Question: Use a pie chart to display the data, which represent the numbers of student loan borrowers (in millions) by balance owed in a recent

Use a pie chart to display the data, which represent the numbers of student loan borrowers (in millions) by balance owed in a recent quarter. Describe any patterns. $1 to $10,000 16.1 $10,001 to $25,000 12.9 $25,001 to $50,000 8.1 $50,001+ 6.1 Which pie chart below displays the data? O A. C. $1 to $10,000 $10,001 to $25,000 $25,001 to $50,000 $50,001+ $1 to $10,000 $10,001 to $25,000 $25,001 to $50,000 $50,001+ What best describes the data? A. Most student loan balances are $25,000 or less. B. Most student loan balances are $50,001 or more. B. $1 to $10,000 $10,001 to $25,000 $25,001 to $50,000 $50,001+ D. $1 to $10,000 $10,001 to $25,000 000 C. Most student loan balances are between $25,001 and $50,000. D. Most student loan balances are $25,001 or more. $25,001 to $50,000 $50,001+ Compare the three data sets on the right. (i) 7 8 9 10111213 (ii) 7 8 9 10111213 Q Q (!!!) 7 8 9 10111213 (a) Which data set has the greatest sample standard deviation? A. Data set (ii), because it has more entries that are farther away from the mean. B. Data set (iii), because it has more entries that are close to the mean. C. Data set (i), because it has two entries that are far away from the mean. Which data set has the least sample standard deviation? A. Data set (iii), because it has more entries that are close to the mean. B. Data set (i), because it has less entries that are farther away from the mean. O C. Data set (ii), because it has more entries that are farther away from the mean. (b) How are the data sets the same? How do they differ? A. The three data sets have the same standard deviations but have different means. B. The three data sets have the same mean and mode but have different medians and standard deviations. C. The three data sets have the same mode but have different standard deviations and means. O O O D. The three data sets have the same mean, median and mode but have different standard deviations.
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