Describe effect size estimates, tell how they are related to significance tests, and the information they provide that is not provided by significance tests.

1.  Effect size has has to do with the size of the scatterplot. These relate to significance test because they help to find if thier is any type of relationship (linear/nonlinear) between the variables being used.

2.  Effect size estimates is a way to determine the effect size for a study. It shows how many people we need in the study in order to get a significant result. The effect size can be changed in order to get better significance results. It shows the sign in the correlation. It allows us to look at the sign of the distribution. The effect size estimate provides us with a correlation of the variables.

3.  Effect size tells us the strength and magnitude of the realtionship between two variables.
Pearson's correlation is the most common effect size measure and the r value is the same as the effect size. The sign tells us the direction of the effect and the size tells strenth of the effect. r can also be calculated from the F summary stat in ANOVA by taking the square root of F/(F+df error) and r can also be calucated from the X2 summary stat in a chi-square by taking the square root of X2/N Signficance testing only tells us whether or not there probably is a relationship. It uses the p-value. If P>.05 retain the null and if P< .05 reject the null. The effect size tells us how strong the effect is, it tells us the size of the effect. Significance testing doesn't tell us this it only tells us whether or not there probably is a relationship.

4.  Effect size is the r value. By finding the power and r you can also tell how many subjects you need to find a significant effect. ( p<.05) with the effect size test it does not only tell you if it is significant but if how significant it is and what the percentage chance of a type II error.

5.  The effect size estimates tell the size of the mean difference and how dependable the statistics are. Since the effect size estimates are the "size" of the r, the significant tests are used to determine the direction of the power.

  1. Effect size estimates, r, are used to determine the size of the effect that has potentially been found. The sign is concerned with the type of relationship while the size is concerned with the magnitude of the relationship. Signficance tests only search for whether there is a signficant pattern or not while effect size estimates tell the magnitude of this pattern.
  1. Effect size uses r, which can be described as an estimate of how "good" one's results are depending upon what value of r was obtained. One can take information obtained from ANOVA's and Chi-square's to compute r so that values can be compared from various studies using different designs and analyses. The information effect size estimates provide that is not provided by significance tests is that one can obtain a p-value that can be used as a comparison, and one can compare the results from various studies.