Bài giảng Statistical Techniques in Business and Economics - Chapter 1 What is Statistics?

Chapter 1What is Statistics?When you have completed this chapter, you will be able to:Chapter Goals Explain what is meant by statistics.Identify the role of statistics in the development of knowledge and everyday life. Explain what is meant by descriptive statistics and inferential statistics.and...1.2.3.4.11 - 2 Distinguish between a qualitative variable and a quantitative variable.Chapter Goalsand...5.6.7.8.11 - 3 Distinguish among the nominal, ordinal, interval, and ratio levels of measurement.Collect data from published and unpublished sources.Identify abuses of statistics. Distinguish between a discrete variable and a continuous variable.Chapter Goals11 - 49. Gain an overview of the art and science of  statistics. We recommend that you read this chapter at least twice, once at the beginning and once at the end of your course!it is the art and science of collecting organizing presenting data drawing inferences from a sample of information about an entire population as well as predicting and developing policy analysisWhat is Meant by Statistics?in everyday lifeRole played by Statistics Who uses Statistics?Those using Statistical techniques include :MarketersAccountantsHospitalsInvestorsEconomistsSports peopleStatisticiansConsumersEducatorsQuality ControllersPoliticiansPhysicians Weather ForecastersWho uses Statistics?Who uses Statistics?SportsTypes of StatisticsTypes of StatisticsMethods of collecting organizing presenting and analyzing dataScience of making inferences about a population, based on sample information.DescriptiveInferentialIdentify the following C. Wine tasters sip a few drops of wine to make a decision with respect to all the wine waiting to be released for sale.A. A Gallup poll found that 83% of the people in a survey knew which country won the gold medal in Men’s Hockey in 2002. B. The accounting department of a firm will select a sample of invoices to check for accuracy of all the invoices of the company.DescriptiveInferentialWe start off with particular observations from the real world and draw conclusions about the general patterns in the real world!1. Define the experimental goal or a working hypothesis2. Design an experiment3. Collect data4. Estimate the values/relations5. Draw inferences6. Predict and prepare policy analysisChapters 8 and 12Chapters 3 and 4Chapters 5,7,8 and 9The Method of ExperimentationDefinitions & AssumptionsRules of LogicImplications or HypothesesObjective or Working-HypothesisExperimental Design & Data CollectionStatistical TechniquesInductive MethodDeductive MethodReal Real The Method of ExperimentationA StudyA study was undertaken to estimate the average height of penguins in Antarctica.Let’s review the steps they would take to prepare the estimate.the POPULATIONWhat InformationA population is a collection of all possible individuals, objects, or measurements of interestSay, 101SampleTake aWhat we now need isFromPOPULATIONwhich are deemed to be representative of thePOPULATIONTake a Measurement for each one in the sampleSample101 RecordRaw Data?What NowGoalto put the data into areadable and understandable format!Displaying Data ResultsTwo methods that can be used to ‘see’ what the data conveys are Tables and Graphs/ChartsMore on these in chapter 2Tables are an efficient method of displaying dataand depicting data accurately. e.g.101More on these in chapter 2LineScatterHistogramPieBarGraphsChartsMore on these in chapter 2Why take a sample instead of studying every member of the population? Costs of surveying the entire population may be too large or prohibitive Destruction of elements during investigation Accuracy of resultsMore in chapter 8 Why Study Statistics? Data are everywhere Statistical techniques are used to make many decision that affect our lives No matter what your future line of work, you will make decisions that involve data. An understanding of statistical methods will help you make these decisions more effectively.Types of Types of Data a characteristic of a population or samplethat is of interest to usA VariableQuantitativeQualitativeNumericalObservations Categorical ObservationsTypes