Assume that females have pulse rates that are normally distributed with a mean of u = 72.0 beats per minute and a standard deviation of o = 12.5 beats per minute. Complete parts (a) through (c) below.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
icon
Related questions
Topic Video
Question
**Understanding Normal Distribution of Female Pulse Rates**

Assume that females have pulse rates that are normally distributed with a mean (\( \mu \)) of 72.0 beats per minute and a standard deviation (\( \sigma \)) of 12.5 beats per minute. Let's explore the following scenarios:

### Part (a)
**Scenario:**
If 1 adult female is randomly selected, find the probability that her pulse rate is between 65 beats per minute and 79 beats per minute.

**Solution:**
The probability is \( \mathbf{0.4246} \).

*(Round to four decimal places as needed.)*

### Part (b)
**Scenario:**
If 16 adult females are randomly selected, find the probability that they have pulse rates with a mean between 65 beats per minute and 79 beats per minute.

**Solution:**
The probability is \( \mathbf{0.9750} \).

*(Round to four decimal places as needed.)*

### Part (c)
**Question:**
Why can the normal distribution be used in part (b), even though the sample size does not exceed 30?

**Answer Choices:**
- **A.** Since the original population has a normal distribution, the distribution of sample means is a normal distribution for any sample size.
- **B.** Since the distribution is of sample means, not individuals, the distribution is a normal distribution for any sample size.
- **C.** Since the distribution is of individuals, not sample means, the distribution is a normal distribution for any sample size.
- **D.** Since the mean pulse rate exceeds 30, the distribution of sample means is a normal distribution for any sample size.

**Correct Answer:**
- **A.** Since the original population has a normal distribution, the distribution of sample means is a normal distribution for any sample size.

This principle is rooted in the Central Limit Theorem, which states that if the population from which a sample is drawn is normally distributed, then the sampling distribution of the sample mean will also be normally distributed, regardless of the sample size.
Transcribed Image Text:**Understanding Normal Distribution of Female Pulse Rates** Assume that females have pulse rates that are normally distributed with a mean (\( \mu \)) of 72.0 beats per minute and a standard deviation (\( \sigma \)) of 12.5 beats per minute. Let's explore the following scenarios: ### Part (a) **Scenario:** If 1 adult female is randomly selected, find the probability that her pulse rate is between 65 beats per minute and 79 beats per minute. **Solution:** The probability is \( \mathbf{0.4246} \). *(Round to four decimal places as needed.)* ### Part (b) **Scenario:** If 16 adult females are randomly selected, find the probability that they have pulse rates with a mean between 65 beats per minute and 79 beats per minute. **Solution:** The probability is \( \mathbf{0.9750} \). *(Round to four decimal places as needed.)* ### Part (c) **Question:** Why can the normal distribution be used in part (b), even though the sample size does not exceed 30? **Answer Choices:** - **A.** Since the original population has a normal distribution, the distribution of sample means is a normal distribution for any sample size. - **B.** Since the distribution is of sample means, not individuals, the distribution is a normal distribution for any sample size. - **C.** Since the distribution is of individuals, not sample means, the distribution is a normal distribution for any sample size. - **D.** Since the mean pulse rate exceeds 30, the distribution of sample means is a normal distribution for any sample size. **Correct Answer:** - **A.** Since the original population has a normal distribution, the distribution of sample means is a normal distribution for any sample size. This principle is rooted in the Central Limit Theorem, which states that if the population from which a sample is drawn is normally distributed, then the sampling distribution of the sample mean will also be normally distributed, regardless of the sample size.
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 3 steps with 2 images

Blurred answer
Knowledge Booster
Hypothesis Tests and Confidence Intervals for Means
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.
Similar questions
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman