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65 Cards in this Set
- Front
- Back
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statistics
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the science of collecting, analyzing, and interpreting data
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statistic
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measures of some attribute of a sample
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studies
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scientific approaches to acquire information about a small or large group
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case studies
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an analysis of statistics of one element or a small sample of elements
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non-experimental (observational) studies
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analyses that compare or measure similarities/differences within a group that we do not manipulate
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experimental studies
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analyses that allow us to compare or measure similarities/differences between groups that we did manipulate
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true experimental studies
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studies comparing properties in groups that were randomly assigned
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random assignment
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every element in a group has an equal chance of being assigned to the different groups in the study
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single blind studies
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experiments where the elements are unaware of the groups that they are in --> reduces placebo effect
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double blind studies
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experiments where the elements and experimenters are unaware of the groups that they are in --> reduces demand characteristics
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quasi-experimental studies
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studies that compare properties of groups where assignment wasn't possible --> earthquake example
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descriptive statistics
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statistics focused on a group of numerical observations about a population of interest.
Connie is 5'6" tall, 45 of 186 students have earned an A in the class, the age of students in this class has a correlation of 0.26 with their weekly hours of study |
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inferential statistics
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interpretations about populations based on analyses of smaller set of information
College seniors spend more time studying than freshman, we become less sensitive to taste as we age |
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inferential statistics are calculated by...
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looking at a sample and making assumptions about a population
we can infer sample information by ascribing it to a larger group, or to predict other statistics Note: we make a lot of assumptions in inferential statistics, if we're wrong about them, our inferences about the population can often be wrong |
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sample biasing
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incorrectly assuming something about a population because of the sample that was used
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variables
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general characteristics, usually quantified, that VARY and can be used to compare or describe
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variability
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the fact that variables obtained often differ from one another.
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"Good" variability
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individual differences - variation due to the participants themselves
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"Bad" variability
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measurement error - variation due to the inability to measure something accurately
unreliability - variations due to differences in response to the same situation |
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construct
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a hypothetical or theoretical entity that is being explored in research
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operational definition
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the systematic process of obtaining or measuring a construct
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levels
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the values that a construct can take on
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validity
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accuracy of measurement w respect to intent
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construct validity (face)
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is it measuring what we're interested in
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predictive validity
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does the measure predict related behaviors/measures
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concurrent validity
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does it relate to other measures that are supposed to be measuring the same thing
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reliability
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consistency in measurement
inter-rater reliability, test-retest reliability, internal reliability (parallel forms and similar items) |
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continuous variables
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variables that can assume an infinite number of values
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discrete variables
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variables that have a finite set of values that they can be
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categorical (nominal) variables
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variables that have no numerical meaning (gender, favorite ice cream)
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quantitative variables
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the levels of these variables that are represented as numbers
can be continuous or discrete (data dependent), averages and other arithmetic transformations make sense |
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ordinal variable
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variables that have a natural order, but the precise distance between values is not defined
Ex. grades, rank in school |
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interval variable
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variables that have values where the distance btwn them is meaningful and consistent
Ex. IQ scores, temperature in Fahrenheit |
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ratio variables
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interval variables where there is a true zero and where ratios of values make sense.
Ex. income, height, temperature in Kelvin |
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independent variables
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variables that have at least 2 levels that we either manipulate or observe in a group
Note: participants in each level are thought to either display or be exposed to the conditions of this variable in a consistent manner. All variables are independent in observational studies. |
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dependent variables
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variables that are believed to be caused by or changes by the independent variable
Note: dependent variables are only in experimental studies |
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class
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a segment of the measurement scale that contains more than one possible score value
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interval width
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the range of variables in each class
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cumulative frequency
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total # of variables that have occurred up to that point
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relative proportion
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proportion of the sample population that is in a group
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cumulative proportion
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proportion of the sample population that has occurred up to that group
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real limits
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the maximum and minimum score values in a specific group
URL and LRL overlap |
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measures of central tendency
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tell us about the middle of the distribution, or the points around which the distribution is centered.
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variability
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measures of variability allow us to talk about how close or far from the mean the scores in the distribution are
Ex. range, variance, standard deviation |
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population
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a complete set of people, events, or scores that we're interested in
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parameter
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the measurable characteristic of the population that is of interest
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sample
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a subset or portion of the population
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statistic
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the measurable characteristic of the sample of the population that we're interested in
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sampling
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selecting a subset of the population to collect data from (statistics) in order to make inferences about the population (parameter)
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convenience sampling
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taking a select sample from the population that is easily accessible
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volunteer sampling
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sampling that is obtained through the willing participation of particular individuals
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true random sampling
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taking the entire population and selecting a sample randomly from that population
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cluster sampling
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random sampling of organized groups of individuals from the population
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stratified (representative) sampling
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identifying some major characteristics of interest in the population and generating a sample that is proportionally equivalent to the population
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pseudo-random sampling
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taking everyone that is accessible from a population and selecting a sample randomly from that group
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random assignment
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creating groups by giving each participant an equal chance of being in the experimental conditions/levels
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randomized block design (stratified assignment)
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creating equivalent groups based on important characteristics
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convenient assignment
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assignment of individuals based on experimenter discretion.
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sample statistics
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quantities that characterize samples of raw scores
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sampling statistics
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quantities that characterize sampling distributions of statistics
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subjective probability
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probability based on an individual's opinion of the likelihood that an event will occur, or that an event or relationship is due to more than chance
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expected probability
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a measure of the actual probability of an outcome if the outcomes were random and repeated many times
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hypothesis testing
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statistically verifying that the probability of an outcome is significantly different from chance
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type 1 error
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null hypothesis is TRUE, but you reject it
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type 2 error
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null hypothesis is FALSE, but you retain it
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