Abstract

Public water supplies contain disease-causing microorganisms in the water or distribution ducts. In order to kill off these pathogens, a disinfectant, such as chlorine, is added to the water. Chlorine is the most widely used disinfectant in all U.S. water treatment facilities. Chlorine is known to be one of the most powerful disinfectants to restrict harmful pathogens from reaching the consumer. In the interest of obtaining a better understanding of what variables affect the levels of chlorine in the water, this thesis will analyze a particular set of water samples randomly collected from locations in Orange County, Florida. Thirty water samples will be collected and have their chlorine level, temperature, and pH recorded. A linear regression analysis will be performed on the data collected with several qualitative and quantitative variables. Water storage time, temperature, time of day, location, pH, and dissolved oxygen level will be the independent variables collected from each water sample. All data collected will be analyzed through various Statistical Analysis System (SAS®) procedures. Partial residual plots will be used to determine possible relationships between the chlorine level and the independent variables and stepwise selection to eliminate possible insignificant predictors. From there, several possible models for the data will be selected. F tests will be conducted to determine which of the models appears to be the most useful. All tests will include hypotheses, test statistics, p values, and conclusions. There will also be an analysis of the residual plot, jackknife residuals, leverage values, Cook’s D, press statistic, and normal probability plot of the residuals. Possible outliers will be investigated and the critical values for flagged observations will be stated along with what problems the flagged values indicate.

Notes

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Thesis Completion

2015

Semester

Fall

Advisor

Ni, Liqiang

Degree

Bachelor of Science (B.S.)

College

College of Sciences

Department

Statistics

Degree Program

Statistics

Subjects

Dissertations, Academic -- Sciences; Sciences -- Dissertations, Academic

Format

PDF

Identifier

CFH0004907

Language

English

Access Status

Open Access

Length of Campus-only Access

None

Document Type

Honors in the Major Thesis

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