Nursing Elites

1. Which measure for the center of a small sample set would be most affected by outliers?

• A. Mean
• B. Median
• C. Mode
• D. None of the above

Correct answer: A

Rationale: The mean is calculated by summing all values in a dataset and then dividing by the total number of values. Outliers, which are data points significantly different from the other values, can greatly impact the mean because they affect the sum. The mean is sensitive to extreme values, making it the measure for the center of a small sample set most affected by outliers. The median, on the other hand, is not influenced by outliers as it represents the middle value when the data points are ordered. The mode is the value that appears most frequently in the dataset and is not directly influenced by outliers. Therefore, the correct answer is the mean, as it is highly influenced by outliers in a small sample set.

2. Which statement about the following set is true? {60, 5, 18, 20, 37, 37, 11, 90, 72}

• A. The median and the mean are equal.
• B. The mean is less than the mode.
• C. The mode is greater than the median.
• D. The median is less than the mean.

Correct answer: D

Rationale: To find the median, we first need to arrange the set in ascending order: {5, 11, 18, 20, 37, 37, 60, 72, 90}. The median is the middle value, which is 37 in this case. The mean is calculated by adding all numbers and dividing by the total count, which gives a mean greater than 37. Therefore, the statement that the median is less than the mean is correct. Choice A is incorrect because the median and mean are not equal in this set. Choice B is incorrect as the mean is greater than the mode in this set. Choice C is incorrect as the mode is 37, which is equal to the median, not greater.

3. When the sampling distribution of means is plotted, which of the following is true?

• A. The distribution is approximately normal.
• B. The distribution is positively skewed.
• C. The distribution is negatively skewed.
• D. There is no predictable shape to the distribution.

Correct answer: A

Rationale: When the sampling distribution of means is plotted, the distribution tends to be approximately normal, especially as the sample size increases. This phenomenon is described by the Central Limit Theorem, which states that the sampling distribution of the sample mean will be normally distributed regardless of the shape of the original population distribution as long as the sample size is sufficiently large. Choices B and C are incorrect because sampling distributions of means are not skewed. Choice D is incorrect because there is a predictable shape to the distribution, which is approximately normal.

4. What percentage of the total rainfall in this timeframe occurs during October?

• A. 0.135
• B. 0.151
• C. 0.169
• D. 0.177

Correct answer: B

Rationale: To calculate the percentage of rainfall that occurs during October, divide October's rainfall (4.5 inches) by the total rainfall (29.38 inches) and multiply by 100. So, (4.5 / 29.38) * 100 = 15.31%. Among the choices given, option B, 0.151, is the closest to this calculated percentage. Options A, C, and D are not correct as they do not match the accurate calculation based on the provided data.

5. In a graph that shows the number of nurses in various specialties, what is the independent variable?

• A. Anesthesia
• B. Geriatrics
• C. Nurse specialties
• D. Number of nurses

Correct answer: C

Rationale: The independent variable is the variable that is controlled or manipulated in an experiment or study. In this case, the independent variable is the nurse specialties because it is the factor that is being observed and measured to see how it affects the number of nurses in each specialty. The dependent variable, which changes in response to the independent variable, is the number of nurses. Choices A and B are specific nurse specialties and are actually part of the data being measured, not the independent variable itself. Choice D, 'Number of nurses,' is the dependent variable as it is the outcome that is being influenced by the independent variable, which is the nurse specialties.

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