Lessons in Business Statistics

An Overview of Statistics

IntroductionManagers make sound decisions when they use allManagers make sound decisions when they use allrelevant information in an effective and meaningfulrelevant information in an effective and meaningfulmanner. The principal purpose of statistics is tomanner. The principal purpose of statistics is toprovide decisionprovide decision--makers with a set of techniquesmakers with a set of techniquesfor collecting, analyzing, and interpreting data intofor collecting, analyzing, and interpreting data intoactionable recommendations. Statistical methodsactionable recommendations. Statistical methodsare widely used to aid decisionare widely used to aid decision--makers in allmakers in allfunctional areas of management. This chapterfunctional areas of management. This chapterprovides the basic ideas and concepts at a generalprovides the basic ideas and concepts at a generallevel.level.

1) Why Should I StudyStatistics?

Situation 1Situation 1A company has to decide whether to introduce a new productA company has to decide whether to introduce a new productinto the market or not. The company will introduce the productinto the market or not. The company will introduce the productinto the market if 30% of the target audience in the relevantinto the market if 30% of the target audience in the relevantpopulation will accept the product so that the risk of productpopulation will accept the product so that the risk of productfailure is minimized. Obviously consumer acceptance isfailure is minimized. Obviously consumer acceptance isparamount in making this decision. To know about theparamount in making this decision. To know about theconsumer acceptance in a reasonable manner, the company hasconsumer acceptance in a reasonable manner, the company hasdone a "test marketing" exercise. In the test market, 30% ofdone a "test marketing" exercise. In the test market, 30% ofthe sample target audience (based on a sample of 150the sample target audience (based on a sample of 150consumers) indicate their acceptance of the product. Does theconsumers) indicate their acceptance of the product. Does thesample result at 95% confidence level suggest that 30% of thesample result at 95% confidence level suggest that 30% of thetarget audience in the population (entire market) will accept thtarget audience in the population (entire market) will accept theeproduct?product?

1) Why Should I StudyStatistics? Continues

Situation 2Situation 2A bank which has been steadily losing customers in the lightA bank which has been steadily losing customers in the lightof intense competition wants to investigate the reasons forof intense competition wants to investigate the reasons forthe loss of customers on account of perceived service qualitythe loss of customers on account of perceived service qualityin critical dimensions like response time, reliability, courtesyin critical dimensions like response time, reliability, courtesyof the service staff, and credibility. The bank would like toof the service staff, and credibility. The bank would like toconduct a comprehensive survey to measure the perceivedconduct a comprehensive survey to measure the perceivedservice quality from the customers' angle on theseservice quality from the customers' angle on thesedimensions with that of competition. This would help thedimensions with that of competition. This would help thebank develop and implement effective strategies to woo itsbank develop and implement effective strategies to woo itspresent customers back as well as to attract new customers.present customers back as well as to attract new customers.

1) Why Should I StudyStatistics? Continues

Can you make the right decision in situation 1 andCan you make the right decision in situation 1 andsituation 2 with minimum risk without the help ofsituation 2 with minimum risk without the help ofstatistics? The answer is clearly a "No". Informationstatistics? The answer is clearly a "No". Informationbased decision making using statistical analysis isbased decision making using statistical analysis isabsolutely essential in the present environmentabsolutely essential in the present environmentcharacterized by intense competition, onslaught of newcharacterized by intense competition, onslaught of newproducts and services, globalization, and revolution ofproducts and services, globalization, and revolution ofinformation technology.information technology.

2 ) What is Statistics?

By "Statistics"By "Statistics" we mean methods speciallywe mean methods speciallyadapted to theadapted to the collectioncollection,, classificationclassification,,analysisanalysis,, andand interpretationinterpretation of data forof data formaking effective decisions in all functionalmaking effective decisions in all functionalareas of management.areas of management.

AMEX Gained by Statistical AnalysisAmerican Express Company (AMEX), the pioneer in personalAmerican Express Company (AMEX), the pioneer in personalcharge cards during the eighties used to systematically collectcharge cards during the eighties used to systematically collectcustomer feedback data from the marketplace on a continuouscustomer feedback data from the marketplace on a continuousbasis. AMEX is well known for its caring attitude towardsbasis. AMEX is well known for its caring attitude towardscustomers.customers.

The Analysis and Interpretation of the customer data revealedThe Analysis and Interpretation of the customer data revealedthat the customers wanted the new card to be processed withinthat the customers wanted the new card to be processed withinthree weeks where as AMEX was taking around 5 weeks.three weeks where as AMEX was taking around 5 weeks.AMEX decided to issue new cards within two weeks.AMEX decided to issue new cards within two weeks.Similarly another analysis revealed that the customers wantedSimilarly another analysis revealed that the customers wantedthe stolen/lost cards to be replaced within two days where asthe stolen/lost cards to be replaced within two days where asAMEX was taking two or more weeks to issue replacementAMEX was taking two or more weeks to issue replacementcards. AMEX decided to replace the lost cards within twocards. AMEX decided to replace the lost cards within twodays. As a result of these two decisions, AMEX could generatedays. As a result of these two decisions, AMEX could generate$1.4million additional profit per year.$1.4million additional profit per year.

