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Day 1 Competition

Authored by Victor Gu

Mathematics

Professional Development

CCSS covered

Used 4+ times

Day 1 Competition
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8 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 5 pts

What does DOE stand for?

Determination of Effects

Development of Experiments

Design of Experiments

Dynamic, Optimized Experiments

Tags

CCSS.HSS.IC.B.5

2.

MULTIPLE CHOICE QUESTION

45 sec • 10 pts

Which one of the following is NOT another name for the "factors" in an experiment?

Properties

Treatments

The Xs

Independent Variables

Tags

CCSS.HSS.IC.B.5

3.

MULTIPLE CHOICE QUESTION

45 sec • 10 pts

Which of the following is an example of a traditional null hypothesis?

There is some difference between the true mean change that occur for 2 binders.

True mean changes for binder A and binder B are equal.

Tags

CCSS.HSS.IC.B.5

4.

MULTIPLE CHOICE QUESTION

30 sec • 10 pts

If p-value < α, then one must ___ the null hypothesis.

accept

reject

5.

MULTIPLE CHOICE QUESTION

3 mins • 15 pts

Which of the following is NOT a benefit of replication?

provides the means to estimate the variance of the experimental error

demonstrates the results to be repeatable, at least under current experimental conditions

provides protection against lurking variables.

provides a degree of insurance against aberrant results in the experiment due to unforeseen accidents

6.

MULTIPLE CHOICE QUESTION

3 mins • 20 pts

Media Image

What can you conclude about the difference in the gas price between State A versus State B based on this T-Test?

Assume alpha level of 0.05.

Gas is more expensive in State A

Gas is more expensive in State B

There is no difference in gas prices between State A and B

Tags

CCSS.HSS.ID.A.4

CCSS.HSS.IC.A.1

CCSS.HSS.IC.B.4

CCSS.HSS.ID.A.2

CCSS.HSS.ID.A.3

7.

MULTIPLE SELECT QUESTION

1 min • 12 pts

What is the primary purpose of setting an alpha level (α) in hypothesis testing?

To determine the needed sample size for the study

To define the threshold for rejecting the null hypothesis

To limit the risk of a Type I error

To limit the risk of a Type II error

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