PT154.S1.Q8 > Analytics

SECTION 1 · lr

Question 1 Question 2 Question 3 Question 4 Question 5 Question 6 Question 7 Question 8 Question 9 Question 10 Question 11 Question 12 Question 13 Question 14 Question 15 Question 16 Question 17 Question 18 Question 19 Question 20 Question 21 Question 22 Question 23 Question 24 Question 25 Question 26

SECTION 2 · lr

SECTION 3 · rc

PASSAGE 1

Question 1 Question 2 Question 3 Question 4 Question 5 Question 6

PASSAGE 2

Question 7 Question 8 Question 9 Question 10 Question 11 Question 12 Question 13

PASSAGE 3

Question 14 Question 15 Question 16 Question 17 Question 18 Question 19 Question 20

PASSAGE 4

Question 21 Question 22 Question 23 Question 24 Question 25 Question 26 Question 27

SECTION 4 · lr

For statistics, there is debate between two pedagogical routes: teaching the understructure or the application. This is similar to the choice of teaching a driver how to build a car (understructure) or how to drive (application). Ordinary drivers don’t need to know understructure for their purpose.

The author is leading us towards the conclusion that, since most drivers don’t need building/understructure knowledge of cars, most statistics don’t need building/understructure knowledge of statistics.

This is anti-supported. The author is relying on the assumption that we can presume a driving student’s goal to be learning to drive/to be a driver, and that a statistic student’s goal is to learn the application of statistics/to be a statistician.

Unsupported. The author does not speak to anything that would support distinguishing statistics from mathematics.

Unsupported. Two issues:

There is no ranking of “likeliness to use X skill.” The author does make assumptions about what the students (driving and statistics) have as a learning goal, but we don’t have support (no matter how intuitive it might feel) to say that this is because they’re most likely to use that skill.
This breaks from the form of the comparison. The conclusion begins with “...just as ordinary drivers do not need...”, and so we can expect that the rest of the conclusion will speak to what statisticians do not need.

This matches our prediction. (D) finishes drawing the parallel between what driving students don’t need to learn and what statistic users don’t need to learn.

Unsupported. The author doesn’t talk about students becoming teachers, or what is/isn’t required for that.

Question

90% of people who answer get this correct

This is a low-difficulty question.

CURVE

Score of students with a 50% chance of getting this right

25% 120

131

75% 146

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Popularity Avg. score

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147

10%

157

90%

163

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PrepTest 154 - Section 1 - Question 8

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