A general discussion of significance tests for relationships between two continuous variables. Factors in relationships between two variables The strength of the relationship: is indicated by the correlation coefficient: r but is actually measured by the coefficient of determination: r2 The significance of the relationship is expressed in probability levels: p (e.g., significant at p =.05) This tells how unlikely a given correlation coefficient, r, will […]
Descriptive research design helps in gathering information that will display relationships between variables without changing the environment (U.S Department of Health and Human Services: The Office of Research Integrity, n.d.). The use of independent sample t-test is an appropriate choice for a study of t-test method that compares means of two groups of cases. When […]
A statistical test estimates how consistent an observed statistic is compared to a hypothetical population of similarly obtained statistics – known as the test, or ‘null’ distribution. The further the observed statistic diverges from that test population’s median the less compatible it is with that population, and the less probable it is that such a […]
What makes significance testing a fascinating and important case for investigation is that it appears to have dispersed not because of its appropriateness in various research circumstances, but notwithstanding of it. It may certainly be the case – and I can empirically examine that an increase in the use of probability sampling refreshed the application of […]
