1. Research Methods & Statistics
It’s actually way more exciting than it sounds!!! 

2. Why do we have to learn this research stuff?
Psychology is first and foremost a science…
…So it is based in research.

3. APPLIED VS. BASIC RESEARCH
Applied Research has clear, practical applications.
YOU CAN USE IT!!!
Basic Research explores questions that you may be curious about, but not intended to be immediately used.
Studying how kissing changes when you get older is interesting…but that’s about it.
Research on therapies for drug addicts has a clear purpose.

4. Scientific Attitude
Critical thinking: thinking that doesn’t blindly accept arguments & conclusions BUT examines assumptions, evaluates evidence, & assesses conclusions
1. Curiosity (be eager & inquisitive)
2. Skepticism (scrutinize competing ideas)
3. Humility (recognize that you don’t know everything)

5. Hypothesis & Theory
Hypothesis: a testable prediction about what you expect to happen
Prediction that expresses a relationship between two variables
A variable is anything that can vary among participants in a study
EX: participating in class leads to better test grades than not participating
Theory: an explanation that is testable and backed by evidence
Ex: Freud’s theory of psychosexual dev.

6. Hindsight Bias
Before we dive into how to do research, you should be aware of three hurdles that tend to skew our logic.
The tendency to believe, after learning the outcome, that you knew it all along.
Monday Morning Quarterback!
After Amy Winehouse died my brother said he always knew she was going to die young. Did he really?

7. Overconfidence We tend to think we know more than we do.
82% of U.S. drivers consider themselves to be in the top 30% of their group in terms of safety.
81% of new business owners felt they had an excellent chance of their businesses succeeding. When asked about the success of their peers, the answer was only 39%.

8. EX: Relationship b/w violent media & aggression in kids
3 Types of Research
Psychologists conduct 3 main types of research:
1. Experimental-an investigation seeking to understand relations of cause and effect
2. Descriptive-drawing conclusions from observation & studies
Case studies
Surveys
Naturalistic observations
3. Correlational-assessing the degree of association between 2 or more variables that occur naturally
EX: Relationship b/w violent media & aggression in kids

9. CASE STUDIES
One person is studied in depth in hopes of revealing conclusions about other similar people/cases
Strength: you get a full, detailed picture of one person (tons of info)
Weakness: the findings are not always GENERALIZABLE to the entire population
Individual could be not typical of the larger population

10. Cross-Sectional & Longitudinal Studies
Cross-sectional Study: people of different ages are compared with each other
Longitudinal Study: the same people are restudies & retested over a long period of time
We’ll cover these more in development unit…

11. SURVEYS
Technique for learning self-reported attitudes or behaviors of a particular group by questioning a random sample of the group
Wording is important
Ex: “helping the poor” vs. “welfare”
Ex: 27% approved of “government censorship” of sex & violence in media but 66% approved of “more restrictions on what is shown on tv”
Strengths: cheap & easy way to collect data
Weaknesses:
Not always worded well
People are not always truthful in responses
Very low response rate (maybe 1 in 100)

12. Random Sample
You want to know whether the amount of time spent of homework affects test scores
Identify the population you want to study
Ex: all juniors at La Serna
GET A RANDOM SAMPLE
Represents the larger population b/c everyone has an equal chance of getting chosen (not volunteer=not representative)
Ex: political polls 1500 people across country randomly

13. NATURALISTIC OBSERVATION
Observing & recording behavior in naturally occurring situations
cannot intervene in any way
Ex: watching children interact on a playground
Strengths: easy source of collecting data
Weaknesses:
Cannot know what people are thinking or feeling b/c you are only observing the behavior
Describes behavior but doesn’t explain

14. EXPERIMENTS! The only type of research that can show CAUSE & EFFECT!!!
Operational Definitions
Independent Variable
Dependent Variable
Confounding Variables
Control Group
Experimental Group
Random Assignment
Double Blind
Placebo Effect

15. Operational Definitions
Explain what you mean in your hypothesis.
How will the variables be measured in “real life” terms.
How you operationalize the variables will tell us if the study is valid and reliable.
Let’s say your hypothesis is that chocolate causes violent behavior.
What do you mean by chocolate?
What do you mean by violent behavior?

16. INDEPENDENT VARIABLE Whatever is being manipulated in the experiment.
Hopefully the independent variable brings about change.
*If there is a drug in an experiment, the drug is almost always the independent variable.

