1. Research and Statistics AP Psychology

2. Questions: ► Why do scientists conduct research?  answer answer

3. Questions that Social Psychologists wanted to explore: ► What impact does attractiveness have on perception? ► How do we explain peoples’ behavior?  Famous Experiment Famous Experiment Famous Experiment ► What are the reasons for attitudes or prejudices? ► Why do we conform? ► Why are some people altruistic?

4. ► Describe a phenomenon ► Make predictions about the phenomenon ► Control variables ► Explain phenomenon with some degree of confidence 4 Main Goals of Psychological Research:

5. In order to conduct good psychological research one must:  Use the scientific method. ► Have a clear operational definition.  Allows for replication. ► Have informed consent. ► Follow APA guidelines. APA guidelinesAPA guidelines

7. Various Types of Research Methods Video Video ► Descriptive Research: Scientists use naturalistic observations, case studies, and surveys t o describe and predict behavior and mental processes.

8. Various Types of Research Methods ► Correlational Research: predicts naturally occurring relationships.

9. Various Types of Research Methods ► Experimental Research: Scientists use experiments to control variables and to establish Cause and Effect Relationships (in which one variable can be shown to have caused a change in another.)

10. Descriptive Research ► Naturalistic Observation:  Seeing subjects in natural environment  Best way to gather descriptive data.  Problem- when people know that they are being watched, they act differently. (Hawthorn effect)  Test 1 Test 1 Test 1  Video 1 Video 1 Video 1  Video 2 Video 2 Video 2 ► Case Studies:  Intense examination of a phenomenon.  Useful when something is new and complex.  Problem- limited to what researchers consider important.

11. Surveys ► Researchers use questionnaires and interviews to gather information about behavior, beliefs, and opinions. ► Gives a broad view of a large group. ► Validity depends on representativeness and how questions are worded. ► Problem- people are reluctant to say what they really believe, say what is desired. Descriptive Research

12. Correlation: Correlation: ► Used to say that two traits or behaviors accompany one another and the Correlation Coefficient measures the relationship between the two. ► Correlation does not mean Causation!!! ► Types of correlation:  Positive- two variables same direction  Negative- two variables opposite direction

13. Correlation Coefficient ► A number that measures the strength of a relationship. ► Range is from -1 to +1 ► The relationship gets weaker the closer you get to zero. Which is a stronger correlation? ► -.13 or +.38 ► -.72 or +.59 ► -.91 or +.04

14. Experiments: ► Establish a Cause and Effect relationship. ► Allow researchers to control variables.  By manipulating variables, researchers view effects.  Types of Variables: ► Independent- manipulated factor. ► Dependent- factor that is observed and measured. (depends on the application of the independent variable) ► Confounding a.k.a.Random Variables- uncontrolled factors in research design.

15. Experimental Method: ► 1. Observe some aspect of the universe. ► 2. Invent a tentative description, called a hypothesis, that is consistent with what you have observed. ► 3. Use the hypothesis to make predictions. ► 4. Test those predictions by experiments or further observations and modify the hypothesis in the light of your results. ► 5. Repeat steps 3 and 4 until there are no discrepancies between theory and experiment and/or observation.

16. How do I pick the people to study? ► Pick a sample of people from a population so that you can generalize your findings. Regardless of research design)  Population  Random Sample  Random Assignment  Control Group OR Experimental Group  Larger samples yield more reliable results (External Validity)

17. So now, what do we do with all the data collected??????? ► We use STATISTICS! Yay…..

18. Important stuff to know about data… ► In order for data to be considered worthy or good, sound data it must be…  Reliable- stable and consistent  Valid- it is reporting what it set out to report

19. Statistical Analysis of Research Results: Descriptive or Inferential? ► Statistics are methods for demystifying and making meaning from data. ► Numbers have little meaning unless it is organized. An organized list allows us to see clusters or patterns in data. ► Graphing allows us to see some level of meaning from numbers. (Pie Charts, Line Graphs, Frequency Polygon

20. Descriptive Statistics: ► Used to describe and present data. ► They can tell us the difference between two or more groups. ► Basic categories of DS are  1. Central Tendency  2. Variability  3. Correlation

21. Central Tendencies Central Tendencies ► A way to describe the typical or average score distribution. ► Mean- average, can be skewed. ► Median- best indicator of central tendency, middle score. ► Mode- Most frequently occurring score.

22. Variability: ► Indicates how much spread there is in a distribution. ► Range- difference between lowest and highest score. ► Variance- how different scores are from each other. ► Standard Deviation- most common measure of variability. (how far each value is from the mean.)

23. Let’s practice with Central Tendencies ► What options does Mars Co have when filling bags of M&Ms in regard to color? ► FIXED…..RANDOM…..You decide!

24. Choose a sample from the population…..  Propose a hypothesis by recording a % on worksheet. (f = frequency) Calculate %.  Observe and record actual colors in your sample. (how closely do they match?) ► Will you alter your hypothesis?  Get into groups of 5 people. Record data. ► Will you alter your hypothesis?  Get into 2 big groups. Record data. ► Will you alter your hypothesis?  Get into 1 group. Record data. ► Will you alter your hypothesis?

25. So what… ► ….does this tell us about sampling? ► …does this tell us about randomness? ► …does this tell us about the relationship between research and statistics?

26. Normal/Bell Shaped Curve: Intelligence and IQ

27. Correlation: ► Used to describe the relationship between two variables. (co- relation) ► Measured in numbers from -1.0 to +1.0. ► -1.0 indicates negative relationship ► 0 indicates no relationship ► +1.0 indicates positive relationship ► Scatter plots are used for visual representation.

28. Inferential Statistics: ► Provides the researcher with a measure of confidence that the difference between groups is large enough to be important (or small enough to be insignificant.) In other words, IS provide a measure of how likely it was that results came about by chance. In summary it answers the question- was the difference mostly due to the Independent Variable rather than chance factors.

29. Statistically Significant? (Tests of Statistical Significance.) ► t-test: establishes if results were by chance or because of IV. ► ANOVA: compares means of 2 or more groups