of Data Variables Country of BirthU.K.GermanyTaiwanChinaIndiaJapanRussiaEye ColourBlueBrownHazelGreenRedGenderMale FemaleQualitative – or AttributeVariables Minutes to end of Class55453050Number of Children in a Family 1234 Number of Two-Door Garages in a Street 10203040...Number of Satisfied Maple Leafs Fans 0203040Quantitative – NumericVariablesQuantitativeNumericalObservations can be classified as either Discrete orContinuousDiscrete can only assume certain values and there are usually “gaps” between valuese.g. - Number of bedrooms in a house - Number of hammers sold (1,2,3,etc)VariablesCharacteristicsContinuous can assume any value within a specified range!e.g. - Pressure in a tire - Weight of a pork chop - Height of students in a classQuantitativeNumericalObservations can be classified as either Discrete orContinuousCharacteristicsVariablesSummary of Types of VariablesDataQualitative Categorical ObservationsQuantitativeNumericalObservationsDiscreteContinuous(number of children)(time used for an exam)Collecting DataStatistical AbstractsPublished DataSources of Statistical InformationWeatherSportsInternetSources of Statistical Informationwww.strategis.gc.cawww.bankofcanada.caGovernment of Canada & Provinceswww.gc.cawww.theweathernetwork.comwww.mcgrawhill.ca/college/lindInternationalSources of Statistical Informationwww.census.govwww.un.orgwww.bls.gov/www.oecd.orgIMFwww.imf.orgwww.worldbank.org/Organization for Economic Co-operation and DevelopmentHow to collect dataCommissioned surveys:Sources of Statistical InformationTo develop information for the survey that they are doing, pollsters often contact the selected ‘sample population’. For ExampleAt home, over the telephone, by mail, by email, in the street, and at shopping malls! Levels of NominalOrdinalInterval Ratio Levels of Levels of NominalData can only be classified into categories or counted and cannot be arranged in any particular order ExampleM & MsClassification:Category:CandyBy Colour only(No natural order) Levels of NominalExampleM & MsExhaustive:Mutually Exclusive:where an individual, object, or measurement is included in ONLY ONE CATEGORYwhere each individual, object, or measurement MUST APPEAR in one of the categoriesOrdinal Levels of involves data arranged in some order,but the differences between data values cannot be determined or are meaningless!ExampleDuring a taste test of 4 soft drinks:Mello Yello was ranked number... 1. Sprite number. 2. Seven Up number....... 3.Orange Crush number ..4.Interval Levels of similar to the Ordinal Level, with the additional property that meaningful amounts of differences between data values can be determined. There is no natural zero pointExampleTemperature on the Celsius scale. Ratio Levels of the Interval Level with an inherent zero starting point. Differences and ratios are meaningful for this level of measurement.ExamplesMonthly income of surgeonsDistance travelled by manufacturer’s representatives per monthAbuses of StatisticsDamned LiesStatistics!LiesBenjamin Disraeli said“There are three kinds of lies&Figures don’t lie.Liars figure!CautionAs you begin to study statistical methods, you are cautioned to take what you see published as “statistical facts” with a healthy grain of skepticism! an average may not be representative of all the data graphs can also be misleading be sure to study the sampling methodsFor ExampleCautionCautionReview the following three slides and notice the effect that the different scales have on your interpretation of the pattern between Crime and Unemployment Rates.UnemploymentCrime Rate&1986 - 19990 1 2 3 4 5 6 7 8 9 10 11 123200300028002600240022002000Crime Rate(in thousands)Unemployment Rate (%)Chart 1-11AUnemploymentCrime Rate&1986 -19997 8 9 10 11 1230002500200015001000 500 0Crime Rate(in thousands)Unemployment Rate (%)Chart 1-11B500010001500200025003000UnemploymentCrime Rate&1986 -1999Chart 1-11C3200300028002600240022002000Crime Rate(in thousands)Unemployment Rate (%)7 8 9 10 11 12Test your learning www.mcgrawhill.ca/college/lindClick onOnline Learning Centrefor quizzesextra contentdata setssearchable glossaryaccess to Statistics Canada’s E-Stat dataand much more!This completes Chapter 1.