3 - Nature of Quantiative Research

Question 1

the main steps in quantitative research

Answer 1

theory, hypothesis, research design, devising measures of concepts, select research site, select research subjects/respondents, administer research instruments/collect data, process data, analyze data, findings/conclusions, write up findings/conclusions

Question 2

concept

Answer 2

ideas or mental representations of things

• building blocks of theory
• represents points around which social research is conducted
• categories for organization of ideas/observation
• concept can be interdependent or dependent variable, descriptive or comparative

Question 3

independent variable vs dependent variable

Answer 3

something to be explained vs possible explanation

Question 4

concept can be descriptive or comparative

Answer 4

changes in amount of social mobility in Canada over time vs variations among comparable nations in levels of social mobility

Question 5

why measure concepts?

Answer 5

1. allows for delineation of fine differences between people in terms of characteristic in question (it’s harder to recognize fine distinctions than extreme differences)
2. Provides consistent device for gauging distinctions (measure’s results shouldn’t be affected by time/person administering the measure)
3. Provides basis for estimates of the nature/strength of relationship between concepts

Question 6

Indicators

Answer 6

stand for or represent concept, necessary to measure concepts (can be indirect, for example absenteeism as an indicator for low job satisfaction)

Question 7

two types of definitions of concepts in quantitative research

Answer 7

1. nominal; describes in words like dictionary (crime is any violation of the Criminal Code of Canada)
2. operational; spells out operations that will be performed to measure concept (to measure crime, this researcher will use statistics provided by police force)

Question 8

ways to devise indicators

Answer 8

through questions part of the interview/questionnaire (respondents attitudes, personal experiences, behaviours, etc)
developing criteria for classifying observed behaviour (pupil behaviour in classroom)
through use of official statistics (stats canada)
developing classification schemes to analyze written data (analysis of how newspapers characterize sex workers)

Question 9

using multiple-item measures in survey research

Answer 9

single indicator may misclassify some individuals if wording leads to misunderstanding of meaning
single indicator may not capture all meaning in underlying concept
multiple indicators allow for finer distinctions and sophisticated data analysis

Question 10

reliability

Answer 10

concerned with consistency of measures by looking at stability over time, internal reliability, and inter-observer consistency

Question 11

stability over time

Answer 11

• whether results fluctuate as time progresses, assuming that thing being measured isn’t changing
• most thermometres have this reliability
• test using Test-retest method

Question 12

internal reliability

Answer 12

• aka consistency
• multiple measures administered in one sitting should be consistent
• cronbach’s alpha coefficient
• split half method

Question 13

cronbach’s alpha coefficient

Answer 13

commonly used test in which 1 is perfect internal reliability and 0 is no internal reliability, and .8 is typically considered minimum acceptable level

Question 14

split half method

Answer 14

indicators divided into two halves, respondent’s scores should correlate, in which 1 is perfect internal reliability and 0 is no internal reliability

Question 15

inter-observer consistency

Answer 15

• judgements between several researchers in activity involving subjective judgement
• ex: classifying and categorizing open answers

Question 16

measurement validity

Answer 16

whether indicator accurately/properly gauges concept

-face, concurrent, construct, convergent

Question 17

face validity

Answer 17

measure appears to reflect concept, essentially intuitive process

Question 18

concurrent validity

Answer 18

examining when criterion differs from case to case
-ex: when measuring absenteeism as indicator for low job satisfaction, lack of absenteeism should be seen in those with high job satisfaction

Question 19

construct validity

Answer 19

whether concepts relate to each other in a way consistent to what their theories would predict
ex: routine jobs should have lower job satisfaction than jobs with varied activities. if the routine jobs are found to have equal job satisfaction as complex jobs, it lacks construct validity. Either measure was invalid, deduction was misguided, or theory needs revision

Question 20

convergent validity

Answer 20

• validity should be gauged through comparison to other measures of same concept developed through different methods
• ex problem with convergent approach: measuring crime though police reports or victimization surveys

Question 21

which validities are more important?

Answer 21

face and internal are usually the only ones tested

Question 22

if measure is not reliable ….

Answer 22

it cannot be valid

Question 23

goal of quantitative researchers

Answer 23

to understand social order by making sense of phenomena and evaluate theories and interpretations

Question 24

establishing causality

Answer 24

describing why, not just how

good quantitative research inspires confidence in researcher’s causual inferences

Question 25

generalization of findings

Answer 25

sample must be as representative as possible in order to be confident results are not unique to the sample
probability sampling largely eliminates bias through random sampling

Question 26

critiques of quantitative research

Answer 26

• fails to distinguish people from ‘world of nature’ (some claim science is only applicable to entities/processes that lack self-reflection)
• measurement process produces false sense of precision/accuracy
• reliance on procedure creates disjuncture between research and everyday life (relates of external validity, difference between what people do/say they’ll do)
• analysis of relationship between variables promotes view of social life as remote from everyday experiences
• explanations for findings may not be empathetic (ex: poor inner city areas see more unwed mothers with children because women are marrying later in life instead of marriage losing its popularity)
• assumption of objectivist ontology (assumes reality exists)