17. Dependent Variable Whatever is being measured in the experiment.
It is dependent on the independent variable.
The dependent variable would be the effect of the drug.

18. Beware of Confounding Variables!!!
The object of an experiment is to prove that A causes B.
A confounding variable is anything that could cause change in B, that is not A.
If I wanted to prove that smoking causes heart issues, what are some confounding variables?
Lifestyle and family history may also effect the heart.

19. Random Assignment
Once you have a random sample, randomly assigning them into two groups helps control for confounding variables.
Experimental Group v. Control Group.
Done to assure that each group has minimal differences

20. Control vs. Experimental Group
The group that is given the independent variable
Control Group: the group that is NOT given the independent variable
Serves as comparison to experimental group

21. Single & Double Blind Procedure
Want to avoid experimenter bias
Single Blind: the subjects don’t know if they are in the control of experimental group
Double Blind: neither the subjects nor the researcher know who is in the 2 groups
Requires 3rd party has to participate to obtain data
Placebo
An object/procedure given to control group so they think they are experimental group
Does not contain any of the tested material (IV)

22. Hawthorne Effect But even the control group may experience changes.
Just the fact that you know you are in an experiment can cause change.
Whether the lights were brighter or dimmer, production went up in the Hawthorne electric plant.

23. Research Ethics 1. Obtain informed consent of participants
2. Protect them from harm & discomfort
3. Treat information about participants confidentially
4. Fully debrief participants: explain the research afterward

24. Correlation
Assesses the degree of association between two or more variables that occur naturally together
Ex: Poor school performance may be related to lack of sleep
Ex: education level may be related to political affiliation or income…
Surveys are a good method to provide data for correlations
CORRELATION IS NOT CAUSATION!
Other factors could influence

25. Correlational Method
Correlation expresses a relationship between two variable.
Does not show causation.
As more ice cream is eaten, more people are murdered.
Does ice cream cause murder, or murder cause people to eat ice cream?

26. More Correlation Stuff…
Correlation Coefficient: statistical measure of the relationship between to things (+1 to -1)
The closer to +1 OR -1 the STRONGER the relationship
The closer to 0 the WEAKER the relationship
Scatterplot: graph that represents the values of 2 variables
The direction of dots shows positive or negative correlation
Which is a stronger correlation?
-.13 or +.38
-.72 or +.59
-.91 or +.04

27. Types of Correlation Negative Correlation Positive Correlation
The variables go in opposite directions.
Positive Correlation
The variables go in the SAME direction.
Studying and grades hopefully has a positive correlation.
Heroin use and grades probably has a negative correlation.

28. Positive Correlation b/c both variables are increasing

29. Negative Correlation b/c one variable in increasing and one veriable is decreasing

30. No Relationship (not going in either direction)

31. Statistics Recording the results from our studies.
Must use a common language so we all know what we are talking about.

32. Descriptive Statistics
Just describes sets of data.
You might create a frequency distribution.

33. Central Tendency Mean, Median and Mode.
Watch out for extreme scores or outliers.
Let’s look at the salaries of the employees at Dunder Mifflen Paper in Scranton:
$25,000-Pam
$25,000- Kevin
$25,000- Angela
$100,000- Andy
$100,000- Dwight
$200,000- Jim
$300,000- Michael
The median salary looks good at $100,000.
The mean salary also looks good at about $110,000.
But the mode salary is only $25,000.
Maybe not the best place to work.

34. Normal Distribution
In a normal distribution, the mean, median and mode are all the same.

35. Normal Distribution

36. Distributions
Outliers skew distributions
Mean!!!
If group has one high score, the curve has a positive skew (contains more low scores)
If a group has a low outlier, the curve has a negative skew (contains more high scores)

37. Other measures of variability
Range: distance from highest to lowest scores.
Standard Deviation: the variance of scores around the mean.
The higher the variance or SD, the more spread out the distribution is.
Kobe and Dwight Howard may both score 30 ppg (same mean).
But their SDs are very different.

38. Inferential Statistics
The purpose is to discover whether the finding can be applied to the larger population from which the sample was collected
P-value= .05 for statistical significance
5% likely the results are due to chance

39. Illusory Correlation
When you think that a relationship exists when really there is none
Ex: you think you do better on tests when you wear your lucky sweatshirt

40. Reliable & Valid We want all of our research to be reliable & valid
Reliability (reliable): replicate (repeat) the study & get the same results
Validity (valid): research measures what it is supposed to