In the US, the systolic blood pressure of a randomly selected patient is normally distributed with a mean of 116 mmHg and a standard deviation of 15.5 mmHg. Let X be the systolic blood pressure of a randomly selected patient and let X be the average systolic blood pressure of a random sample of size 22. 1. Describe the probability distribution of X and state its parameters μ and o: X~ Select an answer ( and find the probability that the systolic blood pressure of a randomly selected patient is more than 121.9 mmHg. 2. Use the Central Limit Theorem Select an answer (Round the answer to 4 decimal places) to describe the probability distribution of X and state its parameters x and ox: (Round the answers to 1 decimal place) X~ Select an answer (Hx and find the probability that the average systolic blood pressure of a sample of 22 randomly selected patients is between 117.4 and 121.5 mmHg. (Round the answer to 4 decimal places) σχ

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**Understanding Probability Distributions and the Central Limit Theorem**

In the United States, the systolic blood pressure of a randomly selected patient follows a normal distribution with a mean (µ) of 116 mmHg and a standard deviation (σ) of 15.5 mmHg. Let \( X \) represent the systolic blood pressure of a randomly selected patient, and let \( \overline{X} \) represent the average systolic blood pressure of a random sample of size 22.

1. **Probability Distribution of \( X \)**

   - Describe the probability distribution of \( X \) and specify its parameters \( \mu \) and \( \sigma \):  
     \( X \sim N(\mu = 116, \sigma = 15.5) \)

   - Calculate the probability that the systolic blood pressure of a randomly selected patient is more than 121.9 mmHg.  
     (Round the answer to 4 decimal places)

2. **Using the Central Limit Theorem**

   - Apply the Central Limit Theorem to describe the probability distribution of \( \overline{X} \) and specify its parameters \( \mu_{\overline{X}} \) and \( \sigma_{\overline{X}} \):  
     \( \overline{X} \sim N(\mu_{\overline{X}} = 116, \sigma_{\overline{X}} = 3.306) \)

   - Calculate the probability that the average systolic blood pressure of a sample of 22 randomly selected patients is between 117.4 and 121.5 mmHg.  
     (Round the answer to 4 decimal places)

In this module, students will learn how to determine and describe probability distributions, as well as apply the Central Limit Theorem to understand sample means. Students will also practice calculating probabilities associated with these distributions.
Transcribed Image Text:**Understanding Probability Distributions and the Central Limit Theorem** In the United States, the systolic blood pressure of a randomly selected patient follows a normal distribution with a mean (µ) of 116 mmHg and a standard deviation (σ) of 15.5 mmHg. Let \( X \) represent the systolic blood pressure of a randomly selected patient, and let \( \overline{X} \) represent the average systolic blood pressure of a random sample of size 22. 1. **Probability Distribution of \( X \)** - Describe the probability distribution of \( X \) and specify its parameters \( \mu \) and \( \sigma \): \( X \sim N(\mu = 116, \sigma = 15.5) \) - Calculate the probability that the systolic blood pressure of a randomly selected patient is more than 121.9 mmHg. (Round the answer to 4 decimal places) 2. **Using the Central Limit Theorem** - Apply the Central Limit Theorem to describe the probability distribution of \( \overline{X} \) and specify its parameters \( \mu_{\overline{X}} \) and \( \sigma_{\overline{X}} \): \( \overline{X} \sim N(\mu_{\overline{X}} = 116, \sigma_{\overline{X}} = 3.306) \) - Calculate the probability that the average systolic blood pressure of a sample of 22 randomly selected patients is between 117.4 and 121.5 mmHg. (Round the answer to 4 decimal places) In this module, students will learn how to determine and describe probability distributions, as well as apply the Central Limit Theorem to understand sample means. Students will also practice calculating probabilities associated with these distributions.
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