Q1 Measuring gravity by dropping a ball in a vacuum n an experiment, a ball was dropped through a vertial distnace from rest. The vertical distance tranversed and the corresponding time interva measured at these distances were 3.24, 2.68, 2.35, 1.87, 2.57,2.77 meters, with the corresponding time intervals 0.81, 0.74, 0.69, 0.61, 0.72, 0.75 seconds. The time intervals are measured with an error bar of 0.1 second. Determine the best-fit value of g by fitting the data points against the formula h = gt2 by taking into accont the error in time the time interval. Be reminded that the argument 'sigma' and absolut_sigma=True' in scipy.optimize.curve_fit() are associated with the error bar in h (not At). Hint : You have to calculate Ah for each pair of hị, t¡. Hint : Vour result should be the same (or almost the same) as that obtained using t - 2h
Q1 Measuring gravity by dropping a ball in a vacuum n an experiment, a ball was dropped through a vertial distnace from rest. The vertical distance tranversed and the corresponding time interva measured at these distances were 3.24, 2.68, 2.35, 1.87, 2.57,2.77 meters, with the corresponding time intervals 0.81, 0.74, 0.69, 0.61, 0.72, 0.75 seconds. The time intervals are measured with an error bar of 0.1 second. Determine the best-fit value of g by fitting the data points against the formula h = gt2 by taking into accont the error in time the time interval. Be reminded that the argument 'sigma' and absolut_sigma=True' in scipy.optimize.curve_fit() are associated with the error bar in h (not At). Hint : You have to calculate Ah for each pair of hị, t¡. Hint : Vour result should be the same (or almost the same) as that obtained using t - 2h
C++ for Engineers and Scientists
4th Edition
ISBN:9781133187844
Author:Bronson, Gary J.
Publisher:Bronson, Gary J.
Chapter3: Assignment, Formatting, And Interactive Input
Section3.6: A Case Study: Acid Rain
Problem 7E
Related questions
Question
need help with python.
can modify/ refer from the code below
import numpy as np; from pylab import *;
import scipy.optimize
hdata=[3.24, 2.68, 2.35, 1.87, 2.57,2.77]
tdata=[0.81, 0.74, 0.69, 0.61, 0.72, 0.75];
error_in_t=np.ones(6)*0.1
def t(h,g):
return (2*h/g)**0.5
results=scipy.optimize.curve_fit(t,hdata,tdata,sigma=error_in_t,absolute_sigma=True)
gbest=results[0][0];
var=results[1][0][0];
se=var**0.5
print(gbest)
print(var,se)
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
Step by step
Solved in 2 steps
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.Recommended textbooks for you
C++ for Engineers and Scientists
Computer Science
ISBN:
9781133187844
Author:
Bronson, Gary J.
Publisher:
Course Technology Ptr
C++ for Engineers and Scientists
Computer Science
ISBN:
9781133187844
Author:
Bronson, Gary J.
Publisher:
Course Technology Ptr