Abicycle store installs about 400 tires per day. tires are installed monday through friday for 8 hours per day. the owner of the store estimates the number of properly installed tires per week using the process below.

in the first hour of work on monday, 49 out of 50 tires were properly installed.

so, there were about 8(49) = 392 properly installed tires on monday.

considering 5 working days per week, 5(392) = 1,960 is the number of tires properly installed in one week.

which best explains the validity of the results?
the results are likely invalid because it is unlikely that the tires installed in one hour on monday will represent the entire population of tires.
the results are likely invalid because the entire population during one week was not part of the sample.
the results are likely valid because a large number of tires produced during the week were part of the sample.
the results are likely valid because each tire sampled was part of the population of tires that week.

A bicycle store installs about 400 tires per day. Tires are installed Monday through Friday for 8 hours per day. The owner of the store estimates the number of properly installed tires per week using the process below.

In the first hour of work on Monday, 49 out of 50 tires were properly installed.  

So, there were about 8(49) = 392 properly installed tires on Monday.

Considering 5 working days per week, 5(392) = 1,960 is the number of tires properly installed in one week.

Which best explains the validity of the results?

The results are likely invalid because it is unlikely that the tires installed in one hour on Monday will represent the entire population of tires.

The results are likely invalid because the entire population during one week was not part of the sample.

The results are likely valid because a large number of tires produced during the week were part of the sample.

The results are likely valid because each tire sampled was part of the population of tires that week.

Step-by-step explanation:

the results from a pre-test for students for the year 2000 and the year 2010 are illustrated in the box plot. what do these results tell us about how students performed on the 29 question pre-test for the two years?

if we compare only the lowest and highest scores between the two years, we might conclude that the students in 2010 did better than the students in 2010. this conclusion seems to follow since the lowest score of 8 in 2010 is greater in value than the lowest score of 6 in 2000. also, the highest score of 28 in 2010 is greater in value than the highest score of 27 in 2000.

but the box portion of the illustration gives us more detailed information. the middle bar in each box shows us that the median score of 20 in 2000 is greater in value than the median score of 17 in 2010. further, we note that the box and whiskers divide the illustration into four pieces. each of these four pieces represents the same portion of students. so, the upper half of the students in 2000 scored in the same score range as the upper one-fourth of the students in 2010, see the illustration at a score of 20.

by considering the upper one-fourth, upper half, and upper three-fourths instead of just the lowest and highest scores, we would conclude that the students as a whole did much better in 2000 than in 2010. we would conclude that as a whole the students in 2010 are less prepared than the students in 2000.

in this section, we discuss box-and-whisker plots and the five key values used in constructing a box-and-whisker plot. the key values are called a five-number summary, which consists of the minimum, first quartile, median, third quartile, and maximum.

step-by-step explanation: