Chapter 1 The Where, Why, and How of Data Collection
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1 Chapter 1 The Where, Why, and How of Data Collection Business Statistics:A Decision-Making Approach7th EditionChapter 1 The Where, Why, and How of Data Collection
2 Populations and Samples A Population is the set of all items or individuals of interestExamples: All likely voters in the next electionAll parts produced todayAll sales receipts for NovemberA Sample is a subset of the populationExamples: 1000 voters selected at random for interviewA few parts selected for destructive testingEvery 100th receipt selected for audit
3 Population vs. Sample Population Sample a b c d b c ef gh i jk l m n o p q rs t u v wx y zb cg i no r uy
4 Why Sample? Less time consuming than a census Less costly to administer than a censusIt is possible to obtain statistical results of a sufficiently high precision based on samples.
6 (Probability Sampling) Statistical SamplingItems of the sample are chosen based on known or calculable probabilitiesStatistical Sampling(Probability Sampling)Simple RandomStratifiedSystematicCluster
7 Example of Random Sampling Suggest how the statistical sampling techniques can be used to gather data on employees' preferences for scheduling vacation times.Simple random sampling could be used by assigning each employee a number and then using a random number generator to select employees.Table and Excel Toolpak
8 Simple Random Sampling Every possible sample of a given size has an equal chance of being selectedSelection may be with replacement or without replacementThe sample can be obtained using a table of random numbers or computer random number generator
9 Stratified random sampling could be used to divide the employees into groups with similar characteristics that might affect preferences like marital status or age and then simple random samples can be taken from each group.
10 Stratified Random Sampling Divide population into subgroups (called strata) according to some common characteristicSelect a simple random sample from each subgroupCombine samples from subgroups into onePopulationDividedinto 4strataSample
11 Systematic random sampling could be used by selecting every kth person from a list of employees.
12 Systematic Random Sampling Decide on sample size: nDivide frame of N individuals into groups of k individuals: k=N/nRandomly select one individual from the 1st groupSelect every kth individual thereafterN = 64n = 8k = 8First Group
13 Cluster sampling could be used to look at all employees in a list of randomly selected departments.
14 Cluster SamplingDivide population into several “clusters,” each representative of the populationSelect a simple random sample of clustersAll items in the selected clusters can be used, or items can be chosen from a cluster using another probability sampling techniquePopulation divided into 16 clusters.Randomly selected clusters for sample
15 Exercise1 – 41 from the handout1 – 46 from the handoutUse ToolPak
16 Tools of Business Statistics Descriptive statisticssummarize the population data by describing what was observed in the sample numerically or graphicallyInferential statisticsDrawing conclusions and/or making decisions concerning a population based only on sample data
17 Descriptive Statistics Collect datae.g., Survey, Observation,ExperimentsPresent datae.g., Charts and graphsCharacterize datae.g., Sample mean =
18 Inferential Statistics Making statements about a population by examining sample resultsSample statistics Population parameters(known) Inference (unknown, but canbe estimated fromsample evidence)
19 Inferential Statistics Drawing conclusions and/or making decisions concerning a population based on sample results.Estimatione.g., Estimate the population mean weight using the sample mean weightHypothesis Testinge.g., Use sample evidence to test the claim that the population mean weight is 120 pounds
20 Tools for Collecting Data Data Collection MethodsExperimentsWritten questionnairesTelephone surveysDirect observation and personal interview
21 Survey Design Steps Define the issue Define the population of interest what are the purpose and objectives of the survey?Define the population of interestDevelop survey questionsmake questions clear and unambiguoususe universally-accepted definitionslimit the number of questions
22 Survey Design Steps Pre-test the survey (continued)Pre-test the surveypilot test with a small group of participantsassess clarity and lengthDetermine the sample size and sampling methodSelect sample and administer the survey
23 Types of Questions Closed-end Questions Select from a short list of defined choicesExample: Major: __business __liberal arts__science __otherOpen-end QuestionsRespondents are free to respond with any value, words, or statementExample: What did you like best about this course?Demographic QuestionsQuestions about the respondents’ personal characteristicsExample: Gender: __Female __ Male
24 Data Types Examples: Marital Status Political Party Eye Color (Defined categories)Examples:Number of ChildrenDefects per hour(Counted items)Examples:WeightVoltage(Measured characteristics)
25 Data Types Time Series Data Cross Section Data Ordered data values observed over timeCross Section DataData values observed at a fixed point in time
26 Data Types Sales (in $1000’s) 2003 2004 2005 2006 Atlanta 435 460 475 490Boston320345375395Cleveland405390410Denver260270285280Time Series DataCross Section Data
27 Data Measurement Levels Highest LevelComplete AnalysisMeasurementsRatio/Interval DataRankingsOrdered CategoriesHigher LevelMid-level AnalysisOrdinal DataCategorical Codes ID Numbers Category NamesLowest LevelBasic AnalysisNominal Data
28 ExerciseTry with group members…1 – 661 – 671 – 68