1 / 12

Chapter 14

Chapter 14. Quantitative Data Analysis. Chapter Outline. Quantification of data Univariate Analysis Subgroup Comparisons Bivariate Analysis Introduction to Multivariate Analysis. Developing Code Categories. Two basic approaches:

probinson
Télécharger la présentation

Chapter 14

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

  2. Chapter Outline • Quantification of data • Univariate Analysis • Subgroup Comparisons • Bivariate Analysis • Introduction to Multivariate Analysis

  3. Developing Code Categories Two basic approaches: • Beginning with a coding scheme derived from the research purpose. • Generate codes from the data.

  4. Codebook Construction Purposes: • Primary guide used in the coding process. • Guide for locating variables and interpreting codes in the data file during analysis.

  5. Entering Data • Data entry specialists enter the data into an SPSS data matrix or Excel spreadsheet. • Optical scan sheets. • Part of the process of data collection.

  6. Quantitative Analysis • Univariate - simplest form,describe a case in terms of a single variable. • Bivariate - subgroup comparisons, describe a case in terms of two variables simultaneously. • Multivariate - analysis of two or more variables simultaneously.

  7. Univariate Analysis • Describing a case in terms of the distribution of attributes that comprise it. Example: • Gender - number of women, number of men.

  8. Presenting Univariate Data Goals: • Provide reader with the fullest degree of detail regarding the data. • Present data in a manageable from.

  9. Subgroup Comparisons • Describe subsets of cases, subjects or respondents. Examples • "Collapsing" response categories. • Handling "don't knows."

  10. Bivariate Analysis • Describe a case in terms of two variables simultaneously. • Example: • Gender • Attitudes toward equality for men and women

  11. Constructing Bivariate Tables • Divide cases into groups according to the attributes of the independent variable. • Describe each subgroup in terms of attributes of the dependent variable. • Read the table by comparing the independent variable subgroups in terms of a given attribute of the dependent variable.

  12. Multivariate Analysis • Analysis of more than two variables simultaneously. • Can be used to understand the relationship between two variables more fully.

More Related