Suppose a random sample of data is taken, sample size n = 200, with sample mean 100 and sample standard deviation is 10. ) Calculate the following, giving your answer in interval notation. For example, 3±2 in interval form would be (1,5) because 3-2=1 and 3+2 =5. nterval 1: š ±s nterval 2: š ± 2s nterval 3: š ± 3s

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**Transcription and Explanation for Educational Use**

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**Problem Statement 2:**

Suppose a random sample of data is taken, sample size \( n = 200 \), with sample mean 100 and sample standard deviation is 10.

**a) Calculate the following, giving your answer in interval notation.**

*For example, \(3 \pm 2\) in interval form would be \((1,5)\) because \(3-2=1\) and \(3+2=5\).*

- **Interval 1:** \(\bar{x} \pm s\)
- **Interval 2:** \(\bar{x} \pm 2s\)
- **Interval 3:** \(\bar{x} \pm 3s\)

**Chebychev's Rule**

**b) Using Chebychev's Inequality**

- **AT LEAST** what percentage of data should we expect to be within interval 2?

- **AT LEAST** what percentage of data should we expect to be within interval 3? Show your work by using the formula.

**Empirical Rule**

**c) Suppose that the data are sampled from a normally distributed population. Using the empirical rule, what percentage of the data should we expect to be within interval one?**

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**Explanation:**

1. **Interval Calculations:**
   - Interval 1 represents the range within one standard deviation from the mean.
   - Interval 2 represents the range within two standard deviations from the mean.
   - Interval 3 represents the range within three standard deviations from the mean.

2. **Chebychev's Rule:**
   - This rule provides a minimum percentage of observations that fall within a given number of standard deviations from the mean, applicable to any distribution.
   - The formula for Chebychev's Inequality is: \( 1 - \frac{1}{k^2} \)

3. **Empirical Rule:**
   - Applicable for normally distributed data, this rule states:
     - Approximately 68% of data lies within one standard deviation.
     - Approximately 95% lies within two standard deviations.
     - Approximately 99.7% lies within three standard deviations.

This question requires students to apply statistical concepts, such as interval notation, Chebychev's Inequality, and the Empirical Rule, to estimate data distribution in a sample set.
Transcribed Image Text:**Transcription and Explanation for Educational Use** --- **Problem Statement 2:** Suppose a random sample of data is taken, sample size \( n = 200 \), with sample mean 100 and sample standard deviation is 10. **a) Calculate the following, giving your answer in interval notation.** *For example, \(3 \pm 2\) in interval form would be \((1,5)\) because \(3-2=1\) and \(3+2=5\).* - **Interval 1:** \(\bar{x} \pm s\) - **Interval 2:** \(\bar{x} \pm 2s\) - **Interval 3:** \(\bar{x} \pm 3s\) **Chebychev's Rule** **b) Using Chebychev's Inequality** - **AT LEAST** what percentage of data should we expect to be within interval 2? - **AT LEAST** what percentage of data should we expect to be within interval 3? Show your work by using the formula. **Empirical Rule** **c) Suppose that the data are sampled from a normally distributed population. Using the empirical rule, what percentage of the data should we expect to be within interval one?** --- **Explanation:** 1. **Interval Calculations:** - Interval 1 represents the range within one standard deviation from the mean. - Interval 2 represents the range within two standard deviations from the mean. - Interval 3 represents the range within three standard deviations from the mean. 2. **Chebychev's Rule:** - This rule provides a minimum percentage of observations that fall within a given number of standard deviations from the mean, applicable to any distribution. - The formula for Chebychev's Inequality is: \( 1 - \frac{1}{k^2} \) 3. **Empirical Rule:** - Applicable for normally distributed data, this rule states: - Approximately 68% of data lies within one standard deviation. - Approximately 95% lies within two standard deviations. - Approximately 99.7% lies within three standard deviations. This question requires students to apply statistical concepts, such as interval notation, Chebychev's Inequality, and the Empirical Rule, to estimate data distribution in a sample set.
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