What makes a difference significant?
In principle, a statistically significant result (usually a difference) is a result that’s not attributed to chance. More technically, it means that if the Null Hypothesis is true (which means there really is no difference), there’s a low probability of getting a result that large or larger.
What does it mean when there is a statistically significant difference?
A statistically significant difference is simply one where the measurement system (including sample size, measurement scale, etc.) was capable of detecting a difference (with a defined level of reliability). Just because a difference is detectable, doesn’t make it important, or unlikely.
Why are models and model development so useful?
Models and model development are useful for helping students learn quantitative skills such as graphing, graphical analysis, and visualization; statistics; computational skills, mathematics…. Many models allow one to perform sensitivity studies to assess how changes in key system variables alter the system’s dynamic behavior.
What are the implications of models of measurement?
If it is based on a sound analysis of the variables to be measured and the measurement operations validly reflect the appropriate sources of variation, the effects on performance, effectiveness, or productivity can be dramatic (e.g., Pritchard et al., 1989).
Why are models useful in science education research?
Models provide an environment for interactive student engagement. Evidence from science education research shows that significant learning gains are achieved when students participate in interactive engagement activities.
Why are models useful in a sensitivity study?
Many models allow one to perform sensitivity studies to assess how changes in key system variables alter the system’s dynamic behavior. Such sensitivity studies can help one identify leverage points of a system to either help one affect a desire change with a minimum effort or to help estimate…