商务统计导论全套课件440p

1、商务统计导论全套课件440p商务统计导论全套课件440pCHAPTER 1:A Preview of Business Statisticsto accompanyIntroduction to Business Statisticsfourth edition, by Ronald M. WeiersPresentation by Priscilla Chaffe-Stengel Donald N. Stengel 2002 The Wadsworth GroupCHAPTER 1:A Preview of BusineChapter 1 - Key TermsCollection, sum

2、marization, analysis, and reporting of numerical findingsStatistics - Two UsagesA. The study of statisticsB. Statistics as reported sample measures1. Descriptive 2. Inferential 2002 The Wadsworth GroupChapter 1 - Key TermsCollectioChapter 1 - Key TermsInferential StatisticsChapter 1 - Key TermsInfer

3、enTypes of VariablesQualitative VariablesAttributes, categoriesExamples: male/female, registered to vote/not, ethnicity, eye color.Quantitative VariablesDiscrete - usually take on integer values but can take on fractions when variable allows - counts, how manyContinuous - can take on any value at an

4、y point along an interval - measurements, how much 2002 The Wadsworth GroupTypes of VariablesQualitative Example: Types of VariablesProblem 1.16For each of the following, indicate whether the appropriate variable would be qualitative or quantitative. If the variable is quantitative, indicate whether

5、 it would be discrete or continuous. 2002 The Wadsworth GroupExample: Types of VariablesPrProblem 1.16a) Whether you own an RCA Colortrak television setb) Your status as a full-time or a part-time studentc) Number of people who attended your schools graduation last yearQualitative Variabletwo levels

6、: yes/nono measurementQualitative Variabletwo levels: full/partno measurementQuantitative, Discrete Variablea countable numberonly whole numbers 2002 The Wadsworth GroupProblem 1.16a) Whether you ownProblem 1.16, continuedd) The price of your most recent haircute) Sams travel time from his dorm to t

7、he Student UnionQuantitative, Discrete Variablea countable numberonly whole numbersQuantitative, Continuous Variableany numbertime is measuredcan take on any value greater than zero 2002 The Wadsworth GroupProblem 1.16, continuedd) The Problem 1.16, continuedf) The number of students on campus who b

8、elong to a social fraternity or sororityQuantitative, Discrete Variablea countable numberonly whole numbers 2002 The Wadsworth GroupProblem 1.16, continuedf) The Scales of MeasurementNominal Scale - Labels represent various levels of a categorical variable.Ordinal Scale - Labels represent an order t

9、hat indicates either preference or ranking.Interval Scale - Numerical labels indicate order and distance between elements. There is no absolute zero and multiples of measures are not meaningful.Ratio Scale - Numerical labels indicate order and distance between elements. There is an absolute zero and

10、 multiples of measures are meaningful. 2002 The Wadsworth GroupScales of MeasurementNominal SExample: Scales of MeasurementProblem 1.20Bill scored 1200 on the Scholastic Aptitude Test and entered college as a physics major. As a freshman, he changed to business because he thought it was more interes

11、ting. Because he made the deans list last semester, his parents gave him $30 to buy a new Casio calculator. Identify at least one piece of information in the: 2002 The Wadsworth GroupExample: Scales of MeasurementProblem 1.20, continueda) nominal scale of measurement.1. Bill is going to college.2. B

12、ill will buy a Casio calculator.3. Bill was a physics major.4. Bill is a business major.5. Bill was on the deans list. 2002 The Wadsworth GroupProblem 1.20, continueda) nomiProblem 1.20, continuedb) ordinal scale of measurementc) interval scale of measurementd) ratio scale of measurementBill is a fr

13、eshman.Bill earned a 1200 on the SAT.Bills parents gave him $30. 2002 The Wadsworth GroupProblem 1.20, continuedb) ordiCHAPTER 2:Visual Description of Datato accompanyIntroduction to Business Statisticsfourth edition, by Ronald M. WeiersPresentation by Priscilla Chaffe-Stengel Donald N. Stengel 2002

14、 The Wadsworth GroupCHAPTER 2:Visual Description Chapter 2 - Learning ObjectivesConvert raw data into a data array.Construct:a frequency distribution.a relative frequency distribution.a cumulative relative frequency distribution.Construct a stem-and-leaf diagram.Visually represent data by using grap

15、hs and charts. 2002 The Wadsworth GroupChapter 2 - Learning ObjectiveChapter 2 - Key TermsData arrayAn orderly presentation of data in either ascending or descending numerical order.Frequency DistributionA table that represents the data in classes and that shows the number of observations in each cl

16、ass. 2002 The Wadsworth GroupChapter 2 - Key TermsData arraChapter 2 - Key TermsFrequency DistributionClass - The categoryFrequency - Number in each classClass limits - Boundaries for each classClass interval - Width of each classClass mark - Midpoint of each class 2002 The Wadsworth GroupChapter 2

