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CHAPTER 14, Quantitative data analysis. Chapter Outline. Quantification of Data Univariate Analysis Subgroup Comparisons Bivariate Analysis Introduction to Multivariate Analysis Sociological Diagnostics Ethics and Quantitative Data Analysis Quick Quiz. Quantification of Data. - PowerPoint PPT Presentation
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CHAPTER 14, QUANTITATIVE DATA ANALYSIS
Chapter Outline
Quantification of Data Univariate Analysis Subgroup Comparisons Bivariate Analysis Introduction to Multivariate Analysis Sociological Diagnostics Ethics and Quantitative Data Analysis Quick Quiz
Quantification of Data
Quantification Analysis – The numerical representation and manipulation of observations for the purpose of describing and explaining the phenomena that those observations reflect.
Age 1 = 1 2 = 2 3 = 3 4 = 4 5 = 5
Sex Male = 1 Female = 2
Political Affiliation Democrat = 1 Republican = 2 Independent = 3
Region of Country West = 1 Midwest = 2 South = 3 Northeast = 4
Develop Code Categories1. Use well-developed coding scheme.2. Generate codes from your data.
Codebook Construction Codebook – The document used in data
processing and analysis that tells the location of different data items in a data file.
The codebook also identifies the locations of data items and the meaning of the codes used.
Purposes of the Codebook1. Primary guide in the coking processes2. Guide for locating variables
Figure 14.1
ATTEND
How often do you attend religious services?
0. Never1. Less than once a year2. About once or twice a year3. Several times a year4. About once a month5. 2-3 times a month6. Nearly every week7. Every week8. Several times a week9. Don’t know, No answer
Abbreviated Variable Name
Nu
meri
cal Lab
el
Definition of the Variable
Variable Attributes
Data Entry Excel SPSS
Univariate Analysis
Univariate Analysis – The analysis of a single variable, for purposes of description (examples: frequency distribution, averages, and measures of dispersion).
Example: Gender The number of men in a sample/population and
the number of women in a sample/population.
Distributions Frequency Distributions – A description of
the number of times the various attributes of a variable are observed in a sample.
Figure 14.3
Figure 14.4
Central Tendency Average – An ambiguous term generally
suggesting typical or normal – a central tendency (examples: mean, median, mode).
Mean – an average computed by summing the values of several observations and dividing by the number of observations.
Mode- an average representing the most frequently observed value or attribute.
Median – an average representing the value of the “middle” case in a rank-ordered set of observations.
Practice: The following list represents the scores on a mid-term exam.
100, 94, 88, 91, 75, 61, 93, 82, 70, 88, 71, 88
Determine the mean.
Determine the mode.
Determine the median.
Figure 14.5
Dispersion – The distribution of values around some central value, such as an average.
Standard Deviation – A measure of dispersion around the mean, calculated so that approximately 68 percent of the cases will lie within plus or minus one standard deviation from the mean, 95 percent within two, and 99.9 percent within three standard deviations.
Figure 14.6
Continuous Variable – A variable whose attributes form a steady progression, such as age of income.
Discrete Variable – A variable whose attributes are separate from one another, such as gender or political affiliation.
Detail versus Manageability Provide reader with fullest degree of detail,
balanced with presenting data in a manageable form.
Subgroup Comparisons
Description of subsets of cases, subjects or respondents.
“Collapsing” Response Categories
Handling “Don’t Knows”
Numerical Descriptions in Qualitative Research
Bivariate Analysis
Bivariate Analysis – The analysis of two variables simultaneously, for the purpose of determine the empirical relationship between them.
Constructing a Bivariate Table1. Determine logical direction of relationship
(independent variable and dependent variable).
2. Percentage down versus percentage across.
Figure 14.7
Percentaging a Table
Constructing and Reading Bivariate Tables
Example: Gender and Attitude toward Sexual Equality1. The cases are divided into men and women.2. Each gender subgrouping is described in
terms of approval or disapproval of sexual equality.
3. Men and women are compared in terms of the percentages approving of sexual equality.
Contingency Table – A format for presenting the relationship among variables as percentage distributions.
Guidelines for Presentation of Tables1. A table should have a heading or title that
describes what is contained in the table.2. Original content should be clearly
presented.3. The attributes of each variable should be
clearly indicated.4. The base on which percentage are
computed should be indicated.5. Missing data should be indicated in the
table.
Introduction to Multivariate Analysis Multivariate Analysis – The analysis of
the simultaneous relationships among several variables.
Quick Quiz
1. To conduct a quantitative analysis, researchers often must engage in a _____ after the data have been collected.A. coding processB. case-oriented analysisC. experimental analysisD. field research study
Answer: A.To conduct a quantitative analysis,
researchers often must engage in a coding process after the data have been collected.
2. Which of the following describe the analysis of more than two variables?A. experimental designsB. quasi-experimental designsC. qualitative evaluationsD. multivariate analysis
Answer: D.Multivariate analyses describe the analysis
of more than two variables.
3. The process of converting data to numerical format is called _____.A. feminist researchB. qualificationC. quantification
ANSWER: C.The process of converting data to numerical format is called quantification.
4. Which of the following are basic approaches to the coding process?A. You can begin with a well developed coding scheme.B. You can generate codes from your data.C. both of the aboveD. none of the above
ANSWER: C.The following are basic approaches to the coding process: you can begin with a well developing coding scheme and/or you can generate codes from your data.
5. A _____ is a document that describes the locations of variables and lists the assignments of codes to the attributes composing those variables.A. cross-case analysisB. codebookC. constant comparative methodD. monitoring study
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.
6. The _____ is an average computed by summing the values of several observations and divided by the number of observations.A. frequencyB. meanC. medianD. mode
ANSWER: B.The mean is an average computed by summing the values of several observations and divided by the number of observations.
7. Which of the following are aimed at explanation?A. multivariate analysisB. bivariate analysisC. univariate analysisD. both A and B
ANSWER: D.Multivariate analysis and bivariate analysis are aimed at explanation.
8. The multivariate techniques can serve as power tools forA. predicting behavior.B. diagnosing social problems.C. reacting to issues.D. all of the above
ANSWER: B.The multivariate techniques can serve as powerful tools for diagnosing social problems.