Unit #1: Research Methods in Psychology & Statistics

The Scientific Attitude

Three main components:

1. Curious eagerness

2. Skeptically scrutinize competing ideas

3. Open-minded humility before nature

Hindsight bias

• The tendency to believe, after learning an outcome, that one would have been able to know it.

• Also known as the “I knew it all along” phenomenon

Overconfidence

The idea that we tend to think we know more than we do

• Using critical thinking, or the scientific attitude

• Using the scientific method to test theories by asking research questions, forming hypotheses, doing research, and interpreting results

How do psychologists ask and answer research questions?

Theory

• An explanation using an integrated set of principles that organizes observations and predicts behaviors or events.

• Based on several research studies that have consistent, similar results

• If it effectively organizes a range of self-reports and observations.

• Leads to clear hypotheses (predictions) that anyone can use to check the theory.

• Often stimulates research that leads to a revised theory which better predicts what we know.

What makes a good theory?

Hypothesis

• A testable prediction, often implied by a theory (X will cause Y)

• The researcher’s best guess about what the results of their research study will be.

• Null Hypothesis: X will not cause Y (it is true until you can prove otherwise)

Falsifiability

• A hypothesis, or theory can be shown to be false by an observation or experiment.

• To say that a certain hypothesis is falsifiable is to say that there is possible evidence that would not count as consistent with the hypothesis.

Basic Research

• Curiosity Driven

• Asks Why, What, How

• Can lead to applied research

Applied Research

• Used to solve problems

• Creat new products

• Can lead to new questions

Qualitative

• Descriptive/Words

• Looks for reasons for behavior

• Interviews, surveys, case studies, observations

• Pro: Cheaper/Quicker

• Cons: Subjective

Quantitative

• Numbers

• Measurable, Statistical

• Looks at relationship between variables

• Supports/refuses hypothesis

• Correlational, Experimental

• Pro: Objective

• Cons: $$$, small groups can force us to make

Experimental Method

• Purpose: measuring the extent to which two factors vary together and how well one factor can predict the other.

• Strengths: Can control or manipulate variables to be more more accurate. Can explain cause and effect. Causal (P-value)

• Weaknesses: Placebo effect—-results caused by expectations alone

Random assignment and Manipulation of variables

What does a true experiment have?

Experimental group

Receives the treatment (independent variable)

Control group

Does not receive the treatment

Operational Definition

Variables and procedures need to be specifically explained/defined in every experiment…vague or incomplete descriptions do not

Replication

Repeating a sudy with different participants but gaining the same results

Correlational Studies

• Purpose: measuring the extent to which two factors vary together and how well one factor can predict the other. How well does A predict B?

• Strengths: Correlation helps us make logical predictions; Often takes place outside of the lab, faster to collect a lot of data.

• Weakness: Correlation is NOT causation! One factor does not CAUSE the other to change. An unknown variable could be influencing the relationship.

Correlation coefficient

the score used to MEASURE

Positive correlation

Coefficient closer to +1

Negative correlation

Coefficient closer to -1

Scatterplot

graphs used to plot the scores and show the correlation

Correlation vs. Causation

• Correlation helps predict

• Correlation does not imply cause and effect

• Example: Being taller can predict a higher temperament score in men. However, BEING TALLER does not EXPLAIN why these men have higher scores.

Survey Studies

• Purpose: Descriptive method; Obtaining self-reported attiudes or behaviors of a group, usually through questioning a random sample.

• Strengths: Able to obtain data from many people faster, cheaper, and thus more easily.

• Weaknesses: Response rate (can be low; not enough people to represent the population properly); Self-report (sometimes people lie; inaccurate answers)

Naturalistic Observations

• Purpose: Descriptive method; Observaing and recording behavior in natural situations without trying to manipulate or control the situation.

• Strengths: Describes behavior as we see it.

• Weaknesses: Does not explain the purposes of behavior (no cause and effect); Pays no attention to mental processes.

Case Studies

• Purpose: Descriptive method; Studying one person or group in-depth in hpe of revealing universal principles.

• Strengths: Can try to understand very specific issues; Helped us develop early brain research.

• Weaknesses: Cannot be used to generalize the whole population; often misleads us.

Longitudinal and Cross-Sectional Studies

These two types of studies often used in developmental or health psychology, helping us understand how humans change over or across time.

Longitudinal Studies

• Purpose: Involves looking at variables over an ectended period of time (weeks, months, years) in the same subjects; Can be any type of Psych research.

• Strengths: Helps us understand changes over time.

• Weaknesses: Participants tend to drop out ovr time; can be expensive

Cross-Sectional Studies

• Purpose: Descriptive method, Conducted at a single point in time, comparing many variables i groups of different ages.

• Strengths: Explains what’s happening in a population NOW; Can look at differences in age groups without doing it over a long period. Can look at many variables at once; usually cheap/fast

• Weaknesses: Not causal (does not manipulate variables); Same weaknesses for surveys (if used)