17、- Key TermsFrequencySturges ruleHow to set the approximate number of classes to begin constructing a frequency distribution.where k = approximate number of classes to use andn = the number of observations in the data set . 2002 The Wadsworth GroupSturges ruleHow to set the apHow to Construct aFreque

18、ncy Distribution1. Number of classes Choose an approximate number of classes for your data. Sturges rule can help.2. Estimate the class interval Divide the approximate number of classes (from Step 1) into the range of your data to find the approximate class interval, where the range is defined as th

19、e largest data value minus the smallest data value.3. Determine the class intervalRound the estimate (from Step 2) to a convenient value. 2002 The Wadsworth GroupHow to Construct aFrequency How to Construct aFrequency Distribution, cont.4. Lower Class LimitDetermine the lower class limit for the fir

20、st class by selecting a convenient number that is smaller than the lowest data value. 5. Class LimitsDetermine the other class limits by repeatedly adding the class width (from Step 2) to the prior class limit, starting with the lower class limit (from Step 3).6. Define the classesUse the sequence o

21、f class limits to define the classes. 2002 The Wadsworth GroupHow to Construct aFrequency DConverting to a Relative Frequency Distribution1. Retain the same classes defined in the frequency distribution.2. Sum the total number of observations across all classes of the frequency distribution.3. Divid

22、e the frequency for each class by the total number of observations, forming the percentage of data values in each class. 2002 The Wadsworth GroupConverting to a Relative FrequForming a Cumulative Relative Frequency Distribution1. List the number of observations in the lowest class.2. Add the frequen

23、cy of the lowest class to the frequency of the second class. Record that cumulative sum for the second class.3. Continue to add the prior cumulative sum to the frequency for that class, so that the cumulative sum for the final class is the total number of observations in the data set. 2002 The Wadsw

24、orth GroupForming a Cumulative Relative Forming a Cumulative Relative Frequency Distribution, cont.4. Divide the accumulated frequencies for each class by the total number of observations - giving you the percent of all observations that occurred up to an including that class.An Alternative: Accrue

25、the relative frequencies for each class instead of the raw frequencies. Then you dont have to divide by the total to get percentages. 2002 The Wadsworth GroupForming a Cumulative Relative Example: Problem 2.53The average daily cost to community hospitals for patient stays during 1993 for each of the

26、 50 U.S. states was given in the next table.a) Arrange these into a data array.b) Construct a stem-and-leaf display.*) Approximately how many classes would be appropriate for these data? *not in textbookc & d) Construct a frequency distribution. State interval width and class mark.e) Construct a his

27、togram, a relative frequency distribution, and a cumulative relative frequency distribution. 2002 The Wadsworth GroupExample: Problem 2.53The averaProblem 2.53 - The DataAL $775HI 823MA 1,036NM 1,046SD 506AK 1,136ID 659MI 902NY 784TN 859AZ 1,091IL 917MN 652NC 763TX 1,010AR 678IN 898MS 555ND 507UT 1,

28、081CA 1,221IA 612MO 863OH 940VT 676CO 961KS 666MT 482OK 797VA 830CT 1,058KY 703NE 626OR 1,052WA 1,143DE 1,024LA 875NV 900PA 861WV 701FL 960ME 738NH 976RI 885WI 744GA 775MD 889NJ 829SC 838WY 537 2002 The Wadsworth GroupProblem 2.53 - The DataAL Problem 2.53 - (a) Data ArrayCA 1,221TX 1,010RI 885NY 78

29、4KS 666WA 1,143NH 976LA 875AL 775ID 659AK 1,136CO 961MO 863GA 775MN 652AZ 1,091FL 960PA 861NC 763NE 626UT 1,081CH 940TN 859WI 744IA 612CT 1,058IL 917SC 838ME 738MS 555OR 1,052MI 902VA 830KY 703WY 537NM 1,046NV 900NJ 829WV 701ND 507MA 1,036IN 898HI 823AR 678SD 506DE 1,024MD 889OK 797VT 676MT 482 2002

30、 The Wadsworth GroupProblem 2.53 - (a) Data ArrayProblem 2.53 - (b)The Stem-and-Leaf DisplayStem-and-Leaf DisplayN = 50Leaf Unit: 100 11221 21143, 36 81091, 81, 58, 52, 46, 36, 24, 10 7 976, 61, 60, 40, 17, 02, 00(11) 898, 89, 85, 75, 63, 61, 59, 38, 30, 29, 23 9 797, 84, 75, 75, 63, 44, 38, 03, 01

31、7 678, 76, 66, 59, 52, 26, 12 4 555, 37, 07, 06 1 482Range: $482 - $1,221 2002 The Wadsworth GroupProblem 2.53 - (b)The Stem-anProblem 2.53 - ContinuedTo approximate the number of classes we should use in creating the frequency distribution, use Sturges Rule, n = 50: Sturges rule suggests we use app

32、roximately 7 classes. 2002 The Wadsworth GroupProblem 2.53 - ContinuedTo appConstructing the Frequency DistributionStep 1. Number of classesSturges Rule: approximately 7 classes.The range is: $1,221 $482 = $739$739/7 $106 and $739/8 $92 Steps 2 & 3. The Class Interval So, if we use 8 classes, we can

33、 make each class $100 wide. 2002 The Wadsworth GroupConstructing the Frequency Constructing the Frequency DistributionStep 4. The Lower Class LimitIf we start at $450, we can cover the range in 8 classes, each class $100 in width.The first class : $450 up to $550Steps 5 & 6. Setting Class Limits$450

34、 up to $550$850 up to $950$550 up to $650$950 up to $1,050$650 up to $750 $1,050 up to $1,150$750 up to $850 $1,150 up to $1,250 2002 The Wadsworth GroupConstructing the Frequency Problem 2.53 - (c) & (d)Average daily cost NumberMark $450 under $5504$500 $550 under $650 3$600 $650 under $750 9$700 $

35、750 under $850 9$800 $850 under $950 11$900 $950 under $1,050 7 $1,000$1,050 under $1,150 6 $1,100$1,150 under $1,250 1 $1,200Interval width: $100 2002 The Wadsworth GroupProblem 2.53 - (c) & (d)AveragProblem 2.53 - (e) The Histogram 2002 The Wadsworth GroupProblem 2.53 - (e) The HistogrProblem 2.53

36、 - The Relative Frequency DistributionAverage daily cost Number Rel. Freq. $450 under $550 44/50 = .08 $550 under $650 33/50 = .06 $650 under $750 99/50 = .18 $750 under $850 99/50 = .18 $850 under $950 11 11/50 = .22 $950 under $1,050 77/50 = .14$1,050 under $1,150 66/50 = .12$1,150 under $1,250 11

37、/50 = .02 2002 The Wadsworth GroupProblem 2.53 - The Relative FrProblem 2.53 - (e) The Percentage Polygon 2002 The Wadsworth GroupProblem 2.53 - (e) The PercentProblem 2.53 - The Cumulative Frequency DistributionAverage daily cost Number Cum. Freq. $450 under $5504 4 $550 under $650 3 7 $650 under $

38、750 916 $750 under $850 925 $850 under $950 1136 $950 under $1,050 743$1,050 under $1,150 649$1,150 under $1,250 150 2002 The Wadsworth GroupProblem 2.53 - The Cumulative Problem 2.53 - The Cumulative Relative Frequency DistributionAverage daily cost Cum.Freq. Cum.Rel.Freq. $450 under $550 44/50 = .

39、02 $550 under $650 77/50 = .14 $650 under $750 16 16/50 = .32 $750 under $850 25 25/50 = .50 $850 under $95036 36/50 = .72 $950 under $1,050 43 43/50 = .86$1,050 under $1,150 49 49/50 = .98$1,150 under $1,250 50 50/50 = 1.00 2002 The Wadsworth GroupProblem 2.53 - The Cumulative Problem 2.53 - (e) Th

40、e Percentage Ogive (Less Than) 2002 The Wadsworth GroupProblem 2.53 - (e) The PercentThe Scatter DiagramA scatter diagram is a two-dimensional plot of data representing values of two quantitative variables.x, the independent variable, on the horizontal axisy, the dependent variable, on the vertical

41、axisFour ways in which two variables can be related:1. Direct2. Inverse3. Curvilinear4. No relationship 2002 The Wadsworth GroupThe Scatter DiagramA scatter dAn Example: Problem 2.38For 6 local offices of a large tax preparation firm, the following data describe x = service revenues and y = expenses

42、 for supplies, freight, postage, etc.Draw a scatter diagram representing the data. Does there appear to be any relationship between the variables? If so, is the relationship direct or inverse? 2002 The Wadsworth GroupAn Example: Problem 2.38For 6 Problem 2.38, continued 2002 The Wadsworth GroupThere

43、 appears to be a direct relationship betweenthe service revenue and the office expenses incurred.Problem 2.38, continuedThere aCHAPTER 3:Statistical Description of Datato accompanyIntroduction to Business Statisticsfourth edition, by Ronald M. WeiersPresentation by Priscilla Chaffe-Stengel Donald N.