3) Typical Application Areas

MarketingMarketing

Marketing ResearchMarketing ResearchDemand ProjectionsDemand Projections

FinanceFinance

Financial Ratio AnalysisFinancial Ratio AnalysisCash ForecastingCash Forecasting

Materials ManagementMaterials Management

Inventory ControlInventory ControlIncoming Quality AssessmentIncoming Quality Assessment

Quality ManagementQuality Management

SQC TechniquesSQC TechniquesProcess CapabilityProcess Capability

4) Types of Statistics

Descriptive StatisticsDescriptive Statistics isisconcerned with Dataconcerned with DataSummarization,Summarization,Graphs/Charts, andGraphs/Charts, andTablesTables

Inferential StatisticsInferential Statistics is ais amethod used to talk aboutmethod used to talk abouta Population Parametera Population Parameterfrom a Sample. It involvesfrom a Sample. It involvesPoint Estimation, IntervalPoint Estimation, IntervalEstimation, andEstimation, andHypothesis TestingHypothesis Testing

Descriptive StatisticsExample

05

101520253035404550

1stQtr

3rdQtr

Machine 1

Machine 2

Machine 3

Machine 4

The Quality Control Department of aThe Quality Control Department of alarge manufacturing company wouldlarge manufacturing company wouldlike to compute summary measureslike to compute summary measuressuch as the mean production per shiftsuch as the mean production per shiftfor a particular item. The departmentfor a particular item. The departmentwould also like to get a comparativewould also like to get a comparativepicture of performance of the meanpicture of performance of the meanproduction across the four machines inproduction across the four machines inthe plant by tabulation. Further thethe plant by tabulation. Further thecompany might like to graph thecompany might like to graph thecomparative performance of the fourcomparative performance of the fourmachines by a bar chart depicting themachines by a bar chart depicting themean production per shift.mean production per shift.

Inferential Statistics -ExampleSuppose you, as a marketing manager would like to identify aSuppose you, as a marketing manager would like to identify aniche market for your product. You know from your experienceniche market for your product. You know from your experiencethat an accurate assessment of the income of a typical family isthat an accurate assessment of the income of a typical family iscrucial. The average income of this type of families in thecrucial. The average income of this type of families in thepopulation is estimated by you to be Rs. 320000 based on figurespopulation is estimated by you to be Rs. 320000 based on figuresobtained from a sample. In this example, average income based onobtained from a sample. In this example, average income based onsample is asample is a Point EstimatePoint Estimate of the population. The average incomeof the population. The average incomethat falls with in a statistically formed interval of 320000 pluthat falls with in a statistically formed interval of 320000 plus ors orminus 40000 is called anminus 40000 is called an Interval EstimateInterval Estimate. Any statement such. Any statement suchas the average income in the population is more than Rs. 300000as the average income in the population is more than Rs. 300000per year is aper year is a HypothesisHypothesis. As a manager, the interval estimate may. As a manager, the interval estimate maybe much more important to you than the rest!be much more important to you than the rest!

Caution: Inferential Statistics assumes that the samplingCaution: Inferential Statistics assumes that the samplingmethodology is random (i.e. based on probability sampling)!methodology is random (i.e. based on probability sampling)!

5) Some Key Terms Used inStatistics

PopulationPopulation is the collection of allis the collection of allpossible observations of apossible observations of aspecified characteristic of interest.specified characteristic of interest.An example is all the students inAn example is all the students inthe Quantitative Methods coursethe Quantitative Methods coursein an MBA program.in an MBA program.

SampleSample is a subset of theis a subset of thepopulation. Suppose you want topopulation. Suppose you want toselect a team of 20 students fromselect a team of 20 students from200 students in an MBA program200 students in an MBA programfor participating in a managementfor participating in a managementquiz. The total students 200 is thequiz. The total students 200 is thepopulation. 20 students selectedpopulation. 20 students selectedfor the quiz is the sample.for the quiz is the sample.

ParameterParameter is the populationis the populationcharacteristic of interest. Forcharacteristic of interest. Forexample, you are interested in theexample, you are interested in theaverage income of a particular classaverage income of a particular classof people. The average income ofof people. The average income ofthis entire class of people is called athis entire class of people is called aparameter.parameter.

StatisticStatistic is based on a sample tois based on a sample tomake inferences about themake inferences about thepopulation parameter. If you look atpopulation parameter. If you look atthe previous example, the averagethe previous example, the averageincome in the population can beincome in the population can beestimated by the average incomeestimated by the average incomebased on the sample. This samplebased on the sample. This sampleaverage is called a statistic.average is called a statistic.

6) Types of Data

Qualitative DataQualitative Data are nonnumeric inare nonnumeric innature and can't be measured.nature and can't be measured.Examples are gender, religion, andExamples are gender, religion, andplace of birth.place of birth.

Quantitative DataQuantitative Data are numerical inare numerical innature and can be measured.nature and can be measured.Examples are balance in yourExamples are balance in yoursavings bank account, and numbersavings bank account, and number ofofmembers in your family.members in your family.

Quantitative data can be classifiedQuantitative data can be classifiedinto discrete type or continuousinto discrete type or continuoustypetype.. Discrete typeDiscrete type can take onlycan take onlycertain values, and there arecertain values, and there arediscontinuities between values,discontinuities between values,such as the number of rooms in asuch as the number of rooms in ahotel, which cannot be in fraction.hotel, which cannot be in fraction.Continuous typeContinuous type can take anycan take anyvalue within a specific interval,value within a specific interval,such as the production quantity of asuch as the production quantity of aparticular type of paper (measuredparticular type of paper (measuredin kilograms).in kilograms).

7) Types of Data Measurements-Picture

NominalNominal

OrdinalOrdinal

IntervalInterval

RatioRatio

Information

ContentIncreases

7) Types of Data Measurements

Nominal Data:Nominal Data: The weakest dataThe weakest datameasurement. Numbers are used tomeasurement. Numbers are used tolabel an item or characteristic.label an item or characteristic.Categorization is the main purposeCategorization is the main purposeof this measurement. Examples: Aof this measurement. Examples: Abusiness school may designatebusiness school may designatesubject specialization by numbers,subject specialization by numbers,i.e., MBA in Finance =1, MBA ini.e., MBA in Finance =1, MBA inSystems = 2. Various brands ofSystems = 2. Various brands oftoothpaste; savings bank accounttoothpaste; savings bank accountnumbers are other examples ofnumbers are other examples ofnominal data. Note that nominalnominal data. Note that nominaldata cannot be manipulated in adata cannot be manipulated in anumerical fashion.numerical fashion.

Ordinal or Rank Data:Ordinal or Rank Data: NumbersNumbersare used to rank. An example isare used to rank. An example isCustomer Preference for your brand.Customer Preference for your brand.An average preference is rated at 3,An average preference is rated at 3,a strong preference at 5. Simplea strong preference at 5. Simplearithmetic operations are notarithmetic operations are notpossible for ordinal data. Ordinalpossible for ordinal data. Ordinaldata can also be verbalized on adata can also be verbalized on acontinuum like excellent, good, faircontinuum like excellent, good, fairand poor. In ordinal data, distanceand poor. In ordinal data, distancebetween objects cannot bebetween objects cannot bemeasured.measured.

7) Types of Data MeasurementsContinues

Interval Data:Interval Data: If you have dataIf you have datawith ordinal properties and can alsowith ordinal properties and can alsomeasure the distance betweenmeasure the distance betweenobjects, you have an intervalobjects, you have an intervalmeasurement. Interval data aremeasurement. Interval data aresuperiorsuperior to ordinal data because,to ordinal data because,with them, decision makers canwith them, decision makers canmeasure the distances betweenmeasure the distances betweenobjects. For example, frozenobjects. For example, frozen--foodfooddistributors are concerned withdistributors are concerned withtemperature, which is an intervaltemperature, which is an intervalmeasurement. Interval data havemeasurement. Interval data havearbitrary zero point. Basicarbitrary zero point. Basicarithmetic operations are possiblearithmetic operations are possiblewith interval datawith interval data

Ratio DataRatio Data:: It is the highest level ofIt is the highest level ofmeasurement and allows you tomeasurement and allows you toperform all basic arithmeticperform all basic arithmeticoperations, including division andoperations, including division andmultiplication. Data measured on amultiplication. Data measured on aratio scale have a fixed zero point.ratio scale have a fixed zero point.Examples include business data,Examples include business data,such as cost, revenue, market sharesuch as cost, revenue, market shareand profit.and profit.

8) Data SourcesPrimary DataPrimary Data are collected by the organization itself for aare collected by the organization itself for aparticular purpose. The benefits of primary data are that they fparticular purpose. The benefits of primary data are that they fititthe needs exactly, are up to date, and reliable.the needs exactly, are up to date, and reliable.

Secondary DataSecondary Data are collected by other organizations or forare collected by other organizations or forother purposes. Any data, which are not collected by theother purposes. Any data, which are not collected by theorganization for the specified purpose, are secondary data.organization for the specified purpose, are secondary data.These may be published by other organizations, available fromThese may be published by other organizations, available fromresearch studies, published by the government, and so on.research studies, published by the government, and so on.Secondary data have the advantages of being much cheaper andSecondary data have the advantages of being much cheaper andfaster to collect. They also have the benefit of using sources,faster to collect. They also have the benefit of using sources,which are not generally available. Companies will, forwhich are not generally available. Companies will, forexample, respond to a survey by the Government of India, orexample, respond to a survey by the Government of India, orConfederation of Indian Industry, but they would not answerConfederation of Indian Industry, but they would not answerquestions from another companyquestions from another company..

9) A Step-By- Step Approach toStatistical Investigation