The Environmental Protection Agency (EPA) requires that cities monitor over 80 contaminants in their drinking water. Samples from the Lake Huron Water Treatment Plant gave the results shown here. All observations were below the allowable maximum, as shown by the reported range of contaminant levels. (presumably the mean would be the midrange).   Substance Range Detected Allowable Maximum Origin of Substance Chromium 0.45 to 0.61 100 Discharge from steel and pulp mills, natural erosion Barium 0.006 to 0.018 2 Discharge from drilling wastes, metal refineries, natural erosion Fluoride 1.04 to 1.14 4 Natural erosion, water additive, discharge from fertilizer and aluminum factories   For each substance, estimate the standard deviation σ by assuming uniform distribution and normal distribution shown in Table 8.8 in Section 8.7. (Round your answers to 4 decimal places.)

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The Environmental Protection Agency (EPA) requires that cities monitor over 80 contaminants in their drinking water. Samples from the Lake Huron Water Treatment Plant gave the results shown here. All observations were below the allowable maximum, as shown by the reported range of contaminant levels. (presumably the mean would be the midrange).
 

Substance Range Detected Allowable Maximum Origin of Substance
Chromium 0.45 to 0.61 100 Discharge from steel and pulp mills, natural erosion
Barium 0.006 to 0.018 2 Discharge from drilling wastes, metal refineries, natural erosion
Fluoride 1.04 to 1.14 4 Natural erosion, water additive, discharge from fertilizer and aluminum factories

 
For each substance, estimate the standard deviation σ by assuming uniform distribution and normal distribution shown in Table 8.8 in Section 8.7. (Round your answers to 4 decimal places.)

Table 8.8
Four Ways to Estimate o
Method 1: Take a Preliminary Sample
Take a small preliminary sample and use the sample estimate s in place of o. This method is common, though its
logic is somewhat circular (i.e., we must take a sample to plan a sample).
Method 2: Assume Uniform Population
)2/12]/2. For example, we might guess the weight of a
Estimate upper and lower limits a and b and set o = [(b – a
light-duty truck to range from 1,500 pounds to 3,500 pounds, implying a standard deviation of o = [(3,500 –
1,500)?/12]1/2.
smaller than our guess, so we get a larger n than necessary (a conservative result).
= 577 pounds. Because a uniform distribution has no central tendency, the actual o is probably
Method 3: Assume Normal Population
Estimate upper and lower bounds a and b, and set o = (b – a)/6. This assumes normality with most of the data
within u + 30 and u – 30, so the estimated range is 60. For example, we might guess the weight of a light truck to
range from 1,500 pounds to 3,500 pounds, implying o = (3,500 – 1,500)/6 = 333 pounds. Recent research suggests
that this method may not be conservative enough (see Related Reading).
Method 4: Poisson Arrivals
In the special case when 2 is a Poisson arrival rate, then o = Va. For example, if you think the arrival rate is about 20
customers per hour, then you would estimate o = V20 = 4.47.
Transcribed Image Text:Table 8.8 Four Ways to Estimate o Method 1: Take a Preliminary Sample Take a small preliminary sample and use the sample estimate s in place of o. This method is common, though its logic is somewhat circular (i.e., we must take a sample to plan a sample). Method 2: Assume Uniform Population )2/12]/2. For example, we might guess the weight of a Estimate upper and lower limits a and b and set o = [(b – a light-duty truck to range from 1,500 pounds to 3,500 pounds, implying a standard deviation of o = [(3,500 – 1,500)?/12]1/2. smaller than our guess, so we get a larger n than necessary (a conservative result). = 577 pounds. Because a uniform distribution has no central tendency, the actual o is probably Method 3: Assume Normal Population Estimate upper and lower bounds a and b, and set o = (b – a)/6. This assumes normality with most of the data within u + 30 and u – 30, so the estimated range is 60. For example, we might guess the weight of a light truck to range from 1,500 pounds to 3,500 pounds, implying o = (3,500 – 1,500)/6 = 333 pounds. Recent research suggests that this method may not be conservative enough (see Related Reading). Method 4: Poisson Arrivals In the special case when 2 is a Poisson arrival rate, then o = Va. For example, if you think the arrival rate is about 20 customers per hour, then you would estimate o = V20 = 4.47.
Uniform Distribution
Normal Distribution
Chromium
Barium
Fluoride
Transcribed Image Text:Uniform Distribution Normal Distribution Chromium Barium Fluoride
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