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In statistical hypothesis testing, a two-sample test is a test performed on the data of two random samples, each independently obtained from a different given population. The purpose of the test is to determine whether the difference between these two populations is statistically significant .
A closed-ended question is any question for which a researcher provides research participants with options from which to choose a response. [1] Closed-ended questions are sometimes phrased as a statement that requires a response. A closed-ended question contrasts with an open-ended question, which cannot easily be answered with specific ...
Statistical hypothesis: A statement about the parameters describing a population (not a sample). Test statistic: A value calculated from a sample without any unknown parameters, often to summarize the sample for comparison purposes. Simple hypothesis: Any hypothesis which specifies the population distribution completely.
In descriptive statistics, summary statistics are used to summarize a set of observations, in order to communicate the largest amount of information as simply as possible. Statisticians commonly try to describe the observations in
A research question is "a question that a research project sets out to answer". [1] Choosing a research question is an essential element of both quantitative and qualitative research . Investigation will require data collection and analysis, and the methodology for this will vary widely.
Test items generally encompass three primary components: Item stem: This represents the question, statement, or task presented. Answer format: The manner in which the respondent provides an answer, including options for multiple-choice questions. Evaluation criteria: The criteria used to assess and score the response.
For exactness, the t-test and Z-test require normality of the sample means, and the t-test additionally requires that the sample variance follows a scaled χ 2 distribution, and that the sample mean and sample variance be statistically independent. Normality of the individual data values is not required if these conditions are met.
Descriptive statistics provide simple summaries about the sample and about the observations that have been made. Such summaries may be either quantitative, i.e. summary statistics, or visual, i.e. simple-to-understand graphs. These summaries may either form the basis of the initial description of the data as part of a more extensive statistical ...