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The science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data. |
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A characteristic or attribute that can assume different values. |
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Consists of the collection, organization, summarization, and presentation of data. |
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Generalizing from samples to populations, performing estimations and hypothesis tests, determining relationships among variables, and making predictions. |
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All subjects (human or otherwise) that are being studied. |
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A group of subjects selected from a population. |
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Values that can be counted. |
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Can assume an infinite number of values between any two specific values. They are obtained by measuring. They often include fractions and decimals. |
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Nominal Level of Measurement |
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Classifies data into mutually exclusive (nonoverlapping), exhausting categories in which no order or ranking can be imposed on the data. |
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Ordinal Level of Measurement |
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Classifies data into categories that can be ranked; however, precise differences between the ranks do not exist. |
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Interval Level of Measurement |
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Ranks data and precise differences between units of measure do exist; however, there is no meaningful zero. |
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Ratio Level of Measurement |
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All of the characteristics of interval measurement, and there exists a true zero. In addition, true ratios exist when the same variable is measured on two different members of the population. |
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The researcher merely observes what is happening or what has happened in the past and tries to draw conclusions based on these observations. |
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The researcher manipulates one of the variables and tries to determine how the manipulation influences other variables. |
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Independent Variable
or
Explanatory Variable |
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The variable in an experimental study that is the one thing being manipulated by the researcher.
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A variable that influences the dependent or outcome variable but was not separated from the independent variable. |
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Subjects are selected by random numbers. |
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Sampling Method: Systematic
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Subjects are selected by using every kth number after the first subject is randomly selected from 1 through k. |
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Sampling Method: Stratified
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Subjects are selected by dividing up the population into groups (strata), and subjects are randomly selected within groups. |
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Subjects are selected by using an intact group that is representative of the population. |
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Values (measurements or observations) that variables can assume. |
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Variable whose value are determined by chance. |
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A collection of data values.
Each value is called a "data value" or "datum". |
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The chance of an event occuring. |
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An area of inferential statistics that is a decision-making process for evaluating claims about a population based on information obtained from samples. |
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Variables that can be placed into distinct categories, according to some characteristic or attribute. |
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Numerical variables that can be ordered or ranked. |
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How variables are categorized, counted, or measured. These can either be: nominal, ordinal, interval, or ratio. |
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Samples selected by using chance methods or random numbers. |
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Samples obtains by numbering each subject of the population and then selecting the kth subject. |
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Samples obtained by dividing the population into groups (strata) according to some characteristic that is important to the study, then sampling from each group. |
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Samples obtained by dividing the population into groups called clusters by some means (i.e. geographical location). Then the researcher randomly selects some of these clusters and uses all members of these clusters as the subjects of the samples. |
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Samples obtained through convenience. (The subjects just happened to be there at the time, i.e. a survey). |
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Using already pre-made groups for an experiment. |
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The group that received special instruction.
Opposite: Control group |
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The group that does not receive special instruction/treatment.
Opposite: Treatment group |
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When one is aware that they are part of an experiment. This effects results. |
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