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Measuring Water Hardness

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In an experiment for measuring water hardness in a water sample, using Atomic Absorption Spectrophotometry, I obtained a value of 173.74 ppm hardness for my water sample. Using EDTA determination, I obtained a value of 440 ppm hardness for my sample. In both these methods, I was measuring the hardness in relation specifically to Mg and Ca Ions.

Considering the fact that AA Spectrophotometry is a highly accurate method for measuring water hardness, I was wondering if there could be any possible explanations as to why the hardness for water obtained through EDTA determination is greatly larger than AA hardness. I recognize the fact human error is likely whilst carrying out an EDTA determination of a water sample.

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Actually there are a number of typical interference events for the EDTA water hardness test that are mentioned in the Standard Methods for Water Analysis used in Drinking Water certification by the EPA. These are also discussed in the SW846 guidance documents for RCRA analysis of ground water and soils. EDTA also picks up on K and Na in the hardness test as interferents and there are additives to suppress ...

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This solution is comprised of a detailed explanation which outlines possible interferents which may result when conducting water hardness tests. This is completed in 280 words.

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Calculations of Regression Analysis

See the attached file.
1. If Janice Position-Classification, personnel officer for the Bureau of Forms, can forecast agency separations 6 months from now, she can plan recruitment efforts to replace these people. Janice believes that separations 6 months from now are determined by the number of agency people passed over for promotion (X1), the number of agency people 64 years old or older (X2), and the ratio of government salaries to private sector salaries (X3). Using regression, Janice finds the following:

Y^ = 27.4 + .35X1 + .54X2 - 271X3
sb1 = .0031 sb2 = 0.136 sb3 = 263 Sy|x = 54
R2 = .89 Adj. R2 = .85 N = 214

Write a one-page memo explaining the results, and then forecast the number of separations if 418 people are passed over for promotion, 327 people are 64 years old or older, and government salaries equal those in the private sector.

2. The McKeesport Fire Department wants to know how likely it is that a truck pump will fail. The fire chief, George Pyro (no relation), thinks pump failure is a function of age (X1) and water hardness (X2 measured on a scale of 1 to 10). The department statistician runs a regression on a dummy variable (coded 1 for failure and 0 for no failure) for 217 pumps. She finds the following:

Y^ = .14 + .01X1 + .05X2
sb1 = .0002 sb2 = .025 Sy|x = .04 R2 = .93 Adj. R2 = .92

Write a memo explaining what the regression means. If the average water hardness is 3 and the chief would like to replace any pump with a probability of failing of .80 or more, at what age should pumps be replaced?

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