1. AP EXAM AP students in psychology should be able to do the following:
Research Methods (8–10%)
Psychology is an empirical discipline. Psychologists develop knowledge by doing research. Research provides guidance for psychologists who develop theories to explain behavior and who apply theories to solve problems in behavior.
AP students in psychology should be able to do the following:
• Differentiate types of research (e.g., experiments, correlation studies, survey research, naturalistic observations, case studies) with regard to purpose, strengths, and weaknesses.
• Describe how research design drives the reasonable conclusions that can be drawn (e.g., experiments are useful for determining cause and effect; the use of experimental controls reduces alternative explanations).
• Identify independent, dependent, confounding, and control variables in experimental designs.
• Distinguish between random assignment of participants to conditions in experiments and random selection of participants, primarily in correlational studies and surveys.
• Predict the validity of behavioral explanations based on the quality of research design (e.g., confounding variables limit confidence in research conclusions).
• Distinguish the purposes of descriptive statistics and inferential statistics.
• Apply basic descriptive statistical concepts, including interpreting and
constructing graphs and calculating simple descriptive statistics
(e.g., measures of central tendency, standard deviation).
• Discuss the value of reliance on operational definitions and measurement in behavioral research.
• Identify how ethical issues inform and constrain research practices.
• Describe how ethical and legal guidelines (e.g., those provided by the American Psychological Association, federal regulations, local institutional review boards) protect research participants and promote sound ethical practice.

2. Psychology is first and foremost a science
Psychology is first and foremost a science. Thus it is based in research.

3. Clever Hans
Clever Hans the horse could do simple math and spell out the answers to simple questions. He wasn’t always correct, but he was most of the time.
While a team of scientists, veterinarians, zoologists and circus trainers could not figure out how Hans was correctly answer the questions, Oskar Pfungst, a psychologist did. What did he discover?

4. Hans’ Secret
While Hans could not do math or correctly answer questions on his own, he was very perceptive.
Hans was picking up on subtle body language given off by his owner who asked the questions.
When the owner was hidden from view, suddenly Hans could not answer the questions correctly.
How does this story relate to methodology?

5. Psychology's Main Goal
The goal of psychology is to develop explanations for behavior and mental processes…explain why we do what we do.
These explanations, based on solid empirical studies are called theories.
A theory is a testable explanation for a set of facts or observations.

6. Scientific Method
The scientific method is a 5 step process for empirical investigation of a hypothesis, under conditions designed to control biases and subjective judgments.
Empirical investigation is the collecting of objective information, firsthand, by making careful measurements based on direct experience.

7. The 5 Steps of Scientific Method- Step 1
1. Developing a Hypothesis:
Hypothesis: A statement predicting the outcome of a scientific study or describing the relationship among variables in a study.
A hypothesis literally means a little theory.

8. What is a variable?
A variable is anything that can vary among participants in a study.
E.g. of a Hypothesis
Participating in class leads to better grades than not participating.

9. The 5 Steps of Scientific Method
All hypotheses must be testable and falsifiable, or shown to be either supported or incorrect.
Falsifiability is the possibility that an assertion can be shown false by an observation or experiment. That something is "falsifiable" does not mean it is false; rather, that if it is false, then this can be shown by observation or experiment.
A theory cannot be considered scientific if it does not admit the possibility of being shown false.

10. Operational Definition
All good hypotheses need an operational definition.
An operational definition describes exactly what the variables are and how they are measured within the context of your study.

11. Operational Definitions
Explain what you mean in your hypothesis.
Explain how the variables will be measured in “real life” terms.
How you operationalize the variables will tell us if the study is valid and reliable.
 For example, if you were doing a study on the impact of sleep deprivation on driving performance, you would need to operationally define what you mean by sleep deprivation and driving performance.

12. Operational Definitions
Let’s say your hypothesis is that chocolate causes violent behavior.
What do you mean by chocolate?
What do you mean by violent behavior?
How can it be measured?

13. Step 2: Performing a Controlled Test
2. Performing a controlled test: A hypothesis must undergo rigorous tests before it will be accepted as a legitimate theory.
To make a test controlled, one must account for the independent variable.
Independent Variable: A stimulus condition that the experimenter changes independently of all other carefully controlled conditions in the experiment.

14. 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

15. Step 3: Gathering Objective Data
3. Gathering objective data: getting information by direct observation that relies only on the independent variable and not on the experimenter’s hopes. This data is called the dependent variable.
Dependent Variable: The measured outcome of a study, or the response of the subjects in the study.

16. 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.

17. Independent Variable vs. Dependent Variable
A good way to remember which is which:
Independent Variable (IV) = stimulus or cause
Dependent Variable (DV) = response or effect
Both the IV and the DV must have an operation definition. That means, you must explain what each will look like and how it will be measured.

