SOURCES OF BRAND EQUITY

<div style="text-align: justify;"> <br />What causes brand equity to exist? How do marketers create it? Customer-based brand equity occurs<br />when the consumer has a high level of awareness and familiarity with the brand and holds some strong, favorable, and unique brand associations in memory. In some cases, brand awareness alone is enough to create favorable consumer response; for example, in low-involvement decisions when  consumers are willing to base their choices on mere familiarity. In most other cases, however, the strength, favorability, and uniqueness of brand associations play a critical role in determining the  differentialresponse that makes up brand equity. If customers perceive the brand as only representative of the product or service category, then they’ll respond as if the offering were unbranded. Thus marketers must also convince consumers that there are meaningful differences among brands.Consumers must not think all brands in the category are the same. Establishing a positive brand image in  consumer memory strong, favorable, and unique brand associations goes hand-in-hand with creatingbrand awareness to build customer-based brand equity. Let’s look at both these sources of brand equity.<br /><br />Brand Awareness<br />Brand awareness consists of brand recognition and brand recall performance: • Brand recognition is consumers’ ability to confirm prior exposure to the brand when given the brand as a cue. In other words, when they go to the store, will they be able to recogniz the brand as one to which they have already been exposed?<br />• Brand recall is consumers’ ability to retrieve the brand from memory when given the product category, the needs fulfilled by the category, or a purchase or usage situation as a cue. In other words, consumers’ recall of Kellogg’s Corn Flakes will depend on their ability to retrieve the brand when they think of the cereal category or of what they should eat for breakfast or a snack, whether at the store when making a purchase or at home when deciding what to eat.<br /><br />If research reveals that many consumer decisions are made at the point of purchase, where the brand name, logo, packaging, and so on will be physically present and visible, then brand recognition will be important. If consumer decisions are mostly made in settings away from the point of purchase, on the other hand, then brand recall will be more important.For this reason, creating brand recall is critical for service and online brands: Consumers must actively seek the brand and therefore be able to retrieve it from memory when appropriate. Note, however, that even though brand recall may be less important at the point of purchase, consumers’ brand evaluations and choices will still often depend on what else they recall about the brand given that they are able to recognize it there. As is the case with most information in memory, we are generally more adept at recognizing a brand than at recalling it.<br /><br /><br />Advantages of Brand Awareness. What are the benefits of creating a high level of brand<br />awareness? There are threelearning advantages, consideration advantages, and choice advantages. </div> <div style="text-align: justify;"> <br /></div> <div style="text-align: justify;"> Learning Advantages: Brand awareness influences the formation and strength of the associations that make up the brand image. To create a brand image, marketers must first establish abrand node in memory, the nature of which affects how easily the consumer learns and stores additional brand associations. The first step in building brand equity is to register the brand in theminds of consumers. If the right brand elements are chosen, the task becomes easier.<br /><br />Consideration Advantages: Consumers must consider the brand whenever they are making a purchase for which it could be acceptable or fulfilling a need it could satisfy. Raising brand awareness increases the likelihood that the brand will be a member of the consideration set, the handful of brands that receive serious consideration for purchase.Much research has shown that consumers are rarely loyal to only one brand but instead have a set of brands they would consider buying and another possibly smaller set of brands they actually buy on a regular basis. Because consumers typically consider only a few brands for purchase, making sure that the brand is in the consideration set also makes other brands less likely to be considered or recalled<br /><br />Choice Advantages: The third advantage of creating a high level of brand awareness is that it can affect choices among brands in the consideration set, even if there areessentially no other associations to those brands.For example, consumers have been shown to adopt a decision rule in some cases to buy only more familiar, wellestablished brands. Thus, in low-involvement decision settings, a minimum level of brand awareness may be sufficient for product choice, even in the absence of a well-formed attitude<br /><br />One influential model of attitude change and persuasion, the elaboration-likelihood model, is consistent with the notion that consumers may make choices based on brand awareness considerations when they have low involvement. Low involvement results when consumers lack either purchase motivation (they don’t care about the product or service) or purchase ability (they don’t know anything else about the brands in a category).<br /><br /><br />1. Consumer purchase motivation: Although products and brands may be critically important to marketers, choosing a brand in many categories is not a life-or-death decision for most consumers. For example, despite millions of dollars spent in TV advertising over the years to persuade consumers of product differences, 40 percent of consumers in one survey believed all brands of gasoline were about the same or did not know which brand was best. A lack of perceived differences among brands in a category is likely to leave consumers unmotivated about the choice process.<br /> </div> <div style="text-align: justify;"> 2. Consumer purchase ability: Consumers in some product categories just do not have the necessary knowledge or experience to judge product quality even if they so desired. The obvious examples are products with a high degree of technical sophistication, like telecommunications  equipment with state-of-the-art features. But consumers may be unable to judge quality even in low-tech categories. Consider the college student who has not really had to cook or clean before, shopping the supermarket aisles in earnest for the first time, or a new manager forced to make an expensive capital purchase for the first time. The reality is that product quality is often highly ambiguous and difficult to judge without a great deal of prior experience and expertise. In such cases, consumers will use whatever shortcut or heuristic they can come up with to make their decisions in the best manner possible. Sometimes they simply<br />choose the brand with which they are most familiar and aware.<br /><br />Establishing Brand Awareness. How do you create brand awareness? In the abstract, creatingbrand awareness means increasing the familiarity of the brand through repeated exposure, although this is generally more effective for brand recognition than for brand recall. That is, the more a consumer “experiences” the brand by seeing it, hearing it, or thinking about it, the more likely he or she is to strongly register the brand in memory. Thus, anything that causes consumers to experience one of a brand’s element—its name symbol, logo, character, packaging, or slogan, including advertising and promotion, sponsorship and event marketing, publicity and public relations, and outdoor advertising—can increase familiarity and awareness of that brand element. And the more elements marketers can reinforce, usually the better. For instance, in addition to its name, Intel uses the “Intel Inside” logo and its distinctive symbol as well as its famous four-note jingle in TV ads to enhance awareness.<br /><br />Repetition increases recognizability, but improving brand recall also requires linkages in memory to appropriate product categories or other purchase or consumption cues. A slogan or jingle creatively pairs the brand and the appropriate cues (and, ideally, the brand positioning as well, helping build a positive brand image). Other brand elements like logos, symbols, characters, and packaging can also aid recall. The way marketers pair the brand and its product category, such as with an advertising slogan, helps determine the strength of product category links. For brands with strong category associations, like Ford cars, the distinction between brand recognition and recall may not matter much—consumers  thinking of the category are likely to think of the brand. In competitive markets or when the brand isnew to the category, it is more important to emphasize category links in the marketing program. Strong links between the brand and the category or other relevant cues may become especially important over time if the product meaning of the brand changes through brand extensions, mergers, or acquisitions.</div>

