1 / 9

Chapter 14 Quantitative Data Analysis

Chapter 14 Quantitative Data Analysis. Key Terms. Quantitative analysis Numerical representation and manipulation of observations for the purpose of describing and explaining the phenomena that those observations reflect.

jhammond
Télécharger la présentation

Chapter 14 Quantitative Data Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Chapter 14 Quantitative Data Analysis Key Terms

  2. Quantitative analysisNumerical representation and manipulation of observations for the purpose of describing and explaining the phenomena that those observations reflect. CodebookDocument that describes the locations of variables and lists the assignments of codes to the attributes composing those variables.

  3. Univariate analysisDescribes a case in terms of a single variable - the distribution of attributes that comprise it. Frequency distributionDescription of the number of times that the various attributes of a variable are observed in a sample.

  4. AverageMeasure of central tendency. MeanResult of diving the sum of the values by the total number of cases.

  5. ModeThe most frequently occurring attribute. MedianMiddle attribute in the ranked distribution of observed attributes.

  6. DispersionRefers to the way values are distributed around some central value. Standard deviationIndex of the amount of variability in a set of data.

  7. Continuous variableIncreases steadily in tiny fractions. Discrete variableJumps from category to category without intervening steps.

  8. Bivariate analysisAnalysis of two variables simultaneously. Focus is on the variables and the empirical relationships. Contingency tablesValues of the dependent variable are contingent on values of the independent variable.

  9. Multivariate analysisAnalysis of more than two variables simultaneously.

More Related