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1、Quantitative Methods For Decision Makers 3rd EditionChapter 3 PRESENTING MANAGEMENT INFORMATIONLearning ObjectivesBy the end of this chapter you should be able to:nAppreciate the potential for using different methods of data presentation in businessnUnderstand the major alternative methods of data p
2、resentationnBe able to choose between the major alternative methodsnAppreciate the limitations of data presentation methods3 PRESENTING MANAGEMENT INFORMATIONnBar chartsnPie chartsnFrequency distributionsnPercentage and cumulative frequenciesnHistogramnFrequency polygonsnOgivesnLorenz curvesnTime-se
3、ries graphsnZ chartsnScatter diagramsTables and Charts for Categorical DataAttribute DataGraphing DataPie ChartsBar ChartsBar and Pie ChartsnBar charts and Pie charts are often used for categorical datanHeight of bar or size of pie slice shows the frequency or percentage for each categoryBar chartsn
4、A bar chart is a chart with rectangular bars of lengths proportional to that value that they represent. nBar charts are used for comparing two or more values. nThe bars can be horizontally or vertically oriented.Bar Chart ExampleInvestment Amount Percentage Type (in thousands $) (%)Stocks 46.5 42.27
5、 Bonds 32.0 29.09 CD 15.5 14.09 Savings 16.0 14.55Total 110.0 100.0Current Investment Portfolio Bar ChartBar chart includes 3 types:nMultiple bar chartnSimple bar chartnComponent bar chartpriniciplesnExperimentnThe key pointnDecidenNumerical scale includes 0nLabels titles sourcesnAvoid enhancementsn
6、As simple as possiblePie chartThe pie chart takes a circle and breaks it up into slices that represent the categories. The size of each slice of the pie varies according to the percentage in each category.Pie Chart ExamplePercentages are rounded to the nearest percentCurrent Investment Portfolio Sav
7、ings 15%CD 14%Bonds 29%Stocks 42%Investment Amount Percentage Type (in thousands $) (%)Stocks 46.5 42.27 Bonds 32.0 29.09 CD 15.5 14.09 Savings 16.0 14.55Total 110.0 100.0OrganizingNumerical DataNumerical DataHistogramFrequencyPolygonOgiveFrequency DistributionspercentageCumulative frequenciesWhat i
8、s a Frequency Distribution?nA frequency distribution is a list or a tablencontaining groupings (ranges within which the data fall)nand the corresponding frequencies with which data fall within each grouping or categoryTabulating Numerical Data: Frequency DistributionsWhy Use a Frequency Distribution
9、?nIt is a way to summarize numerical datanIt condenses the raw data into a more useful form. nIt allows for a quick visual interpretation of the dataKey points forfrequency distributionnUsually at least 5 but no more than 15 groupings nIdeally, each class has the same widthnDetermine the width of ea
10、ch interval bynRound up the interval width to get desirable class boundariesnClass boundaries never overlapSteps nSort raw data in ascending ordernFind rangenSelect number of classesnCompute class interval (width)nDetermine class boundaries (limits)nCount observations & assign to classesFrequency Di
11、stribution ExampleExample: A manufacturer of insulation randomly selects 20 winter days and records the daily high temperature24, 35, 17, 21, 24, 37, 26, 46, 58, 30, 32, 13, 12, 38, 41, 43, 44, 27, 53, 27nSort raw data in ascending order: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 4
12、3, 44, 46, 53, 58nFind range: 58 - 12 = 46nSelect number of classes: 5 (usually between 5 and 15)nCompute class interval (width): 10 (46/5 then round up)nDetermine class boundaries (limits): 10, 20, 30, 40, 50, 60nCount observations & assign to classesFrequency Distribution Example(continued)Tabulat
13、ing Numerical Data: Cumulative FrequencyClass10 but less than 20 3 15 3 1520 but less than 30 6 30 9 4530 but less than 40 5 25 14 7040 but less than 50 4 20 18 9050 but less than 60 2 10 20 100Total 20 100 - -PercentageCumulative Percentage (upper limit)Data in ordered array:12, 13, 17, 21, 24, 24,
14、 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58FrequencyCumulative Frequency (upper limit)Graphing Numerical Data: The HistogramnA graph of the data in a frequency distribution is called a histogram nthe vertical axis is either frequency, relative frequency, or percentage nAdjusted frequency=Class MidpointsHistogram Example(No gaps between bars)Class10 but less than 20 15 3 20
