By Allen Downey B.
If you know the way to software, you've gotten the abilities to show information into wisdom utilizing the instruments of likelihood and facts. This concise advent indicates you the way to accomplish statistical research computationally, instead of mathematically, with courses written in Python.
You'll paintings with a case examine in the course of the booklet that will help you study the whole facts research process—from gathering facts and producing records to determining styles and trying out hypotheses. alongside the way in which, you'll familiarize yourself with distributions, the principles of chance, visualization, and plenty of different instruments and concepts.
* increase your knowing of chance and data through writing and trying out code
* Run experiments to check statistical habit, akin to producing samples from a number of distributions
* Use simulations to appreciate suggestions which are demanding to understand mathematically
* study themes no longer frequently lined in an introductory direction, equivalent to Bayesian estimation
* Import facts from virtually any resource utilizing Python, instead of be restricted to facts that has been wiped clean and formatted for facts instruments
* Use statistical inference to reply to questions about real-world info
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Additional resources for Think Stats
Xmin = 1000 xmax = 200000 17 18 19 20 21 # Record the list sizes in xList and the average access time within # a list that size in yList for 1000 retrievals. now() 38 39 40 41 42 43 44 45 46 47 for v in range(1000): # Find a random location within the list # and retrieve a value. Do a dummy operation # with that value to ensure it is really retrieved. now() 48 49 50 # The difference in time between start and end. deltaT = endtime - starttime 51 52 53 54 # Divide by 1000 for the average access time # But also multiply by 1000000 for microseconds.
2. 2 A Graphics Program 1 import turtle 2 3 4 5 # Command classes would be inserted here but are left out because they # were defined earlier in the chapter. 13 The Accumulator Pattern 6 7 23 # This is our PyList class. It holds a list of our graphics # commands. items + [item] 15 16 17 18 19 20 21 22 23 24 25 26 27 28 # if we want to iterate over this sequence, we define the special method # called __iter__(self). TypeError: # ’PyList’ object is not iterable" if we try to write # for cmd in seq: # where seq is one of these sequences.
5. If you were to execute the code you wrote for answering the last three questions, what would the string referenced by text contain after executing these three lines of code? 6. How would you create a dictionary that maps “Kent” to “Denise” and maps “Steve” to “Lindy”? In these two cases “Kent” and “Steve” are the keys and “Denise” and “Lindy” are the values. 7. Consult Chap. 17. How would you map a key to a value as in the previous problem when the dictionary was first created as an empty dictionary?
Think Stats by Allen Downey B.