Understanding Margin of Error and Data Quality

Understanding Margin of Error and Data Quality

Assessment

Interactive Video

Mathematics

9th - 10th Grade

Hard

Created by

Thomas White

FREE Resource

The video tutorial explains the concept of margin of error, its importance, and how it is used to estimate values within a range. It covers factors affecting margin of error, such as sample size and data quality, and introduces the concept of confidence intervals. The tutorial includes practice problems to reinforce understanding.

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13 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the initial average height of the selected students in the example?

175 cm

165 cm

170 cm

160 cm

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why might the real average height differ from the initial estimate?

Because the measurement tools are faulty

Due to the presence of very tall and very short students

Because the sample size is too large

Due to incorrect data entry

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How do you calculate the lower bound of the average height using margin of error?

Add the margin of error to the estimate

Subtract the margin of error from the estimate

Multiply the margin of error by the estimate

Divide the margin of error by the estimate

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the range of reasonable values for the average height in the example?

160 to 170 cm

165 to 175 cm

155 to 165 cm

150 to 160 cm

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which factor does NOT affect the margin of error?

Quality of data

Time of data collection

Sample size

Type of data collected

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What happens to the margin of error when the sample size increases?

It becomes unpredictable

It increases

It decreases

It remains the same

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why is the quality of data important in determining margin of error?

It ensures the data is collected quickly

It reduces the likelihood of errors in estimation

It makes data collection more expensive

It increases the sample size

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