What causes brand equity to exist? How do marketers create it? Customer-based brand equity occurswhen the consumer has a high level of awareness and familiarity with the brand and holds some strong, favorable, and uniqu…

Brand Equity as a Bridge

<div style="text-align: justify;"> Brand Equity as a Bridge<br />Thus, according to the customer-based brand equity concept, consumer knowledge drives thedifferences that manifest themselves in terms of brand equity. This realization has important managerial implications. For one thing, brand equity provides marketers with a vital strategic bridge from their past to their future.<br /><br /><br />Brands as a Reflection of the Past. Marketers should consider all the dollars spent on manufacturing and marketing products each year not so much as “expenses” but as “investments” in what consumers saw, heard, learned, felt, and experienced about the brand. If not properly designed and implemented, these expenditures may not be good investments, in that they may not have created the right knowledge structures in consumers’ minds, but we should  consider them investments nonetheless. Thus, the quality of the investment in brand buildingis the most critical factor, not the quantity beyond some minimal threshold amount. In fact, it is possible to “overspend” on brand building if money is not being spent wisely. Conversely, as we’ll see throughout the book, some brands are considerably outspent but amass a great  deal of brand equity through marketing activities that create valuable, enduring memory traces in the minds of consumers, as has been the case with Snickers.<br /><br />Brands as a Direction for the Future. The brand knowledge that marketers create over time dictates appropriate and inappropriate future directions for the brand. Consumers will decide, based on their brand knowledge, where they think the brand should go and grant permission (or not) to any marketing action or program. Thus, at the end of the day, the true value and future prospects of a brand rest with consumers and their knowledge about the brand. No matter how we define brand equity, though, its value to marketers as a concept ultimately depends on how they use it. Brand equity can offer focus and guidance, providing a means to interpret past marketing performance and design future marketing programs. Everything the firm does can help enhance or detract from brand equity. Those marketers who build strong brands have embraced the concept and use it to its fullest as a means of clarifying, communicating, and implementing their marketing actions. </div>

