Four steps of a hypothesis test PDF

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Four steps of a hypothesis test 1. Statement of the hypothesis 2. Setting of the criteria for a decision 3. Collection of data and computation of sample statistics 4. Decision making Hypothesis testing: Statistical method that uses sample data to evaluate a supposition about a population

Null hypothesis: states that in the general population there is no change, no difference, or no relationship Alternative hypothesis: states that there is a change, a difference, or a relationship for the general population Alpha level: probability value that is used to defines the concept of very unlikely Critical region: group of extreme sample values very unlikely to be obtained if null hypothesis is true Test Statistic: indicates that the sample data are converted into a single figure to test a hypothesis Type 1 error: Occurs when a researcher rejects a null hypothesis that is actually true Type 2 error: occurs when a researcher fails to reject a null hypothesis that is in fact false Beta: probability of a Type 2 error Significant: result that is very unlikely to occur when the null hypothesis is true Directional hypothesis test: method wherein statistical suppositions specify either an increase or a decrease in the population mean Effect size: measurement of the absolute magnitude of a treatment result Cohen’s D: measure of the distance between two means, typically reported as a positive number Power: probability that the test will correctly reject a false null hypothesis SS/df : calculation of the sample variance as a substitute for the unknown population value V s2/N : estimation of the standard error M-u/SM: computation of the T statistics using the estimated standard error Estimated standard error of M: approximation of the standard distance between a sample mean and the population mean

T statistic: hypothesis testing tool in which estimated standard error is used in the Z-score formula denominator Degree of freedom: figure in a sample that is independent and can vary T distribution: complete set of T values computed for every possible random sample for a sample size Estimated Cohen’s D: figure calculated when substituting sample values In place of population vales Percentage of variance accounted for by the treatment: measurement of reduction in variability after removing the treatment effect Confidence interval: range of values centered on a sample statistic...