This paper compares inferential statistics to single case designs and comments on the usefulness of each of these techniques for the practitioner.
Written in 2004; 1,117 words; 5 sources; MLA; $ 38.95
Paper Summary:
The current paper comments on a quote by J.M Johnson and H.S Pennypacker that compares inferential statistics to single case designs. It discusses how the statement in question calls to account psychology as a science to abandon a traditional reliance on inferential statistics and group design research and to support its practical focus on the individual with reliance on more individually focused research.
From the Paper:
"Inferential statistics is a branch of statistics that consists of generalizing from samples to populations, performing hypothesis testing, determining relationships among variables, and making predictions (Tabachnick & Fidell, 2001). This type of research is the most widely used in psychology, with the majority of published studies in this field relying solely on the use of group comparisons. The major argument for the use of inferential statistics is that it increases the external validity of the study and increases the likelihood of the results generalising to other people. These results are gathered by statistical inference where various methods of calculation are used to find a central tendency within a group. The variability of the results between subjects are often explained by measurement error or extraneous variability because well conducted group research introduces the only variability deliberately as an intervention designed to examine and measure its effect(s) on subjects (Hayes, Barlow & Nelson-Gray, 1999)."
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