18. Step 4: Analyzing the Results: Accepting or Rejecting the Hypothesis
4. Analyzing the results: This step consists of looking at the data collected and seeing if it supports or disproves the hypothesis.

19. Step 5: Publishing, Criticizing and Replicating the Results
5. Publishing, criticizing and replicating the results: The last step of the scientific method is to have the results withstand the criticism and scrutiny of the science community.
Critics check each others’ work by replicating the study, sometimes under slightly different circumstances to see if the same results can be duplicated.
Replicate: To do a study over to see if the same results are obtained. To control for bias, the replication is most often done by someone other than the original researcher.

20. Applied V. 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.

21. Methods of Research
Experimental Method: A kind of research in which the researcher controls and manipulates the conditions including the IV.
Steps in designing an experiment
Hypothesis
Pick Population: Random Selection then Random Assignment.
Operationalize the Variables
Identify Independent and Dependent Variables.
Look for Extraneous Variables
Type of Experiment: Blind, Double Blind etc..
Gather Data
Analyze Results

22. Experimental Method Looking to prove causal relationships
Cause = Effect
Laboratory v. Field Experiments
Smoking causes health issues.

23. Beware of Confounding Variables
Confounding Variables: Variables that have unwanted influence on the outcome of an experiment.
Or, other possible explanations for the dependent variable (result).

24. Beware of Confounding Variables
If I wanted to prove that smoking causes heart issues, what are some confounding variables?
Lifestyle and family history may also affect the heart.

25. The Challenges of Experiments
There are many challenges with conducting experiments. First one has to make sure that all groups being tested have the same conditions. This is called control.
Second, for an experiment to be valid, one has to make sure the subjects are drawn from a population which consists of everyone who fits the description of your test group.

26. Random Selection
To ensure we have a group which represents the demographic we want, we must use random selection.
Random Selection: Each subject of the sample has an equal likelihood of being chosen for the experimental group, or the group which gets the independent variable.
-Ex. Names drawn out of a hat.

27. Sampling
To have confidence in results, they need to be taken from a sample of participants chosen in an unbiased manner.
Random Sample: A sample group of subjects selected by chance, or without biased selection techniques.

28. Random Assignment
Once you have a random sample, randomly assigning them into two groups helps control for confounding variables.
Experimental Group v. Control Group.
Group Matching-  ensure that experimental and control group are equivalent on some criterions ( sex, race, height etc).

29. Sampling
Representative Sample: A sample obtained in such a way that it reflects the distribution of important variables in the larger population in which the researcher are interested-variables such as age, SES, ethnicity, education….

30. Non-Experiment Designs
Sometimes we are unable to do experiments for ethical or practical reasons. In this case we must do another kind of research.
-Ex post facto: Research in which we choose subjects based on a pre-existing condition.
-Ex: Cancer research.

31. Correlation Studies
A correlation study is one where researchers try to show the relationship or correlation between two variables (coincidence).
Correlation studies are largely based in statistics.
It is important to remember that correlation does not necessarily mean causation.
If there is no association between two variables, then there is no causal connection.
Ex: People who carry lighters are likely to get cancer. (Carrying a lighter will not cause cancer, BUT people who carry lighters are likely to smoke, thus getting cancer).

32. Correlational Method Illusory Correlation
As more ice cream is eaten, more people are murdered.
Does ice cream cause murder, or murder
cause people to eat ice cream?
Illusory Correlation
-the perception of a relationship where none exists

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

34. Surveys
A survey is a research method where questions are asked to subjects who report their own answers.
What are some dangers of using a survey?

35. Survey Method Most common type of study in psychology
Measures correlation
Cheap and fast
Need a good random sample
Low-response rate

36. Naturalistic Observation
Naturalistic observations are a method where subjects are observed in their natural environment.
Why would it be important for subjects to not know they are being observed?

37. Naturalistic Observation
Pro
Do not manipulate the environment.
Con
Never really show cause and effect.

38. Case Studies A detailed picture of one or a few subjects.
Tells us a great story but is just descriptive research.
Does not even give us correlation data.
The ideal case study is John and Kate. Really interesting, but what does it tell us about families in general?

39. Longitudinal & Cross Sectional Studies
These studies are designed to cut down on time and expense.
In a longitudinal study, one group or subject is studied for an extended period of time to observe changes in the long term.
Same subjects for the entire study
Cross-sectional studies look at a cross section of the population and studies them at one point in time.
Ex: No child left behind

40. Sources of Bias
Personal/ Experimenter Bias: When the researcher allows his or her personal beliefs affect the outcome of the study.
Expectancy Bias: When the researcher allows his or her expectations to affect the outcome of the study.
Reducing Bias
Double-Blind Procedure
A double-blind study is one in which neither the participants or the experimenters know who is receiving a particular treatment. This procedure is utilized to prevent bias in research results.

