Question 1

How do statisticians define precision?&#10;A) The extent to which the same results would be obtained if another random sample were drawn from the same population&#10;B) A sample which shows least sampling error&#10;C) A large sample size that yields more accuracy of results&#10;D) The extent to which sampling errors can be evaluated with inferential statistics

Accepted Answer

Precision in statistics refers to the consistency of repeated measurements or observations. If another random sample were drawn from the same population and the results were similar, the measurement is considered precise.

Question 2

How does a researcher increase precision?&#10;A) By decreasing the sample size&#10;B) By using a random sampling method&#10;C) By increasing the sample size&#10;D) By using an unbiased sampling method

Accepted Answer

Increasing the sample size generally leads to higher precision in research findings because it reduces the margin of error and makes the results more representative of the entire population.

Question 3

Which of the two studies shows diminished returns in terms of increasing precision?&#10;A) By adding 20 individuals to a sample of 500&#10;B) By adding 20 individuals to a sample of 1,000

Accepted Answer

Adding 20 individuals to a larger sample size (1,000) shows diminished returns in increasing precision compared to adding the same number to a smaller sample (500), because the relative increase in sample size is smaller, thus having a lesser impact on reducing the margin of error.

Question 4

When a small difference is anticipated, a smaller sample size should be used.

Accepted Answer

A larger sample size is needed to detect a small difference with statistical significance, as it reduces the margin of error and increases the power of the test.

Question 5

When a large variation of answers is expected, the research should use the following:&#10;A) A large sample&#10;B) A small sample

Accepted Answer

A large sample is used to capture the diversity and variation in responses, ensuring that the results are representative and reliable.

Question 6

only large samples can identify large group differences.

Accepted Answer

Even small samples can identify large group differences if the differences are substantial enough; the key factor is the effect size, not just the sample size.

Question 7

For a population with very limited variability, which of the following is true?&#10;A) Only a large sample size can yield precise results&#10;B) A small sample size can yield precise results

Accepted Answer

In a population with very limited variability, even a small sample size can yield precise results because the lack of variability means that most individuals in the population are similar to each other. Therefore, even a small sample is likely to be representative of the population.

Question 8

using a large sample corrects for sampling bias.

Accepted Answer

Using a large sample size can reduce the impact of random sampling error, making the sample mean a more accurate estimate of the population mean, but it does not inherently correct for sampling bias. Sampling bias occurs when certain members of the population are systematically more likely to be selected in the sample than others, and increasing the sample size does not address the root cause of this issue.

Question 9

If a rare phenomenon is expected, one should use&#10;A) A small sample&#10;B) A large sample

Accepted Answer

A large sample is needed to increase the likelihood of observing rare events and to ensure the results are statistically significant.

Deck 7: Sample Size