# CitiBike Data and Simulation Models using Excel or @RISK or Arena

First, conclude that bikers enter to Post 1 (post id =1) according to a nonstationary Poisson manner. Complete the beneath board (enclosed represent smooth) of manifestatlon rates at Post 1.  Hint: Create a agetreasure column. Excel ‘Timetreasure (age quotation)’ returns the decimal number of the age represented by a quotation string. The decimal number is a treasure ranging from 0 (zero) to 0.99988426, representing the ages from 0:00:00 (12:00:00 AM) to 23:59:59 (11:59:59 P.M.). For stance, TIMEVALUE("1-June-2017 6:35 AM") = 0.2743. Use the histogram of the agetreasure to abuse the manifestatlon rates. Second, appoint a doom (end post id) to each manifestatlon at Post 1 by using a discrete verisimilitude arrangement of this form:   DISC(p1,1, p2,2,…p12,12) Determine the treasure of p1, p2…p12 using the referring-to quantity bar chart of ‘end post id’. Copy and paste your Excel worksheet. Finally, plant a probabilistic example for the fall continuance from Post 1 to Post i, delay i=1,2,…12 i. First stride is to transport outliers. If a bike has been laceration out for over than 24 hours at a age, it is considered past or stolen. Transport any falls longer than 24 hours (86,400 seconds). You can besides transport over outliers if you imagine it is essential.  ii. Considering the scatterplot beneath (Word instrument) and the subsidence of the 12 posts, mention the verisimilitude arrangement of the fall continuance from Post 1 to Post i, delay i =1, 2,…12.  You can use Arena Input Analyzer, @RISK, or any other statistical software you enjoy. You may incorporate some (or flush all) end posts to mention input verisimilitude arrangements. Copy and paste your Arena Input analyzer results or Excel worksheet. Copy and paste your Excel worksheet.