100 .14 or larger 120 .13 or larger 140 .12 or larger 160 .11 or larger 200 .10 or larger 240 .09 or larger 310 .08 or larger 400 .07 or larger 540 .06 or larger 780 .05 or larger Note. Statistical significance is at the .05 (two-tailed t-test) and based on a standard deviation of .50 for each score. The statistical significance of differences would vary depending of the actual standard deviations. Additional helpful notes to consider: Observe that as the size of the sample increases, the size of the difference needed for statistical significance decreases. Thus, be very cautious in concluding that differences are important when looking at small samples. Keep in mind that the actual score may be more meaningful than a statistically significant difference. For example, 2.7 may be significantly greater than 2.3, but both scores are low compared to other schools. Likewise, 3.8 may be significantly greater than 3.5 but both are very high and likely indicate no need for improvement. Be aware that the size of the differences needed for statistical significance are estimates. Be aware that practical significance is NOT the same as statistical significance. A good example is finding a difference of only .05 to be statistically significant in a sample of 800 students. Is that difference truly meaningful or of practical significance?
100 .14 or larger 120 .13 or larger 140 .12 or larger 160 .11 or larger 200 .10 or larger 240 .09 or larger 310 .08 or larger 400 .07 or larger 540 .06 or larger 780 .05 or larger Note. Statistical significance is at the .05 (two-tailed t-test) and based on a standard deviation of .50 for each score. The statistical significance of differences would vary depending of the actual standard deviations. Additional helpful notes to consider: Observe that as the size of the sample increases, the size of the difference needed for statistical significance decreases. Thus, be very cautious in concluding that differences are important when looking at small samples. Keep in mind that the actual score may be more meaningful than a statistically significant difference. For example, 2.7 may be significantly greater than 2.3, but both scores are low compared to other schools. Likewise, 3.8 may be significantly greater than 3.5 but both are very high and likely indicate no need for improvement. Be aware that the size of the differences needed for statistical significance are estimates. Be aware that practical significance is NOT the same as statistical significance. A good example is finding a difference of only .05 to be statistically significant in a sample of 800 students. Is that difference truly meaningful or of practical significance?
SCS-Interpret-Worksheet-2018-STUDENT.docx