Statistics and Uncertainty

Manual pages 6 to 10: For all reports include the uncertainty analysis: intrinsic or estimated uncertainty of one measurement, and propagation of the uncertainty (Error Propagation).

Include any of the following quantitative measures as applicable in each experiment:

Manual pages 4 to 5: Average, Standard Deviation, Difference (or Absolute Difference or Relative Percent Difference), Coefficient of Variation.

Linear Regression Coefficient (R2)

Analysis and Interpretation:

  • Compare measured parameters values to guidelines or reference values (Content and and references linked in Instructors PPT)
  • Creatively (non-speculative) discuss the measurements (T, RH%, CO2, CO, PM, NO2, HCHO, VOCs) as a function of location.
  • How do you interpret the uncertainty specified for each of the two instruments
  • What are the main points that your group learned from the results?
  • Based on what you learned, suggest one specific experiment that would further knowledge or understanding of the mini-study.
  • More Information:-
  • In this report section, students show their understanding of the connection between the results and the applicable theory. Bring together theory and how it is applied or helps to extract meaning from the experiments’ results.· Categorize the experimental variables demonstrating the level of understanding of the experiment.· Describe the observed relationships, trends, or patterns in the results, referencing them directly.· Explain observations using the applicable theory and explicit logical reasoning statements.· Analyze possible sources of errors or uncertainty and their significance. Classify the type of error (Manual page 5).· Compare experimental results to published data or parameters whenever possible. The information to do this is posted on Canvas.What are logical reasoning statements?Practice using the two main types of logic reasoning; deductive and inductive. For the latter, describe the observed trends and associations to determine the pattern or broad concept. For example, were the primary independent and dependent variables directly or inversely associated? What can be inferred from this association? Is this inference correct? Deductive reasoning is more direct, starting with the accepted theory (premises). The applicable theory is invoked directly to explain the results. In this case, formulate a reasonable hypothesis based on the experiment and explain how the results support or reject your hypothesis.What does it mean to analyze sources of errors or uncertainty?Use specific examples from the data and results. A generic listing of “sources of error” is meaningless. Examine the process and identify at least one or two specific and relevant sources of error or uncertainty and explain how each could have affected the results. Which deviations from the given procedure (or which source of error) have a more significant impact on the experimental results? Which ones probably not? How do you know this?

    In the last paragraph of this section, if applicable, report the final results with an uncertainty margin. Significant findings which were analyzed or evaluated are summarized and written as conclusions.

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