensively regarding the com- pany policy for paying commissions to its sales represen- tatives.

The company sells sporting goods to two major. There are 40 sales representatives who call di- rectly on large-volume customers, such as the athletic de- partments at major colleges and universities and professional sports franchises.

There are 30 sales repre- sentatives who represent the company to retail stores lo- cated in shopping malls and large discounters such as Kmart and Target. Upon his return to corporate headquarters, the CEO asked the sales manager for a report comparing the com- missions earned last year by the two parts of the sales team.

The information is reported below. Write a brief re- port. Would you conclude that there is a difference? Be sure to include information in the report on both the cen- tral tendency and dispersion of the two groups. There is a practice test at the end of each review section. The tests are in two parts. The first part contains several objec- tive questions, usually in a fill-in-the-blank format. The second part is problems. In most cases, it should take 30 to 45 minutes to complete the test.

The problems require a calculator. Check the answers in the Answer Section in the back of the book. Part 1—Objective 1. The science of collecting, organizing, presenting, analyzing, and interpreting data to assist in. Methods of organizing, summarizing, and presenting data in an informative way are.

The entire set of individuals or objects of interest or the measurements obtained from all. List the two types of variables. The number of bedrooms in a house is an example of a. The jersey numbers of Major League Baseball players are an example of what level of.

The classification of students by eye color is an example of what level of measurement? The sum of the differences between each value and the mean is always equal to what value? A set of data contained 70 observations. How many classes would the 2k method suggest to.

What percent of the values in a data set are always larger than the median? The square of the standard deviation is the. The standard deviation assumes a negative value when. Which of the following is least affected by an outlier? Part 2—Problems 1. The Russell index of stock prices increased by the following amounts over the last 3 years. Connect empowers students by continually adapting to deliver precisely what they need, when they need it, and how they need it, so your class time is more engaging and effective.

By presenting assignment, assessment, and topical performance results together with a time metric that is easily visible for aggregate or individual results, Connect Insight gives the user the ability to take a just-in-time approach to teaching and learning, which was never before available.

Connect Insight presents data that empowers students and helps instructors improve class performance in a way that is efficient and effective. Using Connect improves retention rates by You can select and use any asset that enhances your lecture, including:. The level of difficulty varies, as indicated by the easy, medium, and difficult labels. Students can easily download, save the files and use the data to solve end of chapter problems.

Orris of Butler University is a full-featured Excel statistical analysis add-in that is available on the MegaStat website at www. See the website for details on supported versions. Once installed, MegaStat will always be available on the Excel add-ins ribbon with no expiration date or data limita- tions.

MegaStat performs statistical analyses within an Excel workbook. When a MegaStat menu item is selected, a dialog box pops up for data selection and options. Since MegaStat is an easy-to-use extension of Excel, students can focus on learning statistics without being distracted by the software. Ease-of-use features include Auto Expand for quick data selection and Auto Label detect.

MegaStat does most calculations found in introductory statistics textbooks, such as computing descriptive statistics, creating frequency distributions, and computing probabilities as well as hypothesis testing, ANOVA, chi-square analysis, and regression analysis simple and multiple.

MegaStat output is carefully formatted and appended to an output worksheet. Video tutorials are included that provide a walkthrough using MegaStat for typical business statistics topics. Each software product can be packaged with any McGraw-Hill business statistics text. Cannell El Paso Community College. This edition of Statistical Techniques in Business and Economics is the product of many people: students, colleagues, reviewers, and the staff at McGraw-Hill Education.

We thank them all. We wish to express our sincere gratitude to the reviewers:. Their suggestions and thorough reviews of the previous edition and the manuscript of this edi- tion make this a better text. Special thanks go to a number of people. Ed Pappanastos, Troy University, built new data sets and revised Smartbook. Wendy Bailey, Tory University, prepared the test bank.

Vickie Fry, Westmoreland County Community College, provided countless hours of digital accuracy checking and support. We also wish to thank the staff at McGraw-Hill. The information can be synced with a cell phone and displayed with a Fitbit app. Assume you know the daily number of Fitbit Flex 2 units sold last month at the Best Buy store in Collegeville, Pennsylvania. Describe a situation where the number of units sold is considered a sample.

Illustrate a second situation where the number of units sold is considered a population. See Exercise 11 and LO Then, you stop and realize the consequences of the decision. The product will need to make a profit so the pricing and the costs of production and distribution are all very important. The decision to introduce the product is based on many alternatives. So how will you know? Where do you start? Without a long experience in the industry, beginning to develop an intelligence that will make you an expert is essential.

