Masses and Springs
No plagiarism. 1. Introduction: The aim of this assignment is to demonstrate that you are able to study and analyse a physical phenomenon by practical application of the concepts involved and then draw your own conclusions based upon your own experimental data. In particular, carrying out a virtual laboratory experiment using an online Colorado university Phet simulation of an experiment which is relevant to the module syllabus such as Masses and Springs whose url is: https://phet.colorado.edu/sims/html/masses-and-springs/latest/masses-and- springs_en.html 2. Learning Outcomes: This assignment assesses your ability to: demonstrate practical skills following a method and/or adapting the method to improve accuracy; your ability to introduce and explain the context of the topic; accurately record and analyse your own data; draw conclusions and evaluate your findings using scientific arguments. 3. Task/Aim In the case of the masses and spring oscillations experiment, a good example of an Aim would be as follows: To investigate the relationship between the mass and time period of oscillation and to determine a value for the spring constant with uncertainty using algebraic and graphical techniques. 4. Suggested format: Spacing Font Alignment Margins Header and footer single-spaced or 1.5 line spacing Arial font size 11 or 12 Left justified 2.5 cm top and bottom, 2.5 cm left and right Include page number Introduction (5) Carefully researched and referenced account of the theory (including any relevant formulae) and surrounding topics. The theory should include an explanation of all relevant formulae and how you will use them. Why it is worth doing, interesting or relevant to carry out this experiment. Clearly and correctly explained idea of experiment. (Up to one page.) 3. Method (5) Not copied from method sheet, this should be a step by step list of what you did…. What was done precisely, what quantities were measured and how: what instrument did you use to measure each variable? Explain what you did to improve the accuracy of the measurements. Diagram of the experimental set-up: diagram correctly labelled or an equipment list added. How will you use the graph to find the value or values, such as spring constant, k? Show the rearranging you need to do so that the equation matches y = mx + c (or y = mx in cases that c = 0). (Some of this can be done in the analysis section.) Risk assessment: what procedures were undertaken to minimise risks/hazards? 5. Results (5) No made up results; Correct column headings with units; Columns with sensible uncertainties and the calculations of these uncertainties written out in full. Systematic and random sources of error identified (here or in the evaluation). Any additional measurements (such as original length or diameter). 6. Graph to show….. (5) Sensibly chosen scale on each axis. Best fit line fills an A4 page as far as possible and preferably portrait. No forcing through the origin or other mistakes. Large triangle drawn for calculation of gradient. Line of best drawn correctly. Points identified with crosses not blobs or circles. Any anomalies are circled and not included in the line of best fit. Both axes labelled with units. Graph has a sensible title. 7. Analysis of graph and results (5) Comment on graph shape/correlation (for example, straight line or curved, through origin or not, directly proportional or not). Gradient found using a large triangle. Large triangle shown clearly on the graph. Equation rearranged to show how to find the values (e.g. k) indirectly from the gradient. Calculations of percentage uncertainties and combining percentage uncertainties. Calculation of final absolute uncertainty (e.g. for k). 8. Conclusion (5) Answer (e.g. for k) calculated from gradient and above rearranging. Answer (e.g. the spring constant k) has correct unit. Answer (e.g. for k) is stated together with a properly calculated absolute uncertainty. i.e. main result = (……. ……) unit. Compare your result to the theoretically expected result. Does the expected value lie within the error bounds of your result? Why or why not? i.e. what in your opinion is the main source of error? 9. Evaluation (5) What went well with the practical and what didnt go so well, referring to results table and/or graph. For example, if the line of best fit didnt want to go through the origin, what type of error might have led to that? List of systematic and random errors are identified (can be written here or in the results section) List of strategies that were implemented to improve the accuracy of the results are justified. List of strategies that could be used in future to improve the accuracy of the results are explained. Justified explanation of how the method or the choice of equipment could be improved. (About half a page.) 10. Bibliography (its essential to credit all sources) (5) Harvard referencing used. References properly cited as , ,… in the introduction and discussion, adjacent to the text in which you used information from the reference.