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Compute the Compute the time intervals between successive data points. displacements between successive data points. Compute the average velocity by computing the ratio of displacement to time interval for each time interval.

Compute the Compute the time intervals between successive data points. displacements between successive data points. Compute the average velocity by computing the ratio of displacement to time interval for each time interval.

University Physics Volume 1
University Physics Volume 1
18th Edition
ISBN:9781938168277
Author:William Moebs, Samuel J. Ling, Jeff Sanny
Publisher:William Moebs, Samuel J. Ling, Jeff Sanny
Chapter1: Units And Measurement
Section: Chapter Questions
Problem 83AP: A marathon runner completes a 42.188-km course in 2 h, 30 min, and 12s. There is an uncertainty of...
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Can you please help me do step 2 how do u compute them
ti ne, making sure to display quation and de for the trendline. Remember to add axis titles. Each axis title includes the word description, the symbol, and the units. 2. Compute the time intervals between successive data points. Compute the displacements between successive data points. Compute the average velocity by computing the ratio of displacement to time interval for each time interval. 3. Make a graph (an "XY (scatter)" chart) of average velocity Vavx versus time t. Time is plotted along the horizontal axis. Remember to add axis titles. Each axis title includes the word description, the symbol, and the units. 4. We will now use the built-in LINEST function of Excel to obtain the linear fit to the average velocity data. Click on cell 165 of the spreadsheet template. Hold down the shift key while clicking on cell J69. Ten cells should now be highlighted. Type "=LINEST(F66:F77,A66:A77,true,true)" without the quotation marks and then press enter. Ten numbers should now populate the ten cells that had been highlighted. For data that are expected to follow a linear trend, the LINEST command provides the slope and y-intercept of the best-fit linear trendline while also providing the uncertainty in the slope and the y-intercept. 5. When adding a trendline in Excel, there is always the option to display the R² value, which is equal to 1 if the trendline perfectly fits the data. To obtain a qualitative idea of how close the R² value must be to 1 to obtain a fit that "looks good", repeat step C.4 for the increasingly noisy data sets in Table 6 of the spreadsheet template - notice that space has been provided in the template for three new sets of LINEST parameters. Plot all three data sets on a new graph, with linear trendlines, and add a legend. The trendline for a data set should have the same color as the symbols used to represent the data set. 6. You may earn up to one extra credit point if you turn in your data spreadsheet, with all data tables completely calculated and the pots for parts A and B via Canvas by two days (48 hours) before the start of your next scheduled face-to- face lab meeting.
Transcribed Image Text:ti ne, making sure to display quation and de for the trendline. Remember to add axis titles. Each axis title includes the word description, the symbol, and the units. 2. Compute the time intervals between successive data points. Compute the displacements between successive data points. Compute the average velocity by computing the ratio of displacement to time interval for each time interval. 3. Make a graph (an "XY (scatter)" chart) of average velocity Vavx versus time t. Time is plotted along the horizontal axis. Remember to add axis titles. Each axis title includes the word description, the symbol, and the units. 4. We will now use the built-in LINEST function of Excel to obtain the linear fit to the average velocity data. Click on cell 165 of the spreadsheet template. Hold down the shift key while clicking on cell J69. Ten cells should now be highlighted. Type "=LINEST(F66:F77,A66:A77,true,true)" without the quotation marks and then press enter. Ten numbers should now populate the ten cells that had been highlighted. For data that are expected to follow a linear trend, the LINEST command provides the slope and y-intercept of the best-fit linear trendline while also providing the uncertainty in the slope and the y-intercept. 5. When adding a trendline in Excel, there is always the option to display the R² value, which is equal to 1 if the trendline perfectly fits the data. To obtain a qualitative idea of how close the R² value must be to 1 to obtain a fit that "looks good", repeat step C.4 for the increasingly noisy data sets in Table 6 of the spreadsheet template - notice that space has been provided in the template for three new sets of LINEST parameters. Plot all three data sets on a new graph, with linear trendlines, and add a legend. The trendline for a data set should have the same color as the symbols used to represent the data set. 6. You may earn up to one extra credit point if you turn in your data spreadsheet, with all data tables completely calculated and the pots for parts A and B via Canvas by two days (48 hours) before the start of your next scheduled face-to- face lab meeting.
A 3 4 D Time t (s) 58 59 Part C: Plotting, Transforming, and Analyzing Data 50 51 2 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00 2.20 2.40 B w Position X (m) C 0.327 0.351 Uncertainty of Position Sx (m) 0.005 0.005 D 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 Time Interval At (s) Do not fill E Displacement Ax F Average Velocity v_av,x (m) (m/s) Do not fill Do not fill 0.383 0.428 0.483 0.549 0.623 0.710 0.803 0.908 1.026 1.149 1.284 Table 5: Measured Horizontal Position versus Time Data with Computed Quantities G LINEST
Transcribed Image Text:A 3 4 D Time t (s) 58 59 Part C: Plotting, Transforming, and Analyzing Data 50 51 2 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00 2.20 2.40 B w Position X (m) C 0.327 0.351 Uncertainty of Position Sx (m) 0.005 0.005 D 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 Time Interval At (s) Do not fill E Displacement Ax F Average Velocity v_av,x (m) (m/s) Do not fill Do not fill 0.383 0.428 0.483 0.549 0.623 0.710 0.803 0.908 1.026 1.149 1.284 Table 5: Measured Horizontal Position versus Time Data with Computed Quantities G LINEST
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