IB PHYSICS INTERNAL ASSESSMENT COVER Lab Title: Candidate: Exam Year: 2014 Partners Name(s): Instructor: William Wofford Date handed in: Levels Levels available: c = complete; p = partial; n = not at all c (2) p (1) n (0) Total Grade (/6) DESIGN  Identifies a focused problem/research question and identifies the relevant variables and assumptions Clear, focused and all variables identified Unclear /incomplete question and missing variable(s) No question, improper variables, no variables  Designs and explains a method for the effective control and/or monitoring of each of the variables Clear explanation of how and why Incomplete explanation, lack of control of some Not controlling several variables, no regard for monitoring  Provides details on the relevant data to be collected (how, when, why) and the equations that will be used Explains clearly the how, when, why and quantity Insufficient data collected, unclear how, why, when Method does not lead to appropriate or sufficient data  Records appropriate quantitative and associated qualitative raw data, including units & uncertainties All data, all units, all uncertainties and qualitative Small omission or error in quantitative or qualitative aspect Disregard for the stated objectives  Processes quantitative raw data correctly (math calculations and graph plotting and relationships) Correct processing Minor errors in processing or minor omissions Major errors in processing or no processing  Presents processed data appropriately and clearly with errors and uncertainties where relevant Presentation is easy to follow, appropriate Presentation has omissions or is lacking clarity/flow Inappropriate or incomprehensible  States a valid conclusion that includes comparison to literature values and systematic and random error. All present and solid connections to DCP and error Lacking key connections to DCP and/or error No connection made to DCP and /or error  Identifies and evaluates weaknesses & limitations in the procedure, methods and equipment Direct, correct and appropriate evaluation Evaluation is weak, incorrect or lacking key aspects Irrelevant aspects identified or not present  Suggests “realistic” improvements to procedure, method, equipment or calculations A realistic and broad scope of improvements Weak, superficial, few or irrelevant improvements listed Unrealistic or no improvements suggested After reviewing your lab, I have identified the following problem areas: o Research question o Variable identification o Variable control o Producing relevant data o Quantitative data collection (see comments) o Qualitative data collection o Uncertainty values/sig figs o Explanation of calculations o Calculation missing or errors o Presentation of data o Presentation of calculations o Graph presentation o Graph relationship o Interpretation of data o Other (see comments) o Valid conclusion o Evaluation of procedure and methods o Realistic improvements General Comments from instructor: DATA COLLECTION AND PROCESSING CONCLUSION & EVALUATION Authenticity: I confirm this assignment is my own and that I have honored the IB code of conduct and its’ stated integrity standards. Student signature: [Insert title of investigation] I. Design Research Question: Define the problem using a focused research question and identify the relevant variables. Example research questions are given below. Research Question: Is the acceleration of a cart down an inclined plane constant? The aim of the experiment is to investigate the total weight of a bicycle relates to the stopping distance .. The research question is "How does the mass of a parachute affect the amount of time it takes to fall? " Identify experimental variables. Variables must be explicitly identified as dependent (measured), independent (manipulated), or controlled variables (constants). Relevant variables are those that can reasonably be expected to affect the outcome. For example, in the investigation of the bouncing ball, the drop height would be the independent variable and the rebound height would be the dependent variable. Controlled variables would include using the same ball and the same surface for all measurements. Materials, Methods, and Uncertainties Experimental apparatus. Describe the experimental apparatus and list the materials that you used. A sketch of the apparatus may be helpful. Use of data logging software such as DataStudio or LoggerPro should be noted in the description along with the version number. Experimental procedure. The procedure should explicitly reference how you controlled the variables identified in your research question. "Control of variables" refers to the manipulation of the independent variable, measurement of the dependent variable, and the attempt to maintain controlled variables at a constant value. The procedure should describe how you plan to collect sufficient data so that you answer your research question and evaluate the reliability of the data. The collection of sufficient data usually implies selecting a large enough data range to investigate, evaluating a number of data points within the range, and repeating measurements for each data point. Uncertainties: Issues of resolution, precision, accuracy. (OPTIONAL) Discuss how uncertainties are determined for the sensors and timers. In many cases the sensor manufacturer will 'provide information on the accuracy of their devices. II. Data Collection and Processing Recording Raw Data Raw data is the data that was measured or observed. It does not include information that is calculated or surmised. Raw data may include qualitative observations that enhance the interpretation of the results. The quantitative data (numerical measurements) should be recorded in a raw data table. Uncertainties in the raw data should be quantified and recorded in the raw data table. Columns headings should include the name of the variable, units, and an indication of the uncertainty of measurement (if the uncertainty is the same for all measurements). Raw data and the corresponding uncertainty must be recorded with the same number of decimal places. For example, 5.60 ± 0.05 s is correct whereas 5.6 ± 0.05 s is incorrect. All of the raw data for a given variable should be reported to the same level of precision (i.e. decimal places). Raw Data Table Example 1 - student uses a data logging program to measure time and position for a cart moving on a track. Mass mlkg ~m=±O.OI g 335.27 Time tis Mi'::!±O.OOs 0.50 1.00 1.50 2.00 Position xlm ~=±O.OOI 0.189 0.280 0.335 0.544 m Example 2 - student measures the time it takes for a ball to roll down a 1.00 m inclined plane from a height of 0.05 m for three trials Distance slm Mi'::!±O.OO m Height him ~h""'±O.OOl m 1.00 0.050 Time tis M=±O.Ol 6.28 6.39 6.31 s Processed Data Table Data processing is usually understood as combining and manipulating raw data to determine the value of a physical quantity. For data derived from processing raw data (for example, means), the level of precision should be consistent with that of the raw data. Graphs Graphs must include error bars when applicable. When the slope of a linear graph is reported then the minimum and maximum slopes should be used as an approximation of the uncertainty in the slope value. Error Analysis (optional) III. Conclusions & Evaluation [Insert Conclusions and Evaluation here ... ]