44、 Stengel 2002 The Wadsworth GroupCHAPTER 3:Statistical DescripChapter 3 - Learning ObjectivesDescribe data using measures of central tendency and dispersion:for a set of individual data values, andfor a set of grouped data.Convert data to standardized values.Use the computer to visually represent da

45、ta.Use the coefficient of correlation to measure association between two quantitative variables. 2002 The Wadsworth GroupChapter 3 - Learning ObjectiveChapter 3 - Key TermsMeasures of Central Tendency,The CenterMean, population; , sampleWeighted MeanMedianMode(Note comparison of mean, median, and mo

46、de) 2002 The Wadsworth GroupChapter 3 - Key TermsMeasures Chapter 3 - Key TermsMeasures of Dispersion,The SpreadRangeMean absolute deviationVariance(Note the computational difference between s2 and s2.)Standard deviationInterquartile rangeInterquartile deviationCoefficient of variation 2002 The Wads

47、worth GroupChapter 3 - Key TermsMeasures Chapter 3 - Key TermsMeasures of Relative PositionQuantilesQuartilesDecilesPercentilesResidualsStandardized values 2002 The Wadsworth GroupChapter 3 - Key TermsMeasures Chapter 3 - Key TermsMeasures of AssociationCoefficient of correlation, rDirection of the

48、relationship: direct (r 0) or inverse (r 0)Strength of the relationship: When r is close to 1 or 1, the linear relationship between x and y is strong. When r is close to 0, the linear relationship between x and y is weak. When r = 0, there is no linear relationship between x and y.Coefficient of det

49、ermination, r2The percent of total variation in y that is explained by variation in x. 2002 The Wadsworth GroupChapter 3 - Key TermsMeasures The Center: MeanMeanArithmetic average = (sum all values)/# of valuesPopulation: = (Sxi)/NSample: = (Sxi)/nBe sure you know how to get the value easily from yo

50、ur calculator and computer softwares.Problem: Calculate the average number of truck shipments from the United States to five Canadian cities for the following data given in thousands of bags:Montreal, 64.0; Ottawa, 15.0; Toronto, 285.0; Vancouver, 228.0; Winnipeg, 45.0 (Ans: 127.4)x 2002 The Wadswor

51、th GroupThe Center: MeanMeanx The Center: Weighted MeanWhen what you have is grouped data, compute the mean using = (Swixi)/SwiProblem: Calculate the average profit from truck shipments, United States to Canada, for the following data given in thousands of bags and profits per thousand bags:Montreal

52、64.0Ottawa 15.0Toronto 285.0 $15.00 $13.50 $15.50 Vancouver 228.0Winnipeg 45.0 $12.00 $14.00(Ans: $14.04 per thous. bags) 2002 The Wadsworth GroupThe Center: Weighted MeanWhenThe Center: MedianTo find the median: 1. Put the data in an array.2A. If the data set has an ODD number of numbers, the media

53、n is the middle value.2B. If the data set has an EVEN number of numbers, the median is the AVERAGE of the middle two values.(Note that the median of an even set of data values is not necessarily a member of the set of values.)The median is particularly useful if there are outliers in the data set, w

54、hich otherwise tend to sway the value of an arithmetic mean. 2002 The Wadsworth GroupThe Center: MedianTo find theThe Center: ModeThe mode is the most frequent value.While there is just one value for the mean and one value for the median, there may be more than one value for the mode of a data set.T

55、he mode tends to be less frequently used than the mean or the median. 2002 The Wadsworth GroupThe Center: ModeThe mode is tComparing Measures ofCentral TendencyIf mean = median = mode, the shape of the distribution is symmetric.If mode median median mode,the shape of the distribution trails to the r

56、ight,is positively skewed.If mean median median mean,the shape of the distribution trails to the left,is negatively skewed. 2002 The Wadsworth GroupComparing Measures ofCentral The Spread: RangeThe range is the distance between the smallest and the largest data value in the set.Range = largest value

57、 smallest valueSometimes range is reported as an interval, anchored between the smallest and largest data value, rather than the actual width of that interval. 2002 The Wadsworth GroupThe Spread: RangeThe range isKey Concept - ResidualsResiduals are the differences between each data value in the set

58、 and the group mean:for a population, xi for a sample, xi 2002 The Wadsworth GroupKey Concept - ResidualsResiduaThe Spread: MADThe mean absolute deviation is found by summing the absolute values of all residuals and dividing by the number of values in the set:for a population, MAD = (S|xi |)/Nfor a

59、sample, MAD = (S|xi |)/n 2002 The Wadsworth GroupThe Spread: MADThe mean absolThe Spread: VarianceVariance is one of the most frequently used measures of spread,for population,for sample,The right side of each equation is often used as a computational shortcut. 2002 The Wadsworth GroupThe Spread: Va

60、rianceVariance The Spread: Standard DeviationSince variance is given in squared units, we often find uses for the standard deviation, which is the square root of variance:for a population, for a sample,Be sure you know how to get the values easily from your calculator and computer softwares. 2002 Th