市场调查方式英文版第十四章

1、LEARNING OUTCOMESKnow that analysis consists of summarizing, rearranging, ordering, or manipulating dataCreate and interpret simple tabulation and cross-tabulation tablesUnderstand how cross-tabulations can reveal relationshipsPerform basic data transformationsDefine hypothesis and significance leve

2、lDiscuss the steps in the hypothesis-testing procedureDescribe the factors that influence the choice of statistical methods to use for analysisAfter studying this chapter, you should be able to1The Nature of Descriptive AnalysisDescriptive AnalysisThe elementary transformation of raw data in a way t

3、hat describes the basic characteristics such as central tendency, distribution, and variability.HistogramA graphical way of showing a frequency distribution in which the height of a bar corresponds to the observed frequency of the category.2EXHIBIT 14.1Levels of Scale Measurement and Suggested Descr

4、iptive Statistics3TabulationTabulationThe orderly arrangement of data in a table or other summary format showing the number of responses to each response category; tallying. Frequency TableA table showing the different ways respondents answered a question.4Cross-TabulationCross-TabulationAddresses r

5、esearch questions involving relationships among multiple less-than interval variablesResults in a combined frequency table displaying one variable in rows and another variable in columns.Contingency TableA data matrix that displays the frequency of some combination of responses to multiple variables

6、.MarginalsRow and column totals in a contingency table, which are shown in its margins.5EXHIBIT 14.2Cross-Tabulation Tables from a Survey on Ethics in AmericaFrom Roger Ricklefs, “Ethics in America, The Wall Street Journal, October 31, 1983, p. 33, 42; November 1, 1983, p. 33; November 2, 1983, p. 3

7、3; and November 3, 1983, pp. 33, 37.6EXHIBIT 14.3Possible Cross-Tabulations of One Question7Cross-Tabulation (contd)Percentage Cross-TabulationsStatistical base: the number of respondents or observations (in a row or column) used as a basis for computing percentages.Elaboration and RefinementElabora

8、tion analysis: an analysis of the basic cross-tabulation for each level of a variable not previously considered, such as subgroups of the sample.Moderator variable: a third variable that changes the nature of a relationship between the original independent and dependent variables.8EXHIBIT 14.4Cross-

9、Tabulation of Marital Status, Sex, and Responses to the Question “Do You Shop at Target?9Cross-Tabulation (contd)How Many Cross-Tabulations?Every possible response becomes a possible explanatory variable.When hypotheses involve relationships among two categorical variables, cross-tabulations are the

10、 right tool for the job.10Data TransformationData Transformation (also Data Conversion)The process of changing the data from their original form to a format suitable for performing a data analysis addressing research objectives.Bimodal11Calculating Rank OrderRank OrderRanking data can be summarized

11、by performing a data transformation.The transformation involves multiplying the frequency by the ranking score for each choice to resulting in a new scale.12EXHIBIT 14.5Executive Rankings of Potential Conference Destinations13EXHIBIT 14.6Frequencies of Conference Destination Rankings14Tabular and Gr

12、aphic Methods of Displaying DataTablesAre useful for presenting numerical informationFacilitate summarization and communication of dataCan include stubheads and bannerheads that allow the reader to view several cross-tabulations at onceCharts and GraphsTranslate information into visual forms so that

13、 relationships may be easily graspedCan increase the effectiveness of a well-designed presentationCan create strong visual impressions15EXHIBIT 14.7Table of Regional Airline Usage for Vacation/Pleasure by Income and Education Class16EXHIBIT 14.8A Stubhead Format Table Allowing Several Cross-Tabulati

14、ons to Be Included in a Single TableConfidence in Church/Organized ReligionQuestion: I am going to read you a list of institutions in American society. Would you tell me how much confidence you, yourself, have in each onea great deal, quite a lot, some, or very little? The Church or Organized Religi

15、on*Less than 1 percent.From “Confidence in Church/Organized Religion, The Gallup Report 238, July 1985, p. 4.17EXHIBIT 14.9The Basic Forms of Graphic Presentation18EXHIBIT 14.10Line Graphs Highlighting Comparisons over TimeAmericans spend nine more hours at the office today than they did 27 years ag

16、o.Reprinted from “Time Off American Demographics, March 2001, p. 24.19Computer Programs for AnalysisStatistical PackagesSpreadsheetsExcelStatistical software:SASSPSS (Statistical Package for Social Sciences)MINITAB20EXHIBIT 14.11The Basic Data Analysis Window21EXHIBIT 14.12 SAS Computer Output of De

17、scriptive Statistics22EXHIBIT 14.13 SPSS Histogram Output23EXHIBIT 14.14Examples of SPSS Output for Cross-TabulationFrom Real Stats Real Easy: SPSS for Windows. Copyright 1992, SPSS, Inc.24Univariate Statistics: Stating a HypothesisHypothesisUnproven proposition: a supposition that tentatively expla

18、ins certain facts or phenomenaAn assumption about nature of the world.Null Hypothesis (Ho)Statement about the status quoNo difference in sample and populationAlternative Hypothesis (H1)Statement that indicates the opposite of the null hypothesis25The Hypothesis-Testing ProcedureProcessThe specifical

19、ly stated hypothesis is derived from the research objectives.A sample is obtained and the relevant variable is measured. The measured sample value is compared to the value either stated explicitly or implied in the hypothesis.If the value is consistent with the hypothesis, the hypothesis is supporte

20、d.If the value is not consistent with the hypothesis, the hypothesis is not supported.26Significance Levels and p-ValuesSignificance Level ()A critical probability associated with a statistical hypothesis test that indicates how likely an inference supporting a difference between an observed value a

21、nd some statistical expectation is true.The acceptable level of Type I error.p-ValueProbability value, or the observed or computed significance level; p-values are compared to significance levels to test hypotheses.Higher p-values equal more support for an hypothesis.Critical valuesThe values that l

22、ie exactly on the boundary of the region of rejection.27EXHIBIT 14.15A Sampling Distribution of the Mean Assuming = 3.028An Example of Hypothesis TestingThe null hypothesis: the mean is equal to 3.0:The alternative hypothesis: the mean does not equal to 3.0:29An Example of Hypothesis Testing (contd)

23、30EXHIBIT 14.16A Hypothesis Test Using the Sampling Distribution of X under the Hypothesis = 3.031The Chi-Square Test for Goodness of FitChi-square (2) t-testTests for statistical significanceIs particularly appropriate for testing hypotheses about frequencies arranged in a frequency or contingency

24、table.Goodness-of-Fit (GOF)A general term representing how well some computed table or matrix of values matches some population or predetermined table or matrix of the same size.32The Chi-Square Test for Goodness of Fit: The ProcessFormulate the null hypothesis and determine the expected frequency o

25、f each answer.Determine the appropriate significance level.Calculate the 2 value, using the observed frequencies from the sample and the expected frequencies.Make the statistical decision by comparing the calculated 2 value with the critical 2 value.33Chi-Square Formula = chi-square statisticOi = observed frequency in the ith cellEi = expected frequency on the ith cellRi = total observed frequency in the ith r