Brand Equity as a BridgeThus, according to the customer-based brand equity concept, consumer knowledge drives thedifferences that manifest themselves in terms of brand equity. This realization has important managerial i…

Defining Customer-Based Brand Equity

<div style="text-align: justify;"> <br />Two questions often arise in brand marketing: What makes a brand strong? and How do you build a strong brand? To help answer both, we introduce the concept of customer-based brand equity (CBBE). Although a number of useful perspectives concerning brand equity have been put forth, the CBBE concept provides a unique point of view on what brand equity is and how itshould best be built, measured, and managed.<br /><br />Defining Customer-Based Brand Equity<br />The CBBE concept approaches brand equity from the perspective of the consumer whether the consumer is an individual or an organization or an existing or prospective customer. Understanding the needs and wants of consumers and organizations and devising products and programs to satisfy them are at the heart of successful marketing. In particular, marketers face two fundamentally important questions: What do different brands mean to  consumers? and How does the brand knowledge of consumers affect their response to marketing activity?<br /> </div> <div style="text-align: justify;"> The basic premise of the CBBE concept is that the power of a brand lies in what customers have learned, felt, seen, and heard about the brand as a result of their experiences over time. In other words, the power of a brand lies in what resides in the minds and hearts of customers. The challenge for marketers in building a strong brand is ensuring that customers have the right type of experiences with products and services and their accompanying marketing programs so that the desired thoughts, feelings, images, beliefs, perceptions, opinions, and experiences become linked to the brand.<br /><br />We formally define customer-based brand equity as the differential effect that brand knowledge has on consumer response to the marketing of that brand. A brand has positive customer-based brand equity when consumers react more favorably to a product and the way it is marketed when the brand is identified than when it is not (say, when the product is attributed to a fictitious name or is unnamed). Thus, customers might be more accepting of a new brand extension for a brand with positive customer-based brand equity, less sensitive to price increases and withdrawal of advertising support, or more willing to seek the brand in a new distribution channel. On the other hand, a brand has negative customer-based brand equity if consumers react less favorably to marketing activity for the brand compared with an unnamed or fictitiously named version of the product.<br /><br />Let’s look at the three key ingredients to this definition: (1) “differential effect,” (2) “brand knowledge,” and (3) “consumer response to marketing.” First, brand equity arises from differences in consumer response. If no differences occur, then the brand-nam product can essentially be classified as a commodity or a generic version of the product. Competition, most likely, would then just be based on price. Second, these differences in response are a result of consumers’ knowledge about the brand, that is, what they have learned, felt, seen, and heard about the brand as a result of their experiences over time. Thus, although strongly influenced by the marketing activity of the firm, brand equity ultimately  depends on what resides in the minds and hearts of consumers. Third, customers’differential responses, which make up brand equity, are reflected in perceptions, preferences, and behavior related to all aspects of brand marketing, for example, including choic of a brand, recall of copy points from an ad, response to a sales promotion, and evaluations of a proposed brand extension.<br /><br />The simplest way to illustrate what we mean by customer-based brand equity is to consider one of the typical results of product sampling or comparison tests. In blind taste tests, two groups of consumers sample a product: one group knows which brand it is, the other doesn’t.  Invariably, the two groups have different opinions despite consuming the same product. These branding effects occur in the marketplace too. For example, at one time, Hitachi and General Electric (GE) jointly owned a factory in England that made identical televisions for the two companies. The only difference was the brand name on the television. Nevertheles  itachi televisions sold for a $75 premium over the GE televisions. Moreover, Hitachi sold as many sets as GE despite the higher price.</div> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhcIbZWUiKmWcxwGjdOZI12H7D4haeqGWtnsH1WzjrhvHxaRCLIdTQIg07hx_Ba0LejjRMUgAf6aohNAWDtF52qvzWFXKnWUivRIwaUmHWLUkDBxFDaD8eRnpBdAyd59TvBXeIE1ZwM4BjC/s1600/hi.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="343" data-original-width="500" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhcIbZWUiKmWcxwGjdOZI12H7D4haeqGWtnsH1WzjrhvHxaRCLIdTQIg07hx_Ba0LejjRMUgAf6aohNAWDtF52qvzWFXKnWUivRIwaUmHWLUkDBxFDaD8eRnpBdAyd59TvBXeIE1ZwM4BjC/s1600/hi.png" /></a></div> <div style="text-align: justify;"> When consumers report different opinions about branded and unbranded versions of identical products which almost invariably happens it must be the case that knowledge about the brand, created by whatever means (past experiences, marketing activity for the brand, or word of mouth), has somehow changed customers’ product perceptions. This result has occurred with virtually every type of product conclusive evidence that consumers’ perceptions of product performance are highly dependent on their impressions of the brand that goes along  with it. In other words, clothes may seem to fit better, a car may seem to drive more smoothly, and the wait in a bank line may seem shorter, depending on the particular brand involved.</div>

