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GRE
| 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