1. What score has a percentile rank of \( 60 \% \) ? ( 2 pts) 2. What score has a percentile rank of \( 50 \% \) ( 2 pts) 3. What is the percentile rank for \( X=45 \) ? ( 2 pts) 4. What is the percentile rank for \( X=32 \) ? ( 2 pts)
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To determine scores with specific percentile ranks, you must analyze the data distribution. A score that has a percentile rank of \(60 \%\) means that \(60\%\) of the data falls below that score. For \(50\%\), this is the median—essentially the middle point of your dataset. For calculating percentile ranks for specific scores like \(X = 45\) or \(X = 32\), you would compare those scores in your dataset. Using a cumulative frequency distribution can simplify finding out how many scores are below or equal to your score of interest. Remember, the exact values depend on your dataset!