In general, _ % of the values in a data set lie at or below the median. _ % of the values in a data set lie at or below the third quartile (Q3). If a sample consists of 1600 test scores, of them would be at or below the median. If a sample consists of 1600 test scores, __ of them would be at or above the first quartile (Q1)

In general, 50 % of the values in a data set lie at or below the median. 75 % of the values in a data set lie at or below the third quartile (Q3). If a sample consists of 1600 test scores, 0.5*1600 = 800 of them would be at or below the median. If a sample consists of 1600 test scores, 0.75*800 = 1200 of them would be at or above the first quartile (Q1)

Step-by-step explanation:

The median separates the upper half from the lower half of a set. So 50% of the values in a data set lie at or below the median, and 50% lie at or above the median.

The first quartile(Q1) separates the lower 25% from the upper 75% of a set. So 25% of the values in a data set lie at or below the first quartile, and 75% of the values in a data set lie at or above the first quartile.

The third quartile(Q3) separates the lower 75% from the upper 25% of a set. So 75% of the values in a data set lie at or below the third quartile, and 25% of the values in a data set lie at or the third quartile.

The answer is:

In general, 50 % of the values in a data set lie at or below the median. 75 % of the values in a data set lie at or below the third quartile (Q3). If a sample consists of 1600 test scores, 0.5*1600 = 800 of them would be at or below the median. If a sample consists of 1600 test scores, 0.75*800 = 1200 of them would be at or above the first quartile (Q1)

fichoh fichoh · Answer 2 · 2021-10-31T11:04:03+01:00

Using the principle of quartile distribution, the percentage amount of data at or below the median and third quartile are 50% and 75% respectively. Number of scores below the median and at or above the first quartile is 800 and 1200 respectively.

The median(Q2) refers to the second quartile of the the distribution which is 50% of the data or below.

The Lower quartile (Q1) is 25% or below of the distribution while 75% of the distribution refers to the upper quartile (Q3)

The median of 1600 can be calculated thus :

50% × 1600 = 0.5 × 1600 = 800

Above the first quartile :

Below first quartile = 25% × 1600 = 400

Above first quartile = 1600 - 400 = 1200

Therefore, the score above the first quartile is 1200.

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