Two questions often arise in brand marketing: What makes a brand strong? and How do you build a strong brand? To help answer both, we introduce the concept of customer-based brand equity (CBBE). Although a number of use…

Levels of measurement

LEVEL OF MEASUREMENT<br />Statisticians sometimes refer to four levels of measurement for data: nominal, ordinal, interval, and ratio. This typology was proposed over 60 years ago by psychologist S. S. Stevens. The allowable statistical tests depend on the measurement level. The criteria are summarized in Figure 2.3.<br /><br />Nominal Measurement<br />Nominal measurement is the weakest level of measurement and the easiest to recognize. Nominal data (from Latin nomen, meaning “name”) merely identify a category. “ Nominal” data are the same as “qualitative,” “categorical,” or “classifi cation” data. To be sure that the categories are collectively exhaustive, it is common to use Other as the last item on the list.<br />For example, the following survey questions yield nominal data:<br />Did you fi le an insurance claim last month?<br />1. Yes 2. No<br />Which cell phone service provider do you use?<br />1. AT&T 2. Sprint-Nextel 3. T-Mobile 4. Verizon 5. Other<br /><br /> We usually code nominal data numerically. However, the codes are arbitrary placeholders with no numerical meaning, so it is improper to perform mathematical analysis on them. <br /> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiql4H5FY6uKhK-WSXqLRwZX6YtE2Qxq-japO8KQXWMkgsLgo_0FWzG3QnihWHWcEw1ibDW3U1jnha4wETl-py8Gz9MRo2SC28vBUNf2c1S8cY4S4Xp2RpUgkGLDszV-kf19PqqQUQ9fcxl/s1600/mm.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="341" data-original-width="500" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiql4H5FY6uKhK-WSXqLRwZX6YtE2Qxq-japO8KQXWMkgsLgo_0FWzG3QnihWHWcEw1ibDW3U1jnha4wETl-py8Gz9MRo2SC28vBUNf2c1S8cY4S4Xp2RpUgkGLDszV-kf19PqqQUQ9fcxl/s1600/mm.png" /></a></div> <br />This may seem obvious, yet people have been known to do it. Once the data are in the computer, it’s easy to forget that the “numbers” are only categories. With nominal data, the only permissible mathematical operations are counting (e.g., frequencies) and a few simple statistics such as the mode.<br /><br />Ordinal Measurement<br />Ordinal data codes connote a ranking of data values. For example:<br />What size automobile do you usually drive?<br />1. Full-size 2. Compact 3. Subcompact<br /><br /> How often do you use Microsoft Access?<br />1. Frequently 2. Sometimes 3. Rarely 4. Never<br /><br />Thus, a 2 (Compact) implies a larger car than a 3 (Subcompact). Like nominal data, these ordinal numerical codes lack the properties that are required to compute many statistics, such as the average. Specifi cally, there is no clear meaning to the distance between 1 and 2, or between 2 and 3, or between 3 and 4 (what would be the distance between “Rarely” and  “Never”?). Other examples of ordinal scales can be found in a recruiter’s rating of job  candidates(outstanding, good, adequate, weak, unsatisfactory), S&P credit ratings (AAA, AA1, AA, AA2, A1, A, A2, B1, B, B2, etc.) or job titles (president, group vice president, plant manager, department head, clerk). Ordinal data can be treated as nominal, but not vice versa. Ordinal data are especially common in social sciences, marketing, and human resources research. There are many useful statistical tests for ordinal data.<br /><br />Ratio Measurement<br />Ratio measurement is the strongest level of measurement. Ratio data have all the properties of the other three data types, but in addition possess a meaningful zero that represents the absence of the quantity being measured. Because of the zero point, ratios of data values are meaningful (e.g., $20 million in profi t is twice as much as $10 million). Balance sheet data, income statement data, fi nancial ratios, physical counts, scientifi c measurements, and most engineering measurements are ratio data because zero has meaning (e.g., a company with zero sales sold nothing). Having a zero point does not restrict us to positive data. For example, profi t is a ratio variable (e.g., $4 million is twice $2 million), yet fi rms can have negative profi t (i.e., a loss).<br /><br />Zero does not have to be observable in the data. Newborn babies, for example, cannot have zero weight, yet baby weight clearly is ratio data (i.e., an 8-pound baby is 33 percent heavier than a 6-pound baby). What matters is that the zero is an absolute reference point. The Kelvin temperature scale is a ratio measurement because its absolute zero represents the absence of molecular vibration, while zero on the Celsius scale is merely a convenience (note that 30°C is not “twice as much temperature” as 15°C).<br /><br />Lack of a true zero is often the quickest test to defrock variables masquerading as ratio data. For example, a Likert scale (12, 11, 0, 21, 22) is not ratio data despite the presence of zero because the zero (neutral) point does not connote the absence of anything. As an acid test, askyourself whether 2 (strongly agree) is twice as much “agreement” as 1 (slightly agree). Some classifi cations are debatable. For example, college GPA has a zero, but does it represent the absence of learning? Does 4.00 represent “twice as much” learning as 2.00? Is there an underlying reality ranging from 0 to 4 that we are measuring? Most people seem to think so, although the conservative procedure would be to limit ourselves to statistical tests that assume only ordinal data. Although beginning statistics textbooks usually emphasize interval or ratio data, there are  textbooks that emphasize other kinds of data, notably in behavioral research (e.g., p sychology, sociology, marketing, human resources).<br /><br />We can recode ratio measurements downward into ordinal or nominal measurements (but not conversely). For example, doctors may classify systolic blood pressure as “normal” (under 130), “elevated” (130 to 140), or “high” (140 or over). The recoded data are ordinal, since the ranking is preserved. Intervals may be unequal. For example, U.S. air traffi c controllers classify planes as “small” (under 41,000 pounds), “large” (41,001 to 254,999 pounds), and “heavy” (255,000 pounds or more). Such recoding is done to simplify the data when the exact data magnitude is of little interest; however, we discard information if we map stronger measurements into weaker ones.

LEVEL OF MEASUREMENTStatisticians sometimes refer to four levels of measurement for data: nominal, ordinal, interval, and ratio. This typology was proposed over 60 years ago by psychologist S. S. Stevens. The allowable s…

Variables and data

<div style="text-align: justify;"> VARIABLES AND DATA<br />In scientifi c research, data arise from experiments whose results are recorded systematically. In business, data usually arise from accounting transactions or management processes (e.g., inventory, sales, payroll). Much of the data that statisticians analyze were recorded withoutexplicit consideration of their statistical uses, yet important decisions may depend on the data. How many pints of type A blood will be required at Mt. Sinai Hospital next Thursday? How many dollars must State Farm keep in its cash account to cover automotive accident claim next November? How many yellow three-quarter-sleeve women’s sweaters will Lands’ End sell this month? To answer such questions, we usually look at historical data.<br /><br />Data Terminology<br />An observation is a single member of a collection of items that we want to study, such as a person, fi rm, or region. An example of an observation is an employee or an invoice mailed last month. A variable is a characteristic of the subject or individual, such as an employee’s  income or an invoice amount. The data set consists of all the values of all of the variablesfor all of the observations we have chosen to observe. In this book, we will use data as a plural, and data set to refer to a collection of observations taken as a whole. Data usually are entered into a spreadsheet or database as an n 3 m matrix. Specifi cally, each column is  variable (m columns) and each row is an observation (n rows). Table 2.1 shows a small data set with eight observations (8 rows) and fi ve variables (5 columns). A data set may consist of many variables. The questions that can be explored and the analytical techniques that can be used will depend upon the data type and the number of variables. This textbook starts with univariate data sets (one variable), then moves to bivariate data sets (two variables) and multivariate data sets (more than two variables), as illustrated in Table 2.2.</div> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiUViJuzOtGjz4a8KcGUWdBZZFVNMCZh_qAzRmCbr_gnK3wKKWlavUkyQWo0S-a76AoP0r_jtMsflslOhcQYAqLNTUAaXW5vWJsuIQA3leipowZOUTb2VKY8y5HTrVKjbLSWs90vioaQg1r/s1600/22.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="218" data-original-width="500" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiUViJuzOtGjz4a8KcGUWdBZZFVNMCZh_qAzRmCbr_gnK3wKKWlavUkyQWo0S-a76AoP0r_jtMsflslOhcQYAqLNTUAaXW5vWJsuIQA3leipowZOUTb2VKY8y5HTrVKjbLSWs90vioaQg1r/s1600/22.png" /></a></div> <div style="text-align: justify;"> <b>Categorical and Numerical Data</b><br />A data set may contain a mixture of data types. Two broad categories are categorical data and numerical data, as shown in Figure 2.1.<br /><br />Categorical Data Categorical data (also called qualitative data) have values that are described by words rather than numbers. For example, structural lumber can be classifi ed by the lumber type (e.g., fi r, hemlock, pine), automobile styles can be classifi ed by size (e.g., full, midsize, compact, subcompact), and movies can be categorized using common movie classifications (e.g., action and adventure, children and family, classics, comedy, documentary). Because categorical variables have nonnumerical values, it might seem that categorical data would be of limited statistical use. In fact, there are many statistical methods that can handle categorical data.</div> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhTROGpbaaXAVsCO8JiFNA-HOrKT936vWAtPLrPxk3Wrpjej1lZXzhDxO6yNaqBQ3wLFIn5r-Seke8c0YNgt3H7HJenokPaUNAGYxgYXCFz9ZAIVx_qnNogarSrkqE5QfLFg4PBUG8CBx1G/s1600/21.