To determine which score has the higher frequency and which score corresponds to the lower raw score, we need to analyze the given pairs closely.
First, we should look at the definition of frequency in this context. Frequency refers to how often a score appears within the data set. Once we identify the score with the highest frequency from the pairs, we can then compare the two scores to see which score corresponds to the lower raw score.
After examining the pairs:
- Pair A: Score 1 (Frequency: 10), Score 2 (Frequency: 5) – Score 1 has the higher frequency.
- Pair B: Score 3 (Frequency: 7), Score 4 (Frequency: 9) – Score 4 has the higher frequency.
- Pair C: Score 5 (Frequency: 12), Score 6 (Frequency: 8) – Score 5 has the higher frequency.
- Pair D: Score 7 (Frequency: 3), Score 8 (Frequency: 11) – Score 8 has the higher frequency.
Next, to determine which score corresponds to the lower raw score in these pairs, we review the defined raw scores separately:
- From Pair A, Score 1 is lower than Score 2.
- From Pair B, Score 3 is lower than Score 4.
- From Pair C, Score 5 is lower than Score 6.
- From Pair D, Score 7 is lower than Score 8.
In conclusion, by identifying the frequencies, we see which scores are more common and determine the relation of those scores to their raw scores. This analysis helps us understand the distribution of scores and the performance of the individuals in question.