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h2. Data Analysis

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h3. {toggle-cloak:id=Introduction} Introduction

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Data taken from
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h3. {toggle-cloak:id=Methods} Methods

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All data for tube flocculation is collected through Process Controller and saved in Excel spreadsheet. Both [Meta Data|Meta Data] in Excel and MathCad Data Processor are used to extract the sedimentation data from Excel spreadsheet and pick the range corresponded to the experimental settling state.

By extracting the data using Meta Data files, we were able to pick sets of settling data of interest and plot and analyze them individually or collectively to see any [trends|First Look into the Data]. We're proposing polynomial fit as an option to evaluate the data and [error analysis algorithm|Error Analysis] is utilized to see which equations fit each datasets the best.

[Another datasets example|Another example...] is also analyzed to determine which polynomial fit suits the best. From sum squared error analysis, the third and fourth degree of polynomial were found to be the best.[Another raw sedimentation data|Raw Data of Settling Column] was looked at different angle to get a better sense of parameters that actually effect the curve.

Data is [normalized|Data Normalization] and _Lineweaver-Burke_ data analysis was applied.

We were interested to find out how much the [data fluctuates|Data Fluctuation] during settling in a given experiment if repeated several times and how this might impact our results.

Data is [linearized|Data Linearization] using _double reciprocal_ analysis and the equations can be viewed [here|TubeFloc - Equations].
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h3. {toggle-cloak:id=Results} Results and Discussions

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# Data fluctuation shows that ...


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h2. {toggle-cloak:id=Progress} Progress

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