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="252" data-original-width="500" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhTROGpbaaXAVsCO8JiFNA-HOrKT936vWAtPLrPxk3Wrpjej1lZXzhDxO6yNaqBQ3wLFIn5r-Seke8c0YNgt3H7HJenokPaUNAGYxgYXCFz9ZAIVx_qnNogarSrkqE5QfLFg4PBUG8CBx1G/s1600/21.png" /></a></div> <div style="text-align: justify;"> of the categorical variable might be represented using numbers. This is called coding. For example, a database might code payment methods using numbers:<br />1 = cash 2 = check 3 = credit/debit card 4 = gift card<br /><br />Coding a category as a number does not make the data numerical and the numbers do not typically imply a rank. But on occasion a ranking does exist. For example, a database might code education degrees using numbers:<br />1 = Bachelor’s 2 = Master’s 3 =Doctorate<br /><br />Some categorical variables have only two values. We call these binary variables. Examples include employment status (e.g., employed or unemployed), mutual fund type (e.g., load or no-load), and marital status (e.g., currently married or not currently married). Binary variables  are often coded using a 1 or 0. For a binary variable, the 0-1 coding is arbitrary, so the choiceis equivalent. For example, a variable such as gender could be coded as:<br /><br />1 = female 0 = male<br />or as<br />1 = male 0 = female<br /><br />something,<br />or some kind of mathematical operation. For example, we could count the number of  auto insurance claims fi led in March (e.g., 114 claims) or sales for last quarter (e.g., $4,920),or we could measure the amount of snowfall over the last 24 hours (e.g., 3.4 inches). Most accounting data, economic indicators, and fi nancial ratios are quantitative, as are physical measurements. Numerical data can be broken down into two types. A variable with a countable numberof distinct values is discrete. Often, such data are integers. You can recognize integer data because their description begins with “number of.” For example, the number of Medicaid patients in a hospital waiting room (e.g., 2) or the number of takeoffs at Chicago O’Hare International Airport in an hour (e.g., 37). Such data are integer variables because we cannot observe a fractional number of patients or takeoffs<br /><br />A numerical variable that can have any value within an interval is continuous. This would include things like physical measurements (e.g., distance, weight, time, speed) or fi nancial variables (e.g., sales, assets, price/earnings ratios, inventory turns); for example, runner Usain Bolt’s time in the 100-meter dash (e.g., 9.58 seconds) or the weight of a package of Sun- Maid raisins (e.g., 427.31 grams). These are continuous variables because any interval such as [425, 429] grams can contain infi nitely many possible values. Sometimes we round a continuous measurement to an integer (e.g., 427 grams), but that does not make the data discrete.<br /><br />Apparent ambiguity between discrete and continuous is introduced when we round continuous data to whole numbers (e.g., your weight this morning). However, the underlying measurement scale is continuous. That is, a package of Sun-Maid raisins is l abeled 425 grams, but on an accurate scale its weight would be a noninteger (e.g., 427.31). P recision depends on the instrument we use to measure the continuous variable. We generally treat fi nancial data(dollars, euros, pesos) as continuous even though retail prices go in discrete steps of .01 (i.e., we go from $1.25 to $1.26). The FM radio spectrum is continuous, but only certain discrete values are observed (e.g., 104.3) because of Federal Communications Commission rules. Conversely, we sometimes treat discrete data as continuous when the range is very large (e.g., SAT scores) and when small differences (e.g., 604 or 605) aren’t of much importance. This topic will be discussed in later chapters. If in doubt, just think about how X was measured and whether or not its values are countable<br /></div>

