1. Chapter 2 (continued)
Research Approaches and Methods
of Data Collection
9/11/2012

2. Roadmap
• Confirm roster
• Quick review of last class
• Finish chapter 2 material
• Where we’re headed:
– Finish ch. 2 today
– Chapter 3 on Thursday
– Next Tuesday: Exam 1

3. Quick Review
• Variables in psychology research
– Types
– Roles
• Quantitative vs. Qualitative research
• Experimental research and causation
– Requirements for claims of causation
• Settings for experimental research
– Pros and cons

4. Where we left off…
• Reminder of qualitative vs. quantitative
• “zoom out”
• Other (non-experimental) quantitative
research designs

5. Nonexperimental Quantitative
Research
• A descriptive type of research study
• Defining characteristic: no IV manipulation
• Goals
– Provide an accurate picture of phenomenon
– Describe size and direction of relationships
among variables
• Question: If we care so much about
causation, why would we use this kind of
research design?

6. Types of Nonexperimental
Quantitative Research
• Correlational Studies
• Natural Manipulation
• Longitudinal and Cross-Sectional

7. Correlational Research
• A study that describes the relationship between
two variables
• The goal is often to help with prediction.
• Remember the 3rd variable problem.

8. Remember:
Correlation does not imply causation.
Correlation does not imply causation.
Correlation does not imply causation.
Correlation does not imply causation.
Correlation does not imply causation.
Correlation does not imply causation.
Correlation does not imply causation.
Correlation does not imply causation.
Correlation does not imply causation.
Correlation does not imply causation.
Correlation does not imply causation.
Correlation does not imply causation.

9. Natural Manipulation Research
(a.k.a. quasi-experimental)
• Look at effects of variable(s) not actually under the
experimenter’s control
• Examines the impact of individual difference
variables on an outcome variable
• Individual difference variables are existing
characteristics such as traits, characteristics,
experiences*
– Examples?

10. Longitudinal & Cross-Sectional Designs
• Zoom out: still non-experimental quantitative
research

11. Longitudinal Research
• A study that repeatedly measures the same
variables in a single sample of individuals over
a set time
• The time period can vary greatly.
• At least two measurement points, but can be
more

12. Cross-sectional Research
• Measure variable(s) across representative
samples of individuals that differ on a
characteristic
• Key: measure all at one time point

13. Comparing Longitudinal and
Cross-Sectional
• Both have benefits and drawbacks:
• Time to complete the study
• Feasibility to complete the study
• Richness of data
• Cohort issues

14. Cohort effects
• Different age groups have different
experiences over time
– Example:
• A group of 10-15 year-olds have always used computers
• A group of 60-65 year-olds did not routinely use
computers until they were adults (and some still may not)

15. Cohort-Sequential Design
• A combination of longitudinal and cross-
sectional designs
• Measures the same characteristics at several
selected time intervals in groups at different
age levels
• Benefits: less time, less cost, lower attrition

16. Example:
• Formation and maintenance of best-
friendships in children as they advance from
2nd grade to 5th grade
• What would this look like in a longitudinal
study?
• Let’s see what a cohort-sequential design
would look like

17. Fall Spring Fall Spring
2012 2013 2013 2014
Group
(Starting Point)
2nd graders 2nd 2nd 3rd 3rd
4th graders 4th 4th 5th 5th
• Now you can collect data spanning from 2nd grade
to 5th grade in half the time

18. QUALITATIVE RESEARCH

19. Qualitative Research
• Interpretive research approach relying on
multiple types of subjective data
• Researcher’s goal: understand observations
from the participant’s perspective

20. Features of Qualitative Research
• Generally occurs in the field or participant’s
natural setting
• Triangulation
• deeper understanding of phenomena
• Research questions may evolve over course of
data collection

21. Major Methods of Data collection
• Techniques used to physically gather information
used to answer research questions
• Tests
• Questionnaires
• Interviews
• Focus groups
• Observation
• Existing/ Archival data

22. Tests
• Standardized or researcher-constructed instruments
designed to measure:
– Personality, aptitude, achievement, performance
• Information on reliability, validity, and norms usually
available
• Table 2.3, page 55- benefits/weaknesses

23. Questionnaires
• Self-report data collection instrument
– opinions, perceptions, attitudes
• Paper-and-pencil, computer, online
• Table 2.4, page 57

24. Interviews
• Data collection method in which an interviewer asks
the interviewee a series of questions
• Face-to-face, telephone
• Table 2.5, page 58-benefits/weaknesses

25. Focus Groups
• Collection of data in a group situation in which
a moderator leads a discussion with small
group of participants.
• Especially useful for exploring how people
think about an issue
– The difficulties of focus groups
– Table 2.6, page 59-benefits/weaknesses

26. Observation
• Researcher observes and records individuals’
behavior
• Naturalistic—real-world setting
• Laboratory—in a lab or other controlled setting
created by the researcher
• Table 2.7, page 60-benefits and weaknesses

27. Existing or Secondary data
• Collection of data left behind or originally used for
another purpose.
• Documents
• Physical data
• *Archived research data
• Table 2.8, page 61-benefits and weaknesses