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--- public:rem4:rem4-15:experimental_designs_ii [2015/09/15 12:23] – created thorisson
+++ public:rem4:rem4-15:experimental_designs_ii [2024/04/29 13:33] (current) – external edit 127.0.0.1
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 === Some Statistical Methods for Experimental Designs: What to Use When ===
-| Selecting between hypotheses  | Statistical tests help you figure out whether the difference (in means) observed in a dependent variable (as measured between two samples) is large enough to indicate a **non-coincidence**. \\ To make this judgement, the "natural" variation in each group is used as a "baseline".  \\ Significance level is a measure that tells you how non-coincidental you want your measure to be, to be considered as "significant". p<0.05 and p<0.01 are most common (less than 5%, 1% probability of the result being random).  |
+| Selecting between hypotheses  | Statistical tests help you figure out whether the difference (in means and distribution) observed in a dependent variable (as measured between two samples) is large enough to indicate a **non-coincidence**. \\ To make this judgement, the "natural" variation in each group is used as a "baseline".  \\ Significance level is a measure that tells you how non-coincidental you want your measure to be, to be considered as "significant". p<0.05 and p<0.01 are most common (less than 5%, 1% probability of the result being random).  |
 |  **What you study**  |  **What you use**  |
 | Two factors varying along a continuum  | Correlation/regression measures  |
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-=== Levels of System Knowledge in Simulation ===
-| 0 Source Level  | What variables to measure and how to observe them  |
-| 1 Data  | Data collected from a source system  |
-| 1 Generative  | Means to generate data in the system  |
-| 1 Structure  | Components (at lower levels) coupled together to form a generative system  |
-| <sub>Source: G. Klir 1985</sub>  |  |
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-=== Using Models to Validate and Measure: The Model Human Processor ===
-| Card, Moran & Newell  | 1983, 1986  |
-| Model Human Processor  | An attempt to an engineering approach to usability studies  |
-| Use data from psychological studies  | Construct a model of a human user  |
-| Various elements of a user's mind  | Memories, perception modules, cycle times, decay times, etc., plus a number of typical performance values and principles on how to use model to predict performance  |
-| Interest has been growing  | But has been slower than most predicted  |
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