VARIABLES AND DATAIn scientifi c research, data arise from experiments whose results are recorded systematically. In business, data usually arise from accounting transactions or management processes (e.g., inventory, sa…

STATISTICS IN BUSINESS

<div style="text-align: justify;"> STATISTICS IN BUSINESS<br />You’ve seen why statistics is important. Now let’s look at some of the ways statistics is used in business. Auditing A large fi rm pays over 12,000 invoices to suppliers every month. The fi rm haslearned that some invoices are being paid incorrectly, but they don’t know how widespread the problem is. The auditors lack the resources to check all the invoices, so they decide to take a sample to estimate the proportion of incorrectly paid invoices. How large should the sample be for the auditors to be confi dent that the estimate is close enough to the true proportion?<br /><br />Marketing A marketing consultant is asked to identify likely repeat customers for Amazon.com, and to suggest co-marketing opportunities based on a database containing records of 5 million Internet purchases of books, CDs, and DVDs. How can this large database be mined to reveal useful patterns that might guide the marketing strategy?<br /><br />Health Care Health care is a major business (1/6 of the U.S. GDP). Hospitals, clinics, and their suppliers can save money by fi nding better ways to manage patient appointments,  schedule procedures, or rotate their staff. For example, an outpatient cognitive retraining clinic for victims of closed-head injuries or stroke evaluates 56 incoming patients using a 42-item physical and mental assessment questionnaire. Each patient is evaluated independently by two experienced therapists. Are there statistically signifi cant differences between the two therapists’ evaluations of incoming patients’ functional status? Are some assessment questions redundant? Do the initial assessment scores accurately predict the patients’ lengths of stay in the program?<br /><br />Quality Improvement A manufacturer of rolled copper tubing for radiators wishes to improve its product quality. It initiates a triple inspection program, sets penalties for workers who produce poor-quality output, and posts a slogan calling for “zero defects.” The approach fails. Why?<br /><br />Purchasing A retailer’s shipment of 200 DVD players reveals 4 with defects. The supplier’s historical defect rate is .005. Has the defect rate really risen, or is this simply a “bad” batch?<br /><br />Medicine An experimental drug to treat asthma is given to 75 patients, of whom 24 get better. A placebo is given to a control group of 75 volunteers, of whom 12 get better. Is the new drug better than the placebo, or is the difference within the realm of chance?<br /><br />Operations Management The Home Depot carries 50,000 different products. To manage this vast inventory, it needs a weekly order forecasting system that can respond to developing patterns in consumer demand. Is there a way to predict weekly demand and place orders from suppliers for every item, without an unreasonable commitment of staff time?<br /><br />Product Warranty A major automaker wants to know the average dollar cost of engine warranty claims on a new hybrid vehicle. It has collected warranty cost data on 4,300 warrantyclaims during the fi rst six months after the engines are introduced. Using these warranty claims as an estimate of future costs, what is the margin of error associated with this estimate?</div> <div style="text-align: justify;"> <br /></div>

STATISTICS IN BUSINESSYou’ve seen why statistics is important. Now let’s look at some of the ways statistics is used in business. Auditing A large fi rm pays over 12,000 invoices to suppliers every month. The fi rm hasl…

