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Four big terms in statistics are population, sample, parameter, and statistic: A population is the entire group of individuals you want to study, and a sample is a subset of that group.
Treatment. In an experiment, the factor (also called an independent variable) is an explanatory variable manipulated by the experimenter. Each factor has two or more levels, i.e., different values of the factor. Combinations of factor levels are called treatments.
The term statistical treatment is a catch-all term which means to apply any statistical method to your data. Treatments are divided into two groups: descriptive statistics, which summarize your data as a graph or summary statistic and inferential statistics, which make predictions and test hypotheses about your data.
In Data Analysis: Applying any statistical method like regression or calculating a mean to data. In Factor Analysis: Any combination of factor levels is called a treatment. In a Thesis or Experiment: A statistical treatment is a summary of the procedure, including statistical methods used.
Treatment. In experiments, a treatment is something that researchers administer to experimental units. For example, if the experimental units were given 5 mg, 10 mg, 15 mg of a medication, those amounts would be three levels of the treatment.
Statistics is the collecting, organizing and interpreting of information (data). Individuals are the objects described by a set of data. O Descriptive Statistics: Describing your sample when interpreting your data. Variables are characteristics of individuals.
Individual variable is a basic expression of predicate logic which is used as a place-holder with a predicate letter, instead of an individual constant. Individual variables can be bound by quantifiers, and are indicated by characters of the end of the alphabet.
0:30 2:40 Suggested clip Identifying individuals, variables and categorical variables in a data YouTubeStart of suggested client of suggested clip Identifying individuals, variables and categorical variables in a data
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