GRE Word Scramble

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Question	Answer
• Theory	explanation using an integrated set of principles that organizes observations and predicts behaviors or events
• Hypothesis	testable prediction, often implied by a theory
• Hindsight bias	tendency to believe, after learning an outcome, that one would have foreseen it (I-knew-it-all-along phenomenon)
• Hypothesis testing	inferential procedure that uses sample data to evaluate the credibility of a hypothesis about a population. We want to be able to make claims about populations based on samples
a. Null hypothesis (H0)	the IV (treatment) has no effect on the DV for the population
b. Alternative hypothesis (H1)	the IV (treatment) will have an effect on the DV for the population
a. Type I error	researcher rejected the null hypothesis when it is actually correct
b. Type II error	researcher fails to reject the null hypothesis when the null hypothesis is actually wrong
• Replication	repeating the essence of a research study, usually with different participants in different situations, to see whether the basic finding can be reproduced. If similar results are reported, then confidence in the finding’s reliability grows
• Operational definitions	carefully worded statement of the exact procedures (operations) used in a research study. E.g., “human intelligence” may be operationalized as what an intelligence test measures
• Mean	average of a distribution, obtained by adding the scores and then dividing by the # of scores
• Median	middle score in a distribution; half the scores are above it and half are below it (you have to arrange the scores from highest to lowest).
• Mode	most frequently occurring score(s) in a distribution
• Range	difference between the highest and lowest scores in a distribution
• Standard deviation	computed measure of how much scores vary (are different) around the mean score; more useful to look at than range
o Normal curve (aka normal distribution	these data form a symmetrical bell-shaped curve that describes the distribution of many types of data; most scores fall near the mean (about 68% fall within one standard deviation of it) and fewer and fewer near the extremes
1. Experimentation	• It explores cause and effect
• Experiment	an investigator manipulates one or more factors (independent variables) to observe the effect on some behavior or mental process (dependent variable)
• Random assignment	assigning participants to experimental and control groups by chance, thus minimizing preexisting differences between the different groups
• Experimental group	group exposed to the treatment, that is, to one version of the IV
• Control group	group NOT exposed to the treatment; contrasts with the experimental group and serves as a comparison for evaluating the effect of the treatment
• Variables	anything that can vary and is feasible and ethical to measure
o Independent variable (IV)	in an experiment, the factor that is manipulated; effect is being studied. It is NOT influenced by other factors such as:
o Dependent variable (DV)	in an experiment, the outcome that is measured; the variable that may change when the IV is manipulated. It “depends” on your IV, these are examples:
o Confounding variables	in an experiment, factors other than the factors being studied that might influence a study’s results (random assignment controls this)
• Double-blind procedure	both the participants and research staff are ignorant (blind) about whether the participants have received the treatment or a placebo. Commonly used in drug-evaluation studies
• Placebo effect	results caused by expectations alone; any effect on behavior caused by the administration of an inert substance or condition, which the recipient assumes is an active agent
• Cons to experimental research	highly prone to human error, time-consuming, personal bias, ethical implications, can produce artificial results, it can be expensive
2. Descriptive	• Observes and records behavior
• Case study	one individual or group is studied in depth in the hope of revealing universal principles
• Naturalistic observation	observing and recording behavior in naturally occurring situations without trying to manipulate and control the situation
• Survey	obtaining self-reported attitudes or behaviors of a particular group, usually by questioning a representative, random sample of the group
o Wording effects	small changes in the order or wording can make a big difference in someone’s expressed opinions
3. Correlation	• This is a measure of the extent to which 2 factors vary together, and thus how well either factor predicts the other
• Correlation coefficient	statistical index of the relationship between 2 things
o Positive correlation	indicates a direct relationship, meaning that 2 things increase together or decrease together (e.g., height and weight) (above 0 to +1.00)
o Negative correlation	indicates an inverse relationship. As one thing increases, the other decreases (e.g., as a teen’s screen time goes up, their grades go down) (below 0 to -1.00
• Regression toward the mean	analyzes the results of multiple studies to reach an overall conclusion. This can lead to:
o Illusory correlation	perceiving a relationship when none exists, or perceiving a stronger-than-actual relationship
• Random sample	fairly represents a population because each member has an equal chance of inclusion
• Population	all those in a group being studied, from which random samples may be drawn (except for national studies, this does NOT refer to a country’s whole population)
• Statistical significance	statistical statement of how likely it is that a result (such as a difference between samples) occurred by chance, assuming there is no difference between the populations being studied
 Population-specific error	when the survey is self-selected, or when only those participants who are interested in the survey respond to the questions. Researchers can try to overcome this by finding ways to encourage participation
 Sample frame error	when a sample is selected from the wrong population data
 Non-response error	when a useful response is not obtained from the surveys because researchers we unable to contact potential respondents (or potential respondents refused to respond)
Frequency table	2 columns; one column lists the categories, and the other for frequencies with which the items in the categories occur (how many items fit into each category).
• Bar graphs	to present correlations between quantitative variables when the IV has, or is organized into, a relatively small number of levels. Each point on the graph represents the mean score on the DV for participants at 1 level of the IV
• Box and whisker	summarizes set of data. Shape of the boxplot shows how the data is distributed and it shows any outliers. It’s a useful way to compare different sets of data
• Pie charts	shows relative sizes; it’s a circle with wedges cut of varying sizes marked out like slices of a pie. The relative sizes of the wedges correspond to the relative frequencies of the categories
• Histogram	like a bar graph, but the x-axis is a number line; they’re bar charts for continuous data
• Longitudinal	when researchers repeatedly examine the same individuals to see if any changes may happen over a period of time (type of correlational research)
• Cross-sectional	collect data from multiple individuals at a single point in time. You observe the variables without influencing them

Created by: ismary