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Quantitative Data Analysis

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Title: Quantitative Data Analysis


1
Chapter 14
  • Quantitative Data Analysis

2
Chapter Outline
  • Introduction
  • Quantification of Data
  • Univariate Analysis
  • Subgroup Comparisons
  • Bivariate Analysis
  • Introduction to Multivariate Analysis
  • Sociological Diagnostics

3
Quantitative Analysis
  • Numerical representation and manipulation of
    observations for the purpose of describing and
    explaining the phenomena that those observations
    reflect.

4
Developing Code Categories
  • Two basic approaches
  • Beginning with a coding scheme derived from the
    research purpose.
  • Generate codes from the data.

5
Student Responses That Can Be Coded Financial
Concerns
6
Question
  • To conduct a quantitative analysis, researchers
    often must engage in a __________ after the data
    have been collected.
  • coding process
  • case-oriented analysis
  • experimental analysis
  • field research study

7
Answer A
  • To conduct a quantitative analysis, researchers
    often must engage in a coding process after the
    data have been collected.

8
Codebook
  • Document that describes the locations of
    variables and lists the assignments of codes to
    the attributes composing those variables.

9
Codebook Construction
  • Purposes
  • Primary guide used in the coding process.
  • Guide for locating variables and interpreting
    codes in the data file during analysis.

10
A Partial Codebook
11
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.

12
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.

13
Univariate Analysis
  • Describing a case in terms of the distribution of
    attributes that comprise it.
  • Example
  • Gender - number of women, number of men.

14
Presenting Univariate Data
  • Goals
  • Provide reader with the fullest degree of detail
    regarding the data.
  • Present data in a manageable from.

15
GSS Attendance at Religious Services, 2000
16
Bar Chart of GSS Attend, 2000
17
Frequency Distribution
  • Description of the number of times that the
    various attributes of a variable are observed in
    a sample.

18
Measurement
  • AverageMeasure of central tendency.
  • MeanResult of diving the sum of the values by
    the total number of cases.

19
Measurement
  • ModeThe most frequently occurring attribute.
  • MedianMiddle attribute in the ranked
    distribution of observed attributes.

20
Three Averages
21
Dispersion
  • Refers to the way values are distributed around
    some central value.

22
Standard Deviation
  • Index of the amount of variability in a set of
    data.

23
High and Low Standard Deviations
24
Continuous and Discrete Variables
  • Continuous variableIncreases steadily in tiny
    fractions.
  • Discrete variableJumps from category to category
    without intervening steps.

25
Subgroup Comparisons
  • Describe subsets of cases, subjects or
    respondents.
  • Examples
  • "Collapsing" response categories.
  • Handling "don't knows."

26
How is the UN doing in solving the problems it
has had to face?
27
Collapsing Extreme Categories
28
Handling dont knows
29
Bivariate Analysis
  • Describe a case in terms of two variables
    simultaneously.
  • Example
  • Gender
  • Attitudes toward equality for men and women

30
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 independent variable
    subgroups in terms of an attribute of the
    dependent variable.

31
Percentaging a Table
  • Some men and women who favor () sexual equality
    or dont (/) favor it.
  • Separate the men and the women (the independent
    variable).
  • Within each gender group, separate those who
    favor equality from those who dont (the
    dependent variable).

32
Percentaging a Table
  • Count the numbers in each cell of the table.
  • What percentage of the women favor equality?
  • What percentage of the men favor equality?

33
Percentaging a Table
  • Conclusions
  • While a majority of both men and women favored
    sexual equality, women were more likely than men
    to do so.
  • Thus, gender appears to be one of the causes of
    attitudes toward sexual equality.

34
Church Attendance Reported by Men and Women in
2000
35
Contingency Tables
  • Values of the dependent variable are contingent
    on values of the independent variable.

36
Multivariate Analysis
  • Analysis of more than two variables
    simultaneously.

37
Multivariate Analysis
  • Analysis of more than two variables
    simultaneously.
  • Can be used to understand the relationship
    between two variables more fully.

38
Question
  • Which of the following describe the analysis of
    more than two variables?
  • experimental designs
  • quasi-experimental designs
  • qualitative evaluations
  • multivariate analysis
  • none of these choices

39
Answer D
  • Multivariate analysis describes the analysis of
    more than two variables.

40
Sociological Diagnostics
  • Multivariate techniques can be used as powerful
    tools for diagnosing social problems.
  • They replace opinions with facts to settle
    ideological debates with data analysis.

41
Quick Quiz
42
  • 1. The process of converting data to numerical
    format is called _______________.
  • feminist research
  • qualification
  • quantification
  • none of these choices

43
Answer C
  • The process of converting data to numerical
    format is called quantification.

44
  • 2. Which of the following are basic approaches to
    the coding process?
  • you can begin with a well developed coding scheme
  • you can generate codes from your data
  • both a and b
  • none of these choices

45
Answer C
  • The following are basic approaches to the coding
    process
  • you can begin with a well developed coding scheme
  • you can generate codes from your data

46
  • 3. A _________________ is a document that
    describes the locations of variables and lists
    the assignments of codes to the attributes
    composing those variables.
  • cross-case analysis
  • codebook
  • constant comparative method
  • monitoring study

47
Answer B
  • A codebook is a document that describes the
    locations of variables and lists the assignments
    of codes to the attributes composing those
    variables.

48
  • 4. The __________ is an average computed by
    summing the values of several observations and
    dividing by the number of observations.
  • frequency
  • mean
  • median
  • mode

49
Answer B
  • The mean is an average computed by summing the
    values of several observations and dividing by
    the number of observations.

50
  • 5. Which of the following are aimed at
    explanation?
  • multivariate analysis
  • bivariate analysis
  • univariate analysis
  • both a and b

51
Answer D
  • Multivariate analysis and bivariate analysis are
    aimed at explanation.

52
  • 6. The multivariate techniques can serve as
    powerful tools for
  • predicting behavior
  • diagnosing social problems
  • reacting to issues
  • all of these choices

53
Answer B
  • The multivariate techniques can serve as powerful
    tools for diagnosing social problems.
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