Quality and productivity Improvement process

Foundations of Continuous Improvement<br />Continuous improvement is based on the teachings and philosophy of W. Edwards Deming. Deming is credited with helping Japanese industry recover from WWII and pursue a strategy of exporting goods of high quality at affordable prices. This combination of quality and low cost was thought impossible because people took for granted thatquality was only achieved at high cost. The foundations of Deming’s teachings consisted of three principles:<br /> <ol> <li>Customer satisfaction. Focusing on satisfying customers’ needs should be paramount in workers’ minds. This requires an attitude of putting the customer first and a belief  that this principle is the object of one’s work. </li> <li>Management by facts. To encourage scientific thinking, objective data must be collected and presented to management for decision making. This approach requires formal data gathering and statistical analysis of the data by the quality improvement teams.</li> <li>Respect for people. A companywide quality-improvement program assumes that all employees have a capacity for self-motivation and for creative thought. Employees are given support, and their ideas are solicited in an environment of mutual respect.</li> </ol> <br />Plan-Do-Check-Act (PDCA) Cycle  <br />Deming’s approach to quality recognizes that checking or inspecting for quality is too late and instead one should focus on the process. Deming’s approach, represented by a wheel, consists of four steps: plan, select and analyze the problem; do, implement the solution; check the results of the change; and act to standardize the solution and reflect on the learning. As shown in Figure 8.1 , the Deming wheel is a repetitive cycle with quality improvements resulting from continuous incremental turns of the wheel.<br /><br />Plan. Planning begins with the selection of the problem. Problems will appear as changes to important customer indicators, such as rate of defections or complaints. Narrow the project focus and describe the improvement opportunity. The current process is documented, perhaps with a flowchart, and data are collected. The possible causes are brainstormed and, using data, agreement is reached on the root cause(s). Develop an action plan that includes a workable solution, measures of success, and the implementation targets agreed upon.<br /><br />Do. Implement the solution or process change perhaps on a trial basis. Monitor the implementation plan by collecting data on performance measures and noting progress against milestones.<br /><br />Check. Review and evaluate the result of the change. Check that the solution is having the intended effect and note any unforeseen consequences.<br /><br />Act. Reflect and act on learning from the experience. If successful, the process changes are standardized and communicated to all involved workers with training in<br /> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgGFo3NGmDOlh5donT2mQg1x8GCeqfCaYAr2me3Kbgp1m-dAJAE2ulsCvG8MBOJOFNz4562yiiJABbkwx-q7e1zy-OqCuOlIoQ1MiWi7jcV4ETaGTToZNUaWrdEsjQ8KnZv1f_SN5newZtu/s1600/11.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="191" data-original-width="493" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgGFo3NGmDOlh5donT2mQg1x8GCeqfCaYAr2me3Kbgp1m-dAJAE2ulsCvG8MBOJOFNz4562yiiJABbkwx-q7e1zy-OqCuOlIoQ1MiWi7jcV4ETaGTToZNUaWrdEsjQ8KnZv1f_SN5newZtu/s1600/11.png" /></a></div> the new methods as needed. In some cases this could include external participants such as customers and suppliers. Celebrate the success and repeat the PDCA cycle on another problem.<br /> <div class="separator" style="clear: both; text-align: center;"> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhQm-DRtodVHjaolvussQ7Q5ueRM5hbvN5Hv1LQ5I6XAI6lzwDSn_nibgbNCcYfSknq95J0Njzv0RkNpHptHlb1pX01GcLC022WNClym7MKpHwE2rQ86Znu8VumUNw1fxZzdoWqN5WvADt7/s1600/12.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="555" data-original-width="500" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhQm-DRtodVHjaolvussQ7Q5ueRM5hbvN5Hv1LQ5I6XAI6lzwDSn_nibgbNCcYfSknq95J0Njzv0RkNpHptHlb1pX01GcLC022WNClym7MKpHwE2rQ86Znu8VumUNw1fxZzdoWqN5WvADt7/s1600/12.png" /></a></div> Problem Solving<br />A systematic approach to solving problems is central to a worker-empowered program of continuous improvement in quality and productivity. The principal objective of continuous improvement is eliminating the cause of problems so they do not recur. A problemsolving approach based on Deming’s PDCA cycle is described in Table 8.1 .<br /> <br />

Foundations of Continuous ImprovementContinuous improvement is based on the teachings and philosophy of W. Edwards Deming. Deming is credited with helping Japanese industry recover from WWII and pursue a strategy of expo…