1. Wednesday, September 6
Remember Dusty? How could we use correlation to learn more about the relationship with different variables with ADHD?
What is the general ‘rule-of- thumb’ for correlational research?
What is an illusory correlation? Give an example.
Today’s topic:
Experiments and FRQs
Upcoming Dates:
Homework:
Finish reading chapter 2 (pages
FRQ due tomorrow
Work on terms
Assessments:
Quiz?
Test: Tuesday, September 19

2. Correlation Review
Which of the following correlation coefficients is the weakest?
r= -0.73
r= +0.47
r= -0.56
r= +0.69
r= +0.22
Is this scatterplot representing a positive or a negative correlation?

3. Illusory Correlation
Illusory correlation – the perception of a correlation where none exists
Being cold and wet causes one to catch a cold
Humans tend to perceive order in random events… we want order! We want to make sense and organize events!
Random coincidences often don’t look random…

4. Experimental Methods
Because many factors influence everyday behaviors/attitudes, psychologists need to isolate and control variables to establish cause and effect relationships.
They do this using experiments.

5. Experiments
a research method in which an investigator manipulates one or more factors (independent variables) to observe the effect on some behavior or mental process (the dependent variable). By random assignment of participants, the experimenter aims to control other relevant factors.
Manipulate the factors of influence
Hold other variables constant
Unlike correlational studies that uncover naturally occurring relationships, an experiment manipulates a factor to determine its effect.

6. Variables – anything that can vary
Independent variable
The variable manipulated by the experimenter
Dependent variable
The outcome being studied as a result of the ind. variable
Ex: Hypothesis – Pill X can reduce the effects of heart disease.
Ind. - Pill X
Dep. – effects of heart disease

7. Research groups Experimental group Control group Counterbalancing
Participants that receive the independent variable
Control group
Participants NOT exposed to the independent variable
Serves as a comparison for evaluating the effect of the ind. variable (sets a base-line)
Counterbalancing
Using participants as their own control group
Ex: Hypothesis – Pill X can reduce the effects of heart disease. Group A receives Pill X, while Group B receives a placebo (fake drug).
Exp. – Group A receiving Pill X (ind. variable)
Control – Group B receiving placebo

8. Placebos
Placebo – a substance or treatment that has no effect apart from a person’s belief in it.
Placebo effect – a person receiving the placebo may report to positive effects due to a belief in the drug/treatment
Single blind study – participants do not know if they are in the experimental or control group
Double blind study – participants nor researchers know who is in the experimental or control group

9. Experiments Pros: Cons:
Variables can be controlled and manipulated
Can determine cause-and-effect
Can be replicated
Cons:
Labs can not always duplicate real-life environments
Can be expensive
Sometimes not feasible;
not ethical to manipulate certain variables

10. Thursday, September 7
What does it mean if something is statistically significant?
Which measure of central tendency (mode, mean, median) is most effected by outliers?
Today’s topic:
Statistical Research and Ethics in Research
Upcoming Dates:
Homework:
Read
Terms (all of chapter 1 and 2 terms should be done)
Study
Assessments:
Test: Tuesday, September 19

11. Descriptive Statistics
Once research is gathered, it has to be organized in a meaningful way

12. Descriptive Statistics
Descriptive statistics simply describe a set of data
Graphing your findings is usually helpful
Lines graphs (frequency polygons) and bar graphs (histograms) are often used
Central tendency measures statistical data in an attempt to mark the center of a distribution of data

13. Describing Data Measures of Central Tendency
Mode (occurs the most in a distribution)
Mean (arithmetic average of a distribution by adding the scores and then dividing by the number of scores)
Median (middle score in a distribution, half the scores are above it and half are below it)

14. Describing Data Measures of Central Tendency

15. Describing Data Measures of Variability
Range - the difference between the highest and lowest score in a distribution.
Standard Deviation - a computed measure of how much scores vary around the mean score.

16. Statistical significance – if the sample averages are reliable and the difference between the sample averages are large than it is considered statistically significant
It means the difference is probably not due to chance

17. Describing Data Measures of Variability
Normal Curve (bell shaped)
a symmetrical, bell-shaped curve that describes the distribution of many types of data; most scored fall near the mean (68 percent fall within one standard deviation of it) and fewer and fewer near the extremes.

18. COMPARING RESEARCH METHODS
Basic Purpose
How Conducted
What is Manipulated?
Weakness
Descriptive
To observe and record behavior
Case studies, surveys, or naturalistic observations
Nothing
No control of variables; single cases may be misleading
Correlational
To detect naturally occurring relationships; to assess how well one variable predicts another
Compute statistical association, sometimes among survey responses
Does not specify cause and effect
Experimental
To explore cause and effect
Manipulate one or more factors; random assignment to groups
Independent variable(s)
Sometimes not feasible; results may not generalize to other contexts; not ethical to manipulate certain variables