UNIT 2: Research Methods Flashcards
Hindsight Bias
looking back in time makes an event seem as though it were inevitable to happen; ex. after something happens, it just seems so obvious
Overconfidence
occurs when we are more confident that we know something than we are correct
3 Underlying Parts to Science
curiosity (need to find the truth), skepticism (seek proof), and humility (admitting he/she is wrong)
Scientific Method
hypothesis, procedure, observation, conclusion, and report findings
Theory
an explanation that organizes observations and tries to predict outcomes
Hypothesis
a prediction that can be tested
Operational Definition
made to cut down on bias; has two parts: (1) a precise statement of the experimenter’s procedures and concepts and (2) something that is measured numerically ; should be detailed enough to enable other scientists to replicate the experiment
Subjectivity
a judgement based on or including a person’s opinion or emotions
Objectivity
a judgement that has had opinion or emotion stripped away from it
3 Main Types of Research Methods
description (case study), survey, and naturalistic observation
Case Study
a thorough study of one person in hopes of learning about people in general
Survey
asks questions and deals with many more people (cases), but in much less depth; easily quantifies data (turn something into numbers)
Issues with Surveys
wording and random sampling
Wording
results of the survey can be dramatically different depending on the wording of the survey and/or the question order
Random Sampling
surveys must be from a representative sample of whatever group they’re trying to represent. To get a representative sample (where the small-group truly represents the whole group), the survey-takers must come from a random sample
Naturalistic Observation
watching a person or animal behave in its normal surroundings
Correlation Coefficient
used to measure how closely two things go together (or not); seen numerically or in scatter plots
Numerical Correlation Coefficient
on a scale from 1.0 to -1.0; ex: 0.95 (very high), -0.87 (very high), 0.00 (no correlation)
Scatter Plots
graphs with the two things on the X and Y axes and dots scattered throughout the graph
Correlation and Causation
just because the two things correlate, it’s incorrect to say A causes B; only an experiment shows causation because it isolates one variable to be tested
Random Selection
the participants come from a large population and are randomly selected
Random Assignment
the participants are randomly assigned to either the control or the experimental group
Double-blind Procedure
a technique where the participants and researchers don’t know which group they’re in and/or the hypothesis being tested
Placebo Effect
though fake, participants think it’s real and have real positive benefits
Independent Variable (IV)
what the experimenter manipulates; this is the only thing different between the experimental and control groups
Dependent Variable (DV)
what the IV supposedly affects; the DV is what is measured
Confounding Variables
these are other factors that might make the experiment go wrong; these are factors that might affect the DV
Central Tendency
refers to the center of a bunch of numbers; the three usual measurements include mode, mean, median
Mode
the number which occurs most frequently
Mean
the average
Median
the middle number
Range
the distance between the lowest and highest numbers in a group
Standard Deviation
a measurement of how much the numbers vary from the mean (average); if the numbers are close, the SD is low, and vice-versa
Normal Curve
also called “bell curve,” it is often occurs in nature with things like height and intelligence scores on a test
Validity
one of two pillars of measurement; it is a test or bit of research that measures what it’s supposed to measure; ex. you took a test called “Geography Test” but it was algebra. Your score does not reflect your geography knowledge and the test is not valid
Reliability
the test yields the same results over and over; to make test as reliable as possible is to have representative sampling (random selection of participants), low variability (low ranges and low standard deviations = more reliable), and more numbers = better results
Statistical Significance
the observed difference between two numbers is not due to chance; measured by a p-value and goes by the 5% rule (shown like 0.04/4%); ex. scientists will say the numbers are statistically significant if there is less than a 5% chance that they were caused by chance
APA (American Psychological Association)
suggests two things: informed consent (participants know what’s happening and consented) and debriefing (once study is finished, participants and researchers go over it)
Case Study (continued)
Purpose: to gather information
Strengths: inexpensive, can have a single participant
Weaknesses: individual cases can be misleading, doesn’t show causation
Survey (continued)
Purpose: to gather information
Strengths: inexpensive, gathers info fast
Weaknesses: wording and bias can alter results, doesn’t show causation
Naturalistic Observation (continued)
Purpose: to gather information
Strengths: inexpensive
Weaknesses: individual cases can be misleading, doesn’t show causation
Correlation (continued)
Purpose: to find the relationship between two things
Strengths: handles large numbers of people/data
Weaknesses: doesn’t show causation
Experiment (continued)
Purpose: to find cause-and-effect
Strengths: shows cause-and-effect
Weaknesses: more costly, ethical factors may make it impractical
