Let x be a random variable that represents the concentration of iron in water. The EPA specifies that x has a normal distribution with o = 0.7. The company claims that the iron concentration population mean is u = 2.0 downstream from the plant. But 10 samples taken downstream from an industrial | plant show an X = 2.48. а. Does this sample indicate a µ higher than that the company claims? (a = 1%) %3D b. Find a 95% confidence interval for u generated from the sample data.

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### Statistical Analysis of Iron Concentration in Water

#### Problem Statement
Let \( X \) be a random variable that represents the concentration of iron in water. The EPA specifies that \( X \) has a normal distribution with \( \sigma = 0.9 \). The company claims that the iron concentration population mean is \( \mu = 2.0 \) downstream from the plant. But 10 samples taken downstream from an industrial plant show an \( \bar{X} = 2.48 \).

#### Questions
a. Does this sample indicate a \( \mu \) higher than that the company claims? (α = 1%)

b. Find a 95% confidence interval for \( \mu \) generated from the sample data.

#### Analysis
1. **Hypothesis Testing for a Higher Mean Concentration**
   - Null Hypothesis (\( H_0 \)): \( \mu = 2.0 \)
   - Alternative Hypothesis (\( H_1 \)): \( \mu > 2.0 \)
   - Significance Level (\( \alpha \)): 1%

2. **Calculation for Confidence Interval**
   - The 95% confidence interval will be calculated using the sample mean \( \bar{X} \), standard deviation \( \sigma \), and the number of samples \( n = 10 \).

3. **Interpretations**
   - Results of the hypothesis test will determine if there is statistically significant evidence to believe that the iron concentration is higher than what the company claims.
   - The confidence interval will give a range within which the true population mean \( \mu \) is expected to lie with 95% certainty.

This problem involves conducting a one-tailed hypothesis test and calculating the confidence interval for the population mean based on sample data. It teaches the application of statistical inference methods in environmental quality control.
Transcribed Image Text:### Statistical Analysis of Iron Concentration in Water #### Problem Statement Let \( X \) be a random variable that represents the concentration of iron in water. The EPA specifies that \( X \) has a normal distribution with \( \sigma = 0.9 \). The company claims that the iron concentration population mean is \( \mu = 2.0 \) downstream from the plant. But 10 samples taken downstream from an industrial plant show an \( \bar{X} = 2.48 \). #### Questions a. Does this sample indicate a \( \mu \) higher than that the company claims? (α = 1%) b. Find a 95% confidence interval for \( \mu \) generated from the sample data. #### Analysis 1. **Hypothesis Testing for a Higher Mean Concentration** - Null Hypothesis (\( H_0 \)): \( \mu = 2.0 \) - Alternative Hypothesis (\( H_1 \)): \( \mu > 2.0 \) - Significance Level (\( \alpha \)): 1% 2. **Calculation for Confidence Interval** - The 95% confidence interval will be calculated using the sample mean \( \bar{X} \), standard deviation \( \sigma \), and the number of samples \( n = 10 \). 3. **Interpretations** - Results of the hypothesis test will determine if there is statistically significant evidence to believe that the iron concentration is higher than what the company claims. - The confidence interval will give a range within which the true population mean \( \mu \) is expected to lie with 95% certainty. This problem involves conducting a one-tailed hypothesis test and calculating the confidence interval for the population mean based on sample data. It teaches the application of statistical inference methods in environmental quality control.
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