4.2+Making+Sense+of+Data

= **Congratulations!** = You have acquired actual data that you can analyze. [|Time to celebrate!] (<== Click this link before reading on...). The next phase of your work begins.

It is important to determine what your results indicate, if anything. Hopefully, your study has been designed appropriately so that your hypotheses can be tested. Also important is that all the data you need to test your hypotheses were collected (there were no broken samples or “holes” in the data set). This “hole” refers to your need for data, but someone or something (online monitoring device) did not collect that data. “Holes” in a dataset are very problematic and will be discussed later.

To answer questions about the phenomena controlling environmental and water resources engineering processes, it is necessary to calculate basic statistics (mean and standard deviation values), create tables, and figures. For example, you might be interested in whether or not individual water purifier devices change water pH or if a total organic carbon concentration of a river changes due to localized rainfall. Using the correct data you can test that question. The attached file explains how to determine basic statistics and develop testable hypotheses. __ NOTE: When you analyze your data, you typically create MANY more tables and figures during this process than you would actually report in the final communication (e.g., report, email, presentation, journal manuscript). This is normal. You should identify which Tables and Figures BEST describe your results. __

This is VERY common. You must determine what questions to ask and which data to summarize and compare. From your analyses, you can identify general trends in the data and possibly identify reoccurring phenomena (e.g., instrument/analytical variability, missing or unusual results, unequal or inadequate sample sizes). Once you calculate basic statistics, you can then select which advanced statistics such as Analysis of Variance (ANOVA) (to determine if all groups are equal) and multiple comparison tests (to determine which group is different) you should apply to mathematically test your hypotheses. More discussion of what basic statistics you should determine and how to construct testable hypotheses can be found in the attached file.

GUIDANCE: Analyzing and Interpreting Environmental Monitoring Data
Key concepts: Statistically significant difference Type I error Mean Standard deviation Variance Coefficient of variation Analysis of Variance (ANOVA) test Multiple comparison test

GUIDANCE: Conducting a Multiple Comparison Test
Multiple comparison tests will need to be conducted for FASTCE water quality data for students to describe differences between monitoring results. Multiple comparison tests cannot be conducted using MS Excel. Other statistical programs must be used (e.g., SPSS, NCSS, SAS, etc.). Students are responsible for contacting Dr. Whelton ASAP if they do not have access to one of the computer programs listed above. (Posted Oct 19, 2011)