Psychological Science How psychological research is done.

Curiosity, skepticism, humility Psychology, like all science, uses scientific method to construct theories that organize observations and apply testable hypothesis. Can’t rely on common sense.

Limits of intuition Hindsight bias: We tend to believe, after learning an outcome, that we would have foreseen it all along. “I knew it all along” phenomenon Finding out that something has happened makes it seem inevitable. Overconfidence: We tend to think we know more that we do.

Critical thinking Involves thinking that does not blindly accept arguments and conclusions. Examines assumptions Explores hidden values Evaluates evidence Assesses conclusions Ask questions!

Scientific method Step 1: Theory; an explanation that organizes and links observable facts. Must imply testable predictions (Hypothesis). Step 2: Hypothesis, A testable prediction, often implied by a theory.

Scientific method Step 3: Design Research An “ordeal of proof” for the hypothesis. Operational Definitions: A statement of the exact procedures used in a study. Allows a study to be replicated. That is, to repeat the study with other participants or circumstances to see if the theory hold true.

Scientific method Step 4: Observation Gather objective data from direct observation Step 5: Analyze and Refine Run statistical analysis of the data Refine theory if necessary Ideally will go on to publish, receive criticism and replicate results

Research Method #1: Descriptive Psychologists describe behavior using the: Case study Survey Naturalistic Observation Remember, these methods describe behavior, they do not explain it.

The Case Study Examination of one individual or small group in great depth, hoping to reveal truths about all of us. One of oldest methods Can include interviews, observations, and test scores. Frequently used by clinical psychologists.

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?

The Survey Population: all cases in a group from which samples are drawn from a study. That is, the whole group you want to study and describe. Random Sample: A sample that fairly represents a population because each member has an equal chance of being included. Makes sure the group studied represents the targeted population.

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

The Survey Ask people to report their own behavior, thoughts and attitudes. uses questionnaires or interviews. Participants must be representative of the larger population. Best achieved by random sampling.

Naturalistic Observation Watching and recording the behavior of organisms in their natural environment. Such descriptions can be very revealing, such as tool-using chimps. No variables are manipulated. Often used to generate ideas for other research.

Naturalistic Observation Watch subjects in their natural environment. Do not manipulate the environment. Illuminate human behavior The bad is that we can never really show cause and effect.

Correlational Method Correlation expresses a relationship between two variables. 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?

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. Drug use and grades probably has a negative correlation.

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 or or +.04

Overgeneralization False Consensus Effect The tendency to overestimate how much others share our own beliefs and behaviors. To avoid our tendency to over- generalize we must use random sampling.

Research Method #2: Correlational Correlation coefficient: A statistical measure used to describe the strength of a relationship between two factors. How they will change (vary) together. How they predict one another.

Correlations Negative correlation: inverse relationship between two variables Coefficient up to -1.0 Weak correlation: little or no relationship between two variables. Coefficient is near zero Positive correlation: one variable increases or decreases in direct proportion to the other. Coefficient up to +1.0

Correlation Coefficient Correlation coefficient Indicates direction of relationship (positive or negative) Indicates strength of relationship (0.00 to 1.00) r = +.37

Scatter Plot A graph with dots, each dot representing the relationship between two variables. The slope of the dots suggests the relationship of the variables. The amount of scatter suggests the strength of the correlation.

Scatter Plots Perfect positive correlation (+1.00) No relationship (0.00)Perfect negative correlation (-1.00)

September 23, 2013 Objectives: To develop an understanding of correlation, mean, median, and mode.

Do Now: Give an example of a positive correlation that you have experienced or witnessed.

Correlation Coefficient The correlation coefficient tells us nothing about cause and effect. However, it can help us see things more clearly. That is, see relationships that may not be readily visible to us. Shows us the actual extent to which two things relate. Remember: Correlation does not prove causation (only its possibility)!

Illusory Correlation When we see a relationship that does not exist. We will often notice and recall events that confirm this belief. Especially true in regards to unlikely or dramatic events. We search for order in random events.

Research Method #3: Experimentation Best way to uncover cause and effect; test hypotheses. Can manipulate factors of interest. Or, hold constant (control) other factors. Random assignment is an important factor.

