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State them in the below table. Round appropriately such that uncertainties have one significant figures and your other numbers have the same digits after decimal point as your uncertainties. Variable Numerical value Units σ> «ФО R² unitless 4.) Use your linear fit parameters above to state the best estimate of the equation for this line. Remember the equation of the line is y = mx +b where m is the slope and b is the y-intercept. Include units. v(t) (m/s) Error Analysis: = t+ The theoretical value of the slope is 20.45 m/s². 5) Basic error analysis: (Read page 2 of Error Analysis handout). Compute a % error between the theory value and the most probable experimental value . % error = E Q2.) Is the % error positive or negative? What does that tell you? (Read page 3 of Error Analysis handout). Q3.) Can you say if this % error value is "small" or "large"? So can you say if there evidence of discrepancy or no? Do you see the problem with this basic approach? Exercise II: Linear Least Squares Fit / Error Analysis First, read Section II of the "Error Analysis" section in the beginning of your lab manual. 1.) Create a new sheet within your Excel workbook, and copy this set (see right) of mock experiment data into it. 2.) Graph v vs. t, following the graphing guidelines in how to use Excel, step #6 on page 4 to add a linear trendline. t[s] v [m/s] 1 180 234 190 221 228 5 255 6 278 7 291 8 301 Q1.) What is the type of the graph (linear, polynomial, exponential)? What is the unit of the slope? (remember to determine the unit of the slope you can just write the unit of y axis over the unit of x axis and simplify it if necessary). 3.) Use Excel's built-in linest function to find the linear fit parameters for this data set. To do so Read page 5 of how to use Excel. The information that are important in physics are presented in the following table. slope or most probable value σ standard error or uncertainty in slope R2 coefficient of determination y-intercept σ standard error or uncertainty in y-intercept

State them in the below table. Round appropriately such that uncertainties have one significant figures and your other numbers have the same digits after decimal point as your uncertainties. Variable Numerical value Units σ> «ФО R² unitless 4.) Use your linear fit parameters above to state the best estimate of the equation for this line. Remember the equation of the line is y = mx +b where m is the slope and b is the y-intercept. Include units. v(t) (m/s) Error Analysis: = t+ The theoretical value of the slope is 20.45 m/s². 5) Basic error analysis: (Read page 2 of Error Analysis handout). Compute a % error between the theory value and the most probable experimental value . % error = E Q2.) Is the % error positive or negative? What does that tell you? (Read page 3 of Error Analysis handout). Q3.) Can you say if this % error value is "small" or "large"? So can you say if there evidence of discrepancy or no? Do you see the problem with this basic approach? Exercise II: Linear Least Squares Fit / Error Analysis First, read Section II of the "Error Analysis" section in the beginning of your lab manual. 1.) Create a new sheet within your Excel workbook, and copy this set (see right) of mock experiment data into it. 2.) Graph v vs. t, following the graphing guidelines in how to use Excel, step #6 on page 4 to add a linear trendline. t[s] v [m/s] 1 180 234 190 221 228 5 255 6 278 7 291 8 301 Q1.) What is the type of the graph (linear, polynomial, exponential)? What is the unit of the slope? (remember to determine the unit of the slope you can just write the unit of y axis over the unit of x axis and simplify it if necessary). 3.) Use Excel's built-in linest function to find the linear fit parameters for this data set. To do so Read page 5 of how to use Excel. The information that are important in physics are presented in the following table. slope or most probable value σ standard error or uncertainty in slope R2 coefficient of determination y-intercept σ standard error or uncertainty in y-intercept

College Physics
College Physics
11th Edition
ISBN:9781305952300
Author:Raymond A. Serway, Chris Vuille
Publisher:Raymond A. Serway, Chris Vuille
Chapter1: Units, Trigonometry. And Vectors
Section: Chapter Questions
Problem 1CQ: Estimate the order of magnitude of the length, in meters, of each of the following; (a) a mouse, (b)...
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State them in the below table. Round appropriately such that uncertainties have one significant figures and your other numbers have the same digits after decimal point as your uncertainties. Variable Numerical value Units <m> σ<m>> <b> «ФО R² unitless 4.) Use your linear fit parameters above to state the best estimate of the equation for this line. Remember the equation of the line is y = mx +b where m is the slope and b is the y-intercept. Include units. v(t) (m/s) Error Analysis: = t+ The theoretical value of the slope is 20.45 m/s². 5) Basic error analysis: (Read page 2 of Error Analysis handout). Compute a % error between the theory value and the most probable experimental value <m>. % error = E Q2.) Is the % error positive or negative? What does that tell you? (Read page 3 of Error Analysis handout). Q3.) Can you say if this % error value is "small" or "large"? So can you say if there evidence of discrepancy or no? Do you see the problem with this basic approach?
Transcribed Image Text:State them in the below table. Round appropriately such that uncertainties have one significant figures and your other numbers have the same digits after decimal point as your uncertainties. Variable Numerical value Units <m> σ<m>> <b> «ФО R² unitless 4.) Use your linear fit parameters above to state the best estimate of the equation for this line. Remember the equation of the line is y = mx +b where m is the slope and b is the y-intercept. Include units. v(t) (m/s) Error Analysis: = t+ The theoretical value of the slope is 20.45 m/s². 5) Basic error analysis: (Read page 2 of Error Analysis handout). Compute a % error between the theory value and the most probable experimental value <m>. % error = E Q2.) Is the % error positive or negative? What does that tell you? (Read page 3 of Error Analysis handout). Q3.) Can you say if this % error value is "small" or "large"? So can you say if there evidence of discrepancy or no? Do you see the problem with this basic approach?
Exercise II: Linear Least Squares Fit / Error Analysis First, read Section II of the "Error Analysis" section in the beginning of your lab manual. 1.) Create a new sheet within your Excel workbook, and copy this set (see right) of mock experiment data into it. 2.) Graph v vs. t, following the graphing guidelines in how to use Excel, step #6 on page 4 to add a linear trendline. t[s] v [m/s] 1 180 234 190 221 228 5 255 6 278 7 291 8 301 Q1.) What is the type of the graph (linear, polynomial, exponential)? What is the unit of the slope? (remember to determine the unit of the slope you can just write the unit of y axis over the unit of x axis and simplify it if necessary). 3.) Use Excel's built-in linest function to find the linear fit parameters for this data set. To do so Read page 5 of how to use Excel. The information that are important in physics are presented in the following table. <m> slope or most probable value σ<m> standard error or uncertainty in slope R2 coefficient of determination <b> y-intercept σ standard error or uncertainty in y-intercept
Transcribed Image Text:Exercise II: Linear Least Squares Fit / Error Analysis First, read Section II of the "Error Analysis" section in the beginning of your lab manual. 1.) Create a new sheet within your Excel workbook, and copy this set (see right) of mock experiment data into it. 2.) Graph v vs. t, following the graphing guidelines in how to use Excel, step #6 on page 4 to add a linear trendline. t[s] v [m/s] 1 180 234 190 221 228 5 255 6 278 7 291 8 301 Q1.) What is the type of the graph (linear, polynomial, exponential)? What is the unit of the slope? (remember to determine the unit of the slope you can just write the unit of y axis over the unit of x axis and simplify it if necessary). 3.) Use Excel's built-in linest function to find the linear fit parameters for this data set. To do so Read page 5 of how to use Excel. The information that are important in physics are presented in the following table. <m> slope or most probable value σ<m> standard error or uncertainty in slope R2 coefficient of determination <b> y-intercept σ standard error or uncertainty in y-intercept
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