41. Hindsight Bias
The tendency to believe, after learning the outcome, that you knew it all along.
After the Chris Brown/Rihanna incident….many people said they knew Chris Brown was a violent person!!! Did they really?

42. 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%. (Now that's overconfidence!!!)

43. The Barnum Effect
tendency for people to accept very general or vague characterizations of themselves and take them to be accurate.
False Consensus Effect
tendency to overestimate the extent to which others share our beliefs and behaviors

44. Hawthorne Effect
Some people to work harder and perform better when they are participants in an experiment.
Individuals may change their behavior due to the attention they are receiving from researchers rather than because of any manipulation of independent variables.
Whether the lights were brighter or dimmer, production went up in the Hawthorne electric plant.

45. Other Confounding Variables
Placebo effect
Sometimes the act of taking a pill produces an effect if the person believes the pill is active. To compensate for this, scientists often give placebos to determine if an effect is due to the "real" drug or from the act of just taking a pill. 
Order Effects
The positioning of question or tasks in a survey, test, etc., influences the outcome. This is designed to measure whether the order of the questions makes a difference in the outcome of the survey.

46. Recap: Experimental Vocabulary
Independent Variable: factor that is manipulated
Dependent Variable: factor that is measured
Extraneous Variables: factors that effect DV, that are not IV.
Experimental Group: Group exposed to IV
Control Group: Group not exposed to IV
Placebo: inert substance that is in place of IV in Control Group

47. Using Data: Results & Statistics
Recording the results from our studies.
Must use a common language so we all know what we are talking about.

48. Descriptive Statistics
Just describes set(s) of data.
You might create a frequency distribution.
Frequency polygons or histograms.

49. Frequency Distribution
Frequency Distribution: A summary chart which shows how frequently each of the various scores in a set of data occur.
For example, let’s suppose that you are collecting data on how many hours of sleep college students get each night.
After conducting a survey of 30 of your classmates, you are left with the following set of scores:
7, 5, 8, 9, 4, 10, 7, 9, 9, 6, 5, 11, 6, 5, 9, 10, 8, 6, 9, 7, 9, 8, 4, 7, 8, 7, 6, 10, 4, 8
In order to make sense of this information, you need to find a way to organize the data. A frequency distribution is commonly used to categorize information so that it can be interpreted quickly in a visual way.

50. Frequency Distribution
In our example above, the number of hours each week serves as the categories and the occurrences of each number are then tallied.
Frequency distributions are often displayed in a table format 
Hours of Sleep Each Night
Frequency 4 3 5 6 7 8 9 10 11 1
Total 30

51. Histogram A histogram is very similar to a bar graph
Depicts a frequency distribution where the height of the bars indicates the frequency of a group of scores.
Difference between a bar graph & a histogram I
Histogram = no spaces between bars
Bar Graph= Spaces between each bar

52. Mean, Median, Mode
Mean (average): The measure of central tendency most often used to describe a set of data.
To calculate mean, simply add all the scores and divide by the number of scores.
While the mean is easy to calculate, it has a big downside. It can easily be influenced by extreme scores.
Median: A measure of central tendency represented by the score that separates the upper half of the scores in a distribution from the lower half.
The big advantage of this is the median is not effected by extreme scores.
Mode: A measure of central tendency which represents the score that occurs most often.

53. Mean, Median, Mode
The weekly salaries of six employees at McDonalds are $140, $220, $90, $180, $140, $200.
For these six salaries, find:
(a) the mean
(b) the median
(c) the mode

54. Mean, Median, Mode Answers6
Median: 90,140,140,180,200,220
The two numbers that fall in the middle need to be averaged.
= $160 2
Mode: 90,140,140,180,200,220
The number that appears the most is $140

55. Standard Deviation
Standard Deviation (SD): A measure of variability that indicates the average distance between the scores and their mean.
A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data are spread out over a large range of values.

56. Normal Distribution
The standard deviation and mean together tell us a lot about the distribution of scores.
MEAN=50
SD=20
A data set with a mean of 50 (shown in blue) and a standard deviation of 20.

57. A standard deviation of 15 accounts for about 68% of responses.
Normal Distribution
A normal distribution is a bell shaped curve.
A standard deviation of 15 accounts for about 68% of responses.

58. Skewed Distribution
A distribution is skewed if one of its tails is longer than the other.
The first distribution shown has a positive skew. This means that it has a long tail in the positive direction.
The second distribution has a negative skew since it has a long tail in the negative direction.
Finally, the third distribution is symmetric and has no skew (normal distribution).

59. Don’t forget! Outliers skew distributions.
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)

60. A Skewed Distribution
Are the results positively or negatively skewed?

61. Correlation: Negative and Positive
Correlation: A relationship between two variables in which change in one variable are reflected in the changes in the other variable.
Correlation Coefficient:
A number between –1 and +1 expressing the degree of relationship between two variables.
Shows the strength of the relationship
The relationship gets weaker the closer you get to zero.