Variables Independent variables (IV): the variable that is manipulated. The one whose effect is being studied. Dependent variable (DV): the behavior or mental process that is being measured. It may change in response to changes in the independent variable. If the DV changes when only the IV is changes, researchers can conclude the change in IV caused the change in the DV.

If… Then… Use an “if…then..” statement to determine the independent and dependent variables. What follows the “if” is the independent variable (or cause.) What follows the “then” if the dependent variable (or effect.)

Eating cookies before class each day will lead to higher average scores. Variables: Independent (IV) Controlled by experimenter The “cause” variable Dependent (DV) Predicted by experimenter The “effect” variable

Between-Subjects design Subjects are randomly assigned to different experimental groups. Those receiving treatment are the experimental condition. Those not receiving treatment are the control condition. They are the comparison group. Between-Subjects design: because the participants in the experimental and control groups are different individuals.

Confounding Variables Differences between the experimental group and the control group other than those resulting from the independent variable. May include experimenter bias or demand characteristics. Random assignment of participants to either control or experimental groups minimizes the existence of preexisting differences.

Random Sampling To select participants from population Allows you generalize results Random Assignment To divide participants into groups Controls confounding variables

Experimenter Bias Experimenter Bias: when the researchers expectations or preferences about the outcome influence the results obtained. For example: Can be unaware he or she is treating either the experimental group or control group differently from the other. A smile to one group

Demand Characteristics Clues participants discover about the purpose of a study. Includes rumors they hear about how they should respond. Single-blind procedures help with this. The participant does not know which group they belong to - experimental or control.

Double-blind procedure To eliminate both experimenter bias and demand characteristics, experimenters use the double-blind procedure: Neither the research staff nor participants know the treatment participants have received. Often used in drug trials.

Placebo effect In drug experiments, the experimental group receives the active drug. The control group receives a placebo, or drug which seems identical, but lacks the active ingredient. Placebo Effect: experimental results are caused by expectations alone. Thinking you are getting treatment can help you improve.

Within-subjects design A research design that uses each participant as his or her own control. For example; comparing participants behavior before receiving treatment to her behavior after receiving treatment. Counterbalancing: When two treatments are used half the subjects get one first, the other subjects get the other treatment first. Determines if the order of the treatments cause an effect.

Statistical Reasoning Range: Difference between the highest and lowest score. Standard Deviation: How much scores vary around the mean. Statistical significance: how likely it is that a result occurred by chance.

Measures of central tendencies Mode: The most frequently occurring score. Mean: The average Add all scores and divide by total number of scores. Median: The middle score. Half are below and half are above.

Let’s do an experiment. Hypothesis: The red pill will reduce anxiety. We operationalize the definition of anxiety to mean those whose doctors claim they suffer from anxiety. We find 100 people who fit the operationalized definition

We randomly assign half the men to the experimental group and half the men to the control group. (Same with women). I, the researcher, do not know which group will receive the medication and which will receive the placebo. That means this is a double-blind experiment. This will reduce experimenter bias.

The experimental group will receive the actual medication. The medication is called the independent variable. The control group will receive a sugar pill (the placebo). The research team will ask all participants to measure their level of anxiety on a scale from 1 to 10. Anxiety is the dependent variable (what is measured).

The control group will usually report a decrease in anxiety even though they received no medicine. This is called the placebo effect.

Now that the experiment phase is done, you must consider the confounding variables. This is the stuff that will screw up your experiment. Ex: what if the control group had a mean age much less than the experimental group? What if the 2 groups had a different percentage of women?

Our original hypothesis was: the red pill will reduce anxiety by 40%. Results: The experimental group reported a mean of 10% reduction in anxiety versus a 5% reduction for the control group. Theory: After several replications, the medicine has no significant effect on anxiety.

Reliability and validity? A finding is reliable if it can be replicated. If subsequent studies show that the red pill reduces anxiety then the findings are reliable, thus supporting the hypothesis. A study is valid if it measures what it is supposed to measure. If our experiment measured hypertension instead of anxiety, then the test is invalid, even if it is reliable.