You select three other people to work with and meet with them. The conversation focuses on what you need to know and what information and data you need. In your meeting, many questions are asked. How many competitors are already in the market? How are smartphones priced? What features does the market require? What do customers want in a smartphone? What do customers like about the existing products?

The answers will be based on business intelligence consisting of data and information collected through customer surveys, engineering analysis, and market research.

In the end, your presentation to support your decision regarding the introduction of a new smartphone is based on the statistics that you use to summarize and organize your data, the statistics that you use to compare the new product to existing products, and the statistics to esti- mate future sales, costs, and revenues.

The statistics will be the focus of the conversa- tion that you will have with your supervisor about this very important decision. As a decision maker, you will need to acquire and analyze data to support your decisions. The purpose of this text is to develop your knowledge of basic statistical techniques and methods and how to apply them to develop the business and personal intelligence that will help you make decisions.

If you look through your university catalogue, you will find that statistics is required for many college programs. As you investigate a future career in accounting, economics,.

So why is statistics a requirement in so many disciplines? A major driver of the requirement for statistics knowledge is the tech- nologies available for capturing data. Examples include the technology that Google uses to track how Internet users access websites.

As people use Google to search the Internet, Google records every search and then uses these data to sort and prioritize the results for future Internet searches. One recent estimate indicates that Google processes 20, terabytes of information per day. Big-box retailers like Target, Walmart, Kroger, and others scan every purchase and use the data to manage the distribution of products, to make decisions about marketing and sales, and to track daily and even hourly sales.

Police departments collect and use data to provide city residents with maps that communicate informa- tion about crimes committed and their location. Every organization is col- lecting and using data to develop knowledge and intelligence that will help people make informed decisions, and to track the implementation of their decisions. The graphic to the left shows the amount of data gener- ated every minute www.

A good working knowledge of sta- tistics is useful for summarizing and organizing data to provide information that is useful and supportive of decision making. Statistics is used to make valid comparisons and to predict the outcomes of decisions. In summary, there are at least three reasons for studying statistics: 1 data are collected everywhere and require statistical knowledge to.

An understanding of statistics and statistical method will help you make more effective personal and professional decisions. This question can be rephrased in two, subtly different ways: what are statistics and what is statistics? To answer the first question, a statistic is a number used to communi- cate a piece of information.

Examples of statistics are:. Each of these statistics is a numerical fact and communicates a very limited piece of in- formation that is not very useful by itself. Statistics is the set of knowledge and skills used to organize, summarize, and analyze data. The results of statistical analysis will start interesting conversations in the search for knowledge and intelligence that will help us make decisions.

For example:. Is it higher, lower, or about the same? Is there a trend of increasing or decreasing inflation? Is there a relationship between interest rates and government bonds? By collecting data and applying statistics, you can determine the required GPA to be admitted to the Master of Business Administration program at the University of Chicago, Harvard, or the University of Michigan. You can determine the likelihood that you would be admitted to a partic- ular program.

Is there a range of acceptable GPAs? You would like to own an electric car with a small carbon footprint. By collecting additional data and applying statistics, you can analyze the alternatives. For exam- ple, another choice is a hybrid car that runs on both gas and electricity such as a Toyota Prius. What additional information can be collected and summarized so that you can make a good purchase decision? Another example of using statistics to provide information to evaluate decisions is the distribution and market share of Frito-Lay products.

Data are collected on each of the Frito-Lay product lines. These data include the market share and the pounds of product sold. Statistics is used to present this information in a bar chart in Chart 1—1. It also shows the absolute measure of pounds of each product line consumed in the United States. These examples show that statistics is more than the presentation of numerical in- formation. Statistics is about collecting and processing information to create a conversa- tion, to stimulate additional questions, and to provide a basis for making decisions.

Specifically, we define statistics as:. A feature of our textbook is called Statistics in Action. Read each one carefully to get an appreciation of the wide application of statis- tics in management, economics, nursing, law enforcement, sports, and other disciplines.

William Gates, founder of Microsoft Corporation, is the richest. In this book, you will learn the basic techniques and applications of statistics that you can use to support your decisions, both personal and professional. To start, we will differentiate between descriptive and inferential statistics. Their application depends on the questions asked and the type of data available.

Descriptive Statistics Masses of unorganized data—such as the census of population, the weekly earnings of thousands of computer programmers, and the individual responses of 2, registered voters regarding their choice for president of the United States—are of little value as is. However, descriptive statistics can be used to organize data into a meaningful form. We define descriptive statistics as:. The following are examples that apply descriptive statistics to summarize a large amount of data and provide information that is easy to understand.

The longest is I, which stretches from Boston to Seattle, a distance of 3, miles. The shortest is I in New York City, which is 0. Alaska does not have any interstate highways, Texas has the most inter- state miles at 3,, and New York has the most interstate routes with As in previous years, men spent more than twice the amount women spent on the holiday. Statistical methods and techniques to generate descriptive statistics are presented in Chapters 2 and 4.

These include organizing and summarizing data with frequency distributions and presenting frequency distributions with charts and graphs. In addition, statistical measures to summarize the characteristics of a distribution are discussed in Chapter 3.

Inferential Statistics Sometimes we must make decisions based on a limited set of data. For example, we would like to know the operating characteristics, such as fuel efficiency measured by miles per gallon, of sport utility vehicles SUVs currently in use. If we spent a lot of time, money, and effort, all the owners of SUVs could be surveyed. In this case, our goal would be to survey the population of SUV owners. However, based on inferential statistics, we can survey a limited number of SUV owners and collect a sample from the population.

Samples often are used to obtain reliable estimates of population parameters. Sam- pling is discussed in Chapter 8. In the process, we make trade-offs between the time, money, and effort to collect the data and the error of estimating a population parameter. The process of sampling SUVs is illustrated in the following graphic. In this example, we would like to know the mean or average SUV fuel efficiency. The process of sampling from a population with the objective of estimating properties of a population is called inferential statistics.

Where did statistics get its start? Graunt realized that the Bills of Mortality repre- sented only a fraction of all births and deaths in London. However, he used the data to reach broad conclusions or inferences about the im- pact of disease, such as the plague, on the general population.

His logic is an example of statistical inference. His analysis and interpretation of the data are thought to mark the start of statistics. Inferential statistics is widely applied to learn something about a population in busi- ness, agriculture, politics, and government, as shown in the following examples:.

For example, 9. These program ratings are used to make decisions about advertising rates and whether to continue or cancel a program. Internal Revenue Service tax preparation volunteers were tested with three standard tax returns. In other words there were errors on about half of the returns. In this example, the statistics are used to make decisions about how to improve the accuracy rate by correcting the most common errors and improving the training of volunteers.

A feature of our text is self-review problems. There are a number of them inter- spersed throughout each chapter. The first self-review follows. Each self-review tests your comprehension of preceding material. The answer and method of solution are given in Appendix E. You can find the answer to the following self-review in 1—1 in Appendix E. We recommend that you solve each one and then check your answer. The Atlanta-based advertising firm Brandon and Associates asked a sample of 1, con- sumers to try a newly developed chicken dinner by Boston Market.

Of the 1, sampled, 1, said they would purchase the dinner if it is marketed. When an object or individual is observed and recorded as a nonnumeric characteristic, it is a qualitative variable or an attribute. Examples of qualitative variables are gender, bev- erage preference, type of vehicle owned, state of birth, and eye color.

When a variable is qualitative, we usually count the number of observations for each category and determine. For example, if we observe the variable eye color, what percent of the population has blue eyes and what percent has brown eyes? If the variable is type of vehicle, what percent of the total number of cars sold last month were SUVs? Qualitative variables are often summarized in charts and bar graphs Chapter 2.

When a variable can be reported numerically, it is called a quantitative variable. Examples of quantitative variables are the balance in your checking account, the num- ber of gigabytes of data used on your cell phone plan last month, the life of a car battery such as 42 months , and the number of people employed by a company.

Quantitative variables are either discrete or continuous. Examples of dis- crete variables are the number of bedrooms in a house 1, 2, 3, 4, etc. We count, for example, the number of cars arriving at Exit 25 on I-4, and we count the number of statistics students in each section. Notice that a home can have 3 or 4 bedrooms, but it cannot have 3. Typically, discrete variables are counted.

Observations of a continuous variable can assume any value within a specific range. Examples of continuous variables are the air pressure in a tire and the weight of a shipment of tomatoes.

Other examples are the ounces of raisins in a box of raisin bran cereal and the duration of flights from Orlando to San Diego. Grade point average GPA is a continuous variable. We could report the GPA of a particular student as 3. The usual practice is to round to 3 places—3.

Typically, continuous variables result from measuring. The level of measurement determines how data should be summarized and presented. It also will indicate the type of statistical analysis that can be performed. Here are two examples of the relationship between measurement and how we apply statistics. Suppose we assign brown a value of 1, yellow 2, blue 3, orange 4, green. It is a qualita- tive variable. How do we interpret this statistic? As a second example, in a high school track meet there are eight competitors in the meter run.

We report the order of finish and that the mean finish is 4. What does the mean finish tell us? In both of these instances, we have not used the appropriate statistics for the level of measurement. There are four levels of measurement: nominal, ordinal, interval, and ratio. The low- est, or the most primitive, measurement is the nominal level. The highest is the ratio level of measurement.

Nominal-Level Data For the nominal level of measurement, observations of a qualitative variable are mea- sured and recorded as labels or names. The labels or names can only be classified and counted. There is no particular order to the labels. They have no order. They can only be classified and counted. We simply classify the candies by color. There is no natural order.

That is, we could report the brown candies first, the orange first, or any of the other colors first. Recording the variable gender is another example of the nominal level of measurement. Suppose we count the number of students entering a football game with a student ID and report how many are men and how many are women. We could report either the men or the women first. For the data measured at the nominal level, we are limited to counting the number in each category of the variable.

Often, we convert these counts to percentages. To process the data for a variable measured at the nominal level, we often numer- ically code the labels or names. Using this procedure with an alphabetical listing of states, Wisconsin is coded 49 and Wyoming Realize that the number assigned to each state is still a label or name. The reason we assign numerical codes is to facilitate counting the number of students from each state with statistical software.

Note that assigning numbers to the states does not give us license to manipulate the codes as numerical information. Clearly, the nominal level of measurement does not permit any mathematical operation that has any valid interpretation.

Ordinal-Level Data The next higher level of measurement is the ordinal level. For this level of measure- ment a qualitative variable or attribute is either ranked or rated on a relative scale. Variables based on this level of measurement are only ranked or counted.

For example, many businesses make decisions about where to locate their facil- ities; in other words, where is the best place for their business? Business Facilities www. They are based on the evaluation of many different factors, including the cost of labor, business tax climate, quality of life, transportation infrastructure, educated workforce, and economic growth potential.

This is an example of an ordinal scale because the states are ranked in order of best to worst business climate. That is, we know the relative order of the states based. Florida 2. Utah 3. Texas 4. Georgia 5. Indiana 6. Tennessee 7. Nebraska 8. North Carolina 9. Virginia For example, in Florida had the best business climate and Utah was second. Indiana was fifth, and that was better than Tennessee but not as good as Georgia. To put it another way, we do not know if the magnitude of the differ- ence between Louisiana and Utah is the same as between Texas and Georgia.

Another example of the ordinal level measure is based on a scale that measures an attribute. This type of scale is used when students rate instructors on a variety of attri- butes. An important characteristic of using a relative measurement scale is that we cannot distinguish the magnitude of the differences between groups. Table 1—1 lists the frequencies of 60 student ratings of instructional quality for Pro- fessor James Brunner in an Introduction to Finance course.

The data are summarized based on the order of the scale used to rate the instructor. That is, they are summarized by the number of students who indicated a rating of superior 6 , good 26 , and so on. We also can convert the frequencies to percentages.

About Interval-Level Data The interval level of measurement is the next highest level. It includes all the character- istics of the ordinal level, but, in addition, the difference or interval between values is meaningful.

The interval level of measurement is based on a scale with a known unit of measurement. The Fahrenheit temperature scale is an example of the interval level of measurement. Suppose the high temperatures on three consecutive winter days in Boston are 28, 31, and 20 degrees Fahrenheit. These temperatures can be easily ranked, but we can also determine the interval or distance between temperatures. This is possible because 1 de- gree Fahrenheit represents a constant unit of measurement.

That is, the distance between 10 and 15 degrees Fahrenheit is 5 degrees, and is the same as the 5-degree distance between 50 and 55 degrees Fahrenheit. It is also important to note that 0 is just a point on the scale. It does not represent the absence of the condition. The measurement of zero degrees Fahrenheit does not represent the absence of heat or cold. But by our own measurement scale, it is cold!

A major limitation of a variable measured at the interval level is that we cannot make statements similar to 20 degrees Fahrenheit is twice as warm as 10 degrees Fahrenheit. Listed below is information on several dimensions of a standard U. Observe that as the size changes by two units say from size 10 to size 12 or from size 24 to size 26 , each of the mea- surements increases by 2 inches. To put it another way, the intervals are the same.