62. Correlation Coefficient.
A statistical measure of the extent to which two factors relate to one another

63. Comparing Correlation Coefficients
If the correlation coefficient is a positive number, there is a positive correlation (connection) between the variables.
SAT scores and college achievement—among college students, those with higher SAT scores also have higher grades
If the correlation coefficient is a negative number, there is a negative correlation (connection) between variables.
Education and years in jail—people who have more years of education tend to have fewer years in jail
If the correlation coefficient is 0, there is no correlation between variables.
Positive Correlation
Negative Correlation
No Correlation

64. Correlation Coefficient
Which is a stronger correlation?
-.13 or +.38
-.72 or +.59
-.91 or +.04
Remember : The relationship gets weaker the closer you get to zero.

65. Scatterplot Scatterplot
a graphed cluster of dots, each of which represents the values of two variables
the slope of the points suggests the direction of the relationship
the amount of scatter suggests the strength of the correlation
little scatter indicates high correlation
also called a scattergram or scatter diagram

66. Scores A unit that measures the distance of one score from the mean.
A positive z score means a number above the mean.
A negative z score means a number below the mean.

67. Inferential Statistics
The purpose is to discover whether the finding can be applied to the larger population from which the sample was collected.
T-tests, ANOVA or MANOVA- -A t-test’s statistical significance indicates whether or not the difference between two groups’ averages most likely reflects a “real” difference in the population from which the groups were sampled.
P-value= .05 for statistical significance.
5% likely the results are due to chance. (strong
evidence AGAINST a null hypothesis.)

69. APA Ethical Guidelines for Research
IRB- Internal Review Board
Both for humans and animals.

70. Ethics: Human Research
Consent
( MUST be INFORMED)
The participants of an experiment are asked for their agreement to participate
The decision to participate should be based on informed knowledge of the experiment along with their rights
A guardian or family member should also give consent to the study if the participants are 
Children under 18 years of age 
Adults incompetent of understanding the true nature and aims of the study 
Deception:
Deception should be avoided; however slight deception is permissible if:
Participant bias would result from participants knowing the true aims of the study 
The research has potential significant contribution 
It is unavoidable 
The deception does not cause any distress to the participant, including upon being
informed of the deception
If deception is involved, informed consent is not obtained 
Any deception must be revealed at the earliest opportunity 
Debriefing
At the end of the experiment, the participants should be given a debriefing and should be returned to their normal mental states that they entered the experiment with
Participants are informed about the true purpose of the study after the experiment is done

71. Ethics: Human Research
Right to withdraw:
Participants have the capability to stop their participation anytime during the experiment
Protection from harm:
Any situation that might harm the participants in a physical or psychological way should be avoided at all costs
Confidentiality
The real names of any participants should not be revealed; researchers should use pseudonyms
Observation/
Privacy:
Observations made on anyone without their consent is improper without their informed consent unless observations are made in open, public places
Observations in public spaces are not always allowed; observations targeting people such as lovers or people at urinals is intolerable
Relevant Websites:
Belmont Report--
The Nuremberg Code--
Helsinki Ethcs--
Mnemonic Device:
Obviously Dirty Doughnuts Can Cause Problematic Rashes 
(Observation, Deception, Debriefing, Consent, Confidentiality, Protection, Right to withdraw)

72. Ethics: Animal Research
The three R’s:
Replacement: animals should be replaced with invertebrates or less responsive alternatives whenever possible
Refinement: regulations should be followed to minimize the harm inflicted on the animals; appropriate anesthesia should be used; animals should be protected from pathogens
Reduction: the number of animals should be minimized; alternative methods to using animals should be used whenever possible

73. Ethics: Animal Research
Justification of the Research
There should be a clear scientific purpose of the research
The purpose of the research should be
The research done on animals cannot proceed until the protocol has been reviewed by an appropriate animal care committee.
The researcher should monitor the welfare of the animal throughout the course of the experiment
Personnel
Personnel who work with the animals involved should know these guidelines
All animal use procedures should conform to federal protocol
Acquisition of Animals
Animals that are not bred in the research facility should be obtained lawfully
Any wild animal should be trapped in a humane way
Experimental Procedures
Experiments that use restraints of any kind must follow the federal protocol
Any surgical procedure and anesthesia should be conducted under the management of a person with acute knowledge of the procedure
Care & Housing
Laboratory animals are to be provided with humane care and healthful conditions during their stay in any facilities of the institution.
Relevant Website:

74. Stanford Prison Experiment
Experiments
Milgram’s Experiment
Stanford Prison Experiment

75. Recap: Crash Course (10.51 mins)
Video: