Statistically Analysis required for these tables below, by making any of statistical tests for each of them and then analysis the results then writing the report about it and declaring the answers of these two questions by detail.
- Why do some intra-urban areas attract more transit riders than others?
- What types of neighborhoods may induce greater transit demand?
1- These data obtained from the www.walkscore.com for both places (A and B ).
| Data from www.walkscore.com | ||||
| Place | Description of Place | Walk Score | Transit Score | Bike Score |
| A | Commercial area, close to downtown | 91 | 89 | 81 |
| B | Residential area, 20 mile from Downtown | 75 | 45 | 69 |
2- These data obtained from the analyzing the amount of ridership on the one of the routs for bus transit, about 4 bus station ( 1,2 from residential area, and 3,4 commercial area close to Downtown ), ON s mean people rides bus in bus stations, and OFFs mean people drop off from bus in these stations, and the numbers are for ridership’s.
| Ridership Vs Locations 1,2,3 and 4 | ||||
| Residential area, Far from Downtown | Commercial area, so close to downtown | |||
| 1 | 2 | 3 | 4 | |
| ON s | 1731 | 1932 | 821 | 477 |
| OFFs | 3666 | 946 | 9006 | 12669 |
- These data obtained from the analyzing the amount of ridership on the one of the routs for bus transit, for only 2 bus station ( A residential area, and B is commercial area close to downtown ), ON s mean people rides bus in stations, and OFFs mean people drop off from bus in these stations, and the numbers are for ridership’s in weekends and workdays at a period of entire month Nov. 2014.
| Weekend | Workday | |||
| Place | ON s | OFF s | ON s | OFF s |
| A | 426 | 432 | 1453 | 2138 |
| B | 194 | 2488 | 504 | 8366 |
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