Using python Jupyter

The measurements are getting closer to known value, but how long do we need to expose to get a "reliable" estimate? You can do a numerical experiment to find out. Try this: Write a function that will determine exposure time needed for 80 out of 100 estimates of the count rate to fall between 0.45 and 0.55 counts per second. Write the function so that you call it only once to give you the answer. Hints: You don't have to pack everything in a single function. Often it helps to break up the whole task into pieces. (This is part of the skill of computational thinking.) It is perfectly ok for you to have a function that runs another function. The np.where command may be useful for checking whether the results of your draw has the requisite number of values within the range. . Don't hard code anything - assume that you may need to re-use this function later for different bounds, different known_rate, etc. Outline: Outline your program here. ]: def poisson(known_rate, exptime, numdraws): measured_rate=((np.random.poisson (known_rate*exptime, numdraws )))/exptime return measured_rate The measurements are getting closer to known value, but how long do we need to expose to get a "reliable" estimate? You can do a numerical experiment to find out. Try this: Write a function that will determine exposure time needed for 80 out of 100 estimates of the count rate to fall between 0.45 and 0.55 counts per second. Write the function so that you call it only once to give you the answer. Hints: You don't have to pack everything in a single function. Often it helps to break up the whole task into pieces. (This is part of the skill of computational thinking.) It is perfectly ok for you to have a function that runs another function. The np.where command may be useful for checking whether the results of your draw has the requisite number of values within the range. . Don't hard code anything - assume that you may need to re-use this function later for different bounds, different known_rate, etc. Outline: Outline your program here. ]: def poisson(known_rate, exptime, numdraws): measured_rate=((np.random.poisson (known_rate*exptime, numdraws )))/exptime return measured_rate