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Determine if a study is correlational, experimental, or quasi-experimental.
Statistics summarize data collected in studies designed to answer research questions about relationships between variables. There are three types of research designs: correlations, experiments, and quasi-experiments.
In correlational studies, the relationship is examined without manipulating any of the variables. Correlational studies address real-life questions, but can’t draw conclusions about cause and effect.
Cause-and-effect conclusions can be drawn from experiments because they use random assignment to assign cases to groups. The independent variable, the cause, is controlled by the experimenter; its effect is measured in the dependent variable.
In quasi-experiments, cases are categorized on the basis of groups they naturally belong to and then compared on the dependent variable. Quasi-experiments look like experiments but have confounding variables like correlational studies.
Classify variables and determine levels of measurement.
Predictor variables (correlations), independent variables (experiments), and grouping variables (quasi-experiments) are explanatory variables, while criterion variables (correlations) and dependent variables (experiments and quasi-experiments) are outcome variables.
Variables are measured at nominal, ordinal, interval, or ratio levels. As the level of measurement moves up, information contained in the number increases from qualitative (nominal), to basic quantitative (rank order at the ordinal level), to more advanced quantitative (distance information for interval level), and finally proportionality at the ratio level.
Learn the language and rules of statistics.
A population is the larger group of cases that a researcher wishes to study. Researchers almost always study samples, which are subsets of populations.
A statistic is a value calculated for a sample and a parameter is a value calculated for a population. Latin letters are used as abbreviations for statistics; Greek letters as abbreviations for populations.
Descriptive statistics are numbers used to describe a group of cases; inferential statistics are used to draw conclusions about a population from a sample.
Following the order of operations for mathematical operations and applying the rules of rounding are necessary to get the right answer.