Final answer:
To predict a student's final exam score from their third exam score, one needs specific patterns or data, which are not provided here. A blood pressure medication's effectiveness is tested by comparing systolic pressures before and after medication and requires significance at the 1 percent level. In test crosses, recombinant frequency above 50% is unusual and might indicate independent assortment or linkage with far apart genes. Additionally, being at the 80th percentile in an assignment score signifies outperforming 80% of peers.
Step-by-step explanation:
To predict a student's final exam score based on their score on a third exam, we would typically use an established relationship between third exam scores and final exam scores, such as a regression model or correlation data. However, without that information, making a prediction would be speculative. In a typical classroom setting where performance tends to improve slightly over time due to learning and familiarity with the testing style of the instructor, one might cautiously predict a slight improvement over the third exam score. But without specific data or patterns to base this prediction on, this remains a guess.
Regarding blood pressure medication efficacy, to test the effectiveness of a blood pressure medication, you would compare the systolic pressures recorded before and after the medication using a paired t-test or another appropriate statistical analysis. If the decrease in systolic pressure is statistically significant at the 1 percent significance level, then you would conclude that the medication appears to be effective.
Concerning a test cross for two characteristics, the recombinant offspring's predicted frequency would typically not be 60 percent. In Mendelian genetics, the frequency of recombinant offspring for two unlinked genes is expected to be less than 50 percent due to independent assortment. If it's greater, this might indicate linkage and crossing over between genes. However, 60 percent recombination suggests that the genes in question are very far apart on the chromosome or assort independently.
For the statistical example provided (n² pq 1.96² (0.6)(0.4) 0.9220 EBP2 0.04²), it demonstrates the calculation for the sample size needed in a study. It looks like this is part of a formula for determining the number of subjects needed in a study based on expected effect size, power, and significance level.
In the context of a 60-point written assignment, being in the 80th percentile with a score of 49 means that a student scored better than 80 percent of their peers. Only 20 percent of the students scored higher than 49 points.