Instructions
Tables and Graphs
If new Tables and Graphs are required, follow these standards:
Tables
Black and white. Number and title above the table. Use the proper metric units and use the “significant figures” to reflect the accuracy of the measuring device, or error propagation affecting the calculated parameter.
Graphs
· Black and white. Colors should be used only to differentiate more than one plot in one graph.
· Place the number and title below the graph.
· Select the type of graph best suited for the variables. Use a scatter plot (not a line graph) for continuous variables. Typically, the independent variable (IV) is represented on the horizontal (x) axis and the dependent variable (DV) on the vertical (y) axis. Choose good scales for each axis to include all the DV and IV values. If applicable, draw a trend line or other fitting function; in these cases, show the linear trend and the R2 values.
· Experimental points must be displayed with distinct markers and should not be joined by “lines.” Lines are only appropriate if they are trend lines or fitting functions.
· For discrete variables, may use a bar or column graph.
Calculations
· Complete all remaining calculations (dimensional analysis should be explicit).
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 of Experimental Results
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.
Literature Cited
Use in-text citation and list here references in alphabetical order.
The file cannot upload, I will sent via email