1. Research Methods
Chapter 1 & 2

4. What is Research? Definitions…RE-SEARCH…
Quantitative approach…it is about the numbers…
-height, weight, GPA
Qualitative approach (Categorical)…it is not about the numbers…per se…
-political affiliation, gender

5. Classification of Research Questions
Existence Questions
Does X exist?
Composition Questions
What are the components that make up X?
Relationship Questions
Is there a relationship between X and Y?
Comparative Questions
Is Group A different from Group B?
Causality questions
Does X cause, lead to, or prevent changes in Y?
Causality-comparative questions
Does X cause more change in Y than does Z?
Causality-comparative interaction questions
Does X cause more change in Y than does Z under certain
conditions but not other conditions?

6. Hypotheses
A hypothesis is a prediction of the researchers’ expected findings.
Two variables
anxiety and test performance
Question: What is the relationship between anxiety and test performance?
Hypothesis: I predict anxiety and test performance are related.

7. Formulating & Stating Hypotheses
Hypotheses in quantitative studies are formulated before conducting the study.
Hypothesis in qualitative studies are gained throughout the study.
Hypotheses are derived from theory or knowledge gained through literature review.

8. Guidelines for Hypotheses
A good hypothesis
is based upon sound reasoning and is consistent with existing theory or is derived from previous research.
provides an explanation for the predicted outcome.
clearly operationally defines variables and states expected relations among variables.
is testable within a reasonable time frame

9. Types of Hypotheses Nondirectional Hypothesis: Directional Hypothesis:
States that a relationship or difference exists among variables
e.g., There are differences between male and female students in spatial ability.
Directional Hypothesis:
States the expected direction of the relationship or difference among variables
e.g., Male students will outperform female students on a test of spatial ability.

10. Types of Hypotheses Null Hypothesis:
States that there is no significant relationship or difference between variables.
Null hypotheses are stated when there is little existing research or theoretical support for a hypothesis.
e.g., There are no significant differences in spatial ability between male and female students.

11. Hypothesis A good hypothesis: is clearly and concisely stated.
states the relation or difference among variables.
defines variables in measurable terms.

12. Stating the Hypothesis
Model for hypotheses:
P=The participants
X=The treatment, what is changing, the causal or independent variable (IV)
Y=The study outcome, what is being measured, the effect or dependent variable (DV)

13. Example
Identify the P, X, & Y: The purpose of this study is to examine benefits in ninth grade students’ achievement based upon attendance at a Saturday tutoring program.
P=Ninth grade students
X=Saturday program attendance or nonattendance
Y=Achievement

14. Example
Identify the P, X, & Y: The purpose of this study is to examine differences in social skills between those middle school children who are involved in extra- curricular activities and those who are not involved in extra-curricular activities.
P=Middle school children
X=Extra-curricular activities
Y=Social skills

15. Testing the Hypothesis
The hypothesis is used to guide the research study.
The researcher conducts the study and then analyzes the data to determine if the hypothesis is supported.
Hypotheses are not proven—they are supported or not supported.
Valuable contributions to the literature can still be made if a hypothesis is not supported.
Hypothesis testing contributes by expanding, refining, and revising the literature base.

16. Control
Serves as the basis of comparison for the experiment.

17. Hmmm….

18. Misleading Headlines

19. Correlation or Causation ?

21. Correlation, as a statistical term, is the extent to which two numerical variables have a linear relationship (i.e., that increases or decreases at a contsant rate). It is not able to explain why or how, only that is does exist.
Causation, goes a step further stating that a change in the value of the X variable will cause a change in the the value of the y variable
High correlations among variables do not imply causation (e.g., self-concept and achievement).

23. ANY THOUGHTS?

24. Controlling Variable
Confounding variables: variable or factor that was not controlled for, but can have an influence on the results.

25. Appropriate Conclusions
Overstating the results
Headline reads: “Ecstasy use Down from Previous Year.” Reality, the sample was down…?! Read the fine print!
Taking the results beyond the data
Generalizing the results beyond the scope of the study.

26. Good Experiment
As a researcher you want to know that your results were unlikely do to change. I.e., are the results statistically significant!
Make comparison
Includes a large enough sample
Assigns subjects randomly to groups
Controls for variables
Ethical
Collects good data
Makes appropriate conclusions