There is no natural zero point for dress size. Instead, it would have a inch bust, inch waist, and inch hips. More- over, the ratios are not reasonable. If you divide a size 28 by a size 14, you do not get the same answer as dividing a size 20 by a size In short, if the distances between the numbers make sense, but the ratios do not, then you have an interval scale of measurement.

Ratio-Level Data Almost all quantitative variables are recorded on the ratio level of measurement. It has all the characteristics of the interval level, but, in addition, the 0 point and the ratio between two numbers are both meaningful. Examples of the ratio scale of measurement include wages, units of production, weight, changes in stock prices, distance between branch offices, and height. Money is also a good illustration. Weight also is measured at the ratio level of measurement.

If a scale is correctly calibrated, then it will read 0 when nothing is on the scale. Further, something that weighs 1 pound is half as heavy as something that weighs 2 pounds. Table 1—2 illustrates the ratio scale of measurement for the variable, annual income for four father-and-son combinations.

Observe that the senior Lahey earns twice as much as his son. In the Rho family, the son makes twice as much as the father. Chart 1—3 summarizes the major characteristics of the various levels of measure- ment. The level of measurement will determine the type of statistical methods that can be used to analyze a variable. Statistical methods to analyze variables measured on a nominal level are discussed in Chapter 15; methods for ordinal-level variables are dis- cussed in Chapter Statistical methods to analyze variables measured on an interval or ratio level are presented in Chapters 9 through What level of measure- ment is used to assess the variable age?

Two variables are included in this information. What are they and how are they measured? What is the level of measurement for each of the following variables?

Student IQ ratings. Distance students travel to class. The jersey numbers of a sorority soccer team. Number of hours students study per week. Slate is a daily magazine on the Web.

Its business activities can be described by a number of variables. The number of hits on their website on Saturday between am and am. The departments, such as food and drink, politics, foreign policy, sports, etc. The number of years Rockler Soft Close Drawer Slides Error each employee has been employed with Slate.

On the Web, go to your favorite news source and find examples of each type of variable. Write a brief memo that lists the variables and describes them in terms of qualitative or quantitative, discrete or continuous, and the measurement level. In each case, people within each organization reported financial information to investors that indicated the companies were performing much better than the actual situation. When the true financial informa- tion was reported, the companies were worth much less than advertised.

The result was many investors lost all or nearly all of the money they had invested. The real contribution of statistics to society is a moral one.

Information regarding product defects that may be harmful to people must be analyzed and reported with integrity and honesty. As you progress through this text, we will highlight ethical issues in the collection, analysis, presentation, and interpretation of statistical information.

We also hope that, as you learn about using statistics, you will become a more informed consumer of informa- tion. For example, you will question a report based on data that do not fairly represent the population, a report that does not include all relevant statistics, one that includes an incorrect choice of statistical measures, or a presentation that introduces bias in a delib- erate attempt to mislead or misrepresent.

In addition to statistics, an ability to use computer software to summarize, organize, analyze, and present the findings of statistical analysis is essential. In this text, we will be using very elementary applications of business analytics using common and available computer software. Throughout our text, we will use Microsoft Excel and, oc- casionally, Minitab. Universities and colleges usually offer access to Microsoft Excel.

Your computer already may be packaged with Microsoft Excel. If not, the Microsoft Office package with Excel often is sold at a reduced academic price through your uni- versity or college. In this text, we use Excel for the majority of the applications. If your instructor requires this package, it is avail- able at www. This add-in gives Excel the capability to produce additional statistical reports. Occasionally, we use Minitab to illustrate an application.

See www. Minitab also offers discounted academic pricing. The version of Microsoft Excel supports the analyses in our text. For each of the following, determine whether the group is a sample or a population. The participants in a study of a new cholesterol drug. The drivers who received a speeding ticket in Kansas City last month. People on welfare in Cook County Chicago , Illinois.

The 30 stocks that make up the Dow Jones Industrial Average. If you do not have Excel and are using an Apple Mac computer with Excel, you can download the free, trial version of Stat Plus at www. It is a statistical software package that will integrate with Excel for Mac computers. The following example shows the application of Excel to perform a statistical summary.

It refers to sales information from the Applewood Auto Group, a multi-location car sales and service company. The Applewood information has sales information for vehicle sales. Each sale is described by several variables: the age of the buyer, whether the buyer is a re- peat customer, the location of the dealership for the sale, the type of vehicle sold, and the profit for the sale.

Throughout the text, we will motivate the use of computer software to summarize, describe, and present information and data.

The applications of Excel are supported by instructions so that you can learn how to apply Excel to do statistical analysis. The in- structions are presented in Appendix C of this text. Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making more effective decisions.

There are two types of statistics. Descriptive statistics are procedures used to organize and summarize data. Inferential statistics involve taking a sample from a population and making estimates.

A population is an entire set of individuals or objects of interest or the measure-. A sample is a part of the population. There are two types of quantitative variables and they are usually reported numerically. Discrete variables can assume only certain values, and there are usually gaps be-. There are four levels of measurement. With the nominal level, the data are sorted into categories with no particular order to.

The ordinal level of measurement presumes that one classification is ranked higher. The interval level of measurement has the ranking characteristic of the ordinal level of. The ratio level of measurement has all the characteristics of the interval level, plus there is a 0 point and the ratio of two values is meaningful.

Explain the difference between qualitative and quantitative variables. Give an example of qualitative and quantitative variables. Explain the difference between a sample and a population. Explain the difference between a discrete and a continuous variable.

Give an example. For the following situations, would you collect information using a sample or a popula-. Statistics is a course taught at a university. Professor Rauch has taught nearly. You would like to know the aver- age grade for the course.

As part of a research project, you need to report the average profit as a percent- age of revenue for the 1-ranked corporation in the Fortune for each of the last 10 years. You are looking forward to graduation and your first job as a salesperson for one of five large pharmaceutical corporations.

You are shopping for a new MP3 music player such as the Apple iPod. The manu- facturers advertise the number of music tracks that can be stored in the memory. Usually, the advertisers assume relatively short, popular songs to estimate the number of tracks that can be stored. You, however, like Broadway musical tunes and they are much longer. You would like to estimate how many Broadway tunes will fit on your MP3 player.

Exits along interstate highways were formerly numbered successively from the western or southern border of a state. However, the Department of Transportation has recently changed most of them to agree with the numbers on the mile markers along the highway. What level of measurement were data on the consecutive exit numbers? What level of measurement are data on the milepost numbers?

Discuss the advantages of the newer system. What is the level of measurement for each of these three variables? Assume you know the daily number of Fitbit Flex. Illustrate a second sit- uation where the number of units sold is considered a population.

Place these variables in the following classification tables. For each table, summarize your observations and evaluate if the results are generally true. For example, salary is reported as a continuous quantitative variable. It is also a continuous ratio-scaled variable.

Salary b. Gender c. Sales volume of MP3 players d. Soft drink preference e. Temperature f. SAT scores g. Student rank in class h. Rating of a finance professor i. Number of home video screens. Using data from such publications as the Statistical Abstract of the United States, Forbes, or any news source, give examples of variables measured with nominal, ordinal, interval, and ratio scales.

The Struthers Wells Corporation employs more than 10, white-collar workers in its sales offices and manufacturing facilities in the United States, Europe, and Asia. A sam- ple of U. On the basis of these findings, write a brief memo to Ms. Wanda Carter, Vice President of Human Services, regarding all white-collar workers in the firm and their willingness to relocate.

A sample of customers who recently returned items showed thought the policy was fair, 32 thought it took too long to complete the transaction, and the rest had no opin- ion. On the basis of this information, make an inference about customer reaction to the new policy.

The top six- teen manufacturers are listed here. Using computer software, compare the October sales to the October sales for each manufacturer by computing the difference. Make a list of the manufac- turers that increased sales compared to ; make a list of manufacturers that de- creased sales.

Using computer software, compare sales to sales for each manufacturer by computing the percentage change in sales. Make a list of the manufacturers in order of increasing percentage changes. Which manufacturers are in the top five in percentage change? Which manufacturers are in the bottom five in percentage change? Using computer software, first sort the data using the year-to-date sales. Then, design a bar graph to illustrate the and year-to-date sales for the top 12 manufacturers.

Also, design a bar graph to illustrate the percentage change for the top 12 manufacturers. Compare these two graphs and prepare brief written comments.

Write a brief report summarizing the amounts spent during the holidays. Be sure to in- clude the total amount spent and the percent spent by each group. The following chart depicts the earnings in billions of dollars for ExxonMobil for the pe- riod until Write a brief report discussing the earnings at ExxonMobil during.

General Motors Corp. Was one year higher than the others? Did the earnings increase, decrease, or stay the same over the period?

Microwaving Wood For Turning Yoga Handcrafted Wood Table Lamp