to use this document yourself.
• Introduction

• Analysis

• Conclusions

• Problem Description

• Objectives

• Why linear regression

• independent variables according to possible factors

• regression

• discussion

• travel time & distance

• route and number of traffic signals

• number of passengers, children, ages & income

• the other variables

• correlations

• caluculate p value

• revised model

• descriptive statistic table

• result table

• young male

{"cards":[{"_id":"7f1f8dd52a7231d1d700001d","treeId":"7f1f8de32a7231d1d700001b","seq":11073705,"position":1,"parentId":null,"content":""},{"_id":"7f1f8d922a7231d1d700001e","treeId":"7f1f8de32a7231d1d700001b","seq":11073706,"position":1,"parentId":"7f1f8dd52a7231d1d700001d","content":"Introduction"},{"_id":"7f1f8d682a7231d1d700001f","treeId":"7f1f8de32a7231d1d700001b","seq":11073720,"position":1,"parentId":"7f1f8d922a7231d1d700001e","content":"Problem Description"},{"_id":"7f1f8ccb2a7231d1d7000020","treeId":"7f1f8de32a7231d1d700001b","seq":11073721,"position":2,"parentId":"7f1f8d922a7231d1d700001e","content":"Objectives"},{"_id":"7f1f8c812a7231d1d7000021","treeId":"7f1f8de32a7231d1d700001b","seq":11073728,"position":4,"parentId":"7f1f8dd52a7231d1d700001d","content":"Analysis"},{"_id":"7f1f88852a7231d1d7000024","treeId":"7f1f8de32a7231d1d700001b","seq":11074161,"position":1,"parentId":"7f1f8c812a7231d1d7000021","content":"Why linear regression"},{"_id":"7f1f65df2a7231d1d7000029","treeId":"7f1f8de32a7231d1d700001b","seq":11074022,"position":1.5,"parentId":"7f1f8c812a7231d1d7000021","content":"independent variables according to possible factors"},{"_id":"7f1f880b2a7231d1d7000025","treeId":"7f1f8de32a7231d1d700001b","seq":11074133,"position":1,"parentId":"7f1f65df2a7231d1d7000029","content":"travel time & distance\n"},{"_id":"7f1f85812a7231d1d7000026","treeId":"7f1f8de32a7231d1d700001b","seq":11073865,"position":2,"parentId":"7f1f65df2a7231d1d7000029","content":"route and number of traffic signals"},{"_id":"7f1f82b62a7231d1d7000027","treeId":"7f1f8de32a7231d1d700001b","seq":11073866,"position":3,"parentId":"7f1f65df2a7231d1d7000029","content":"number of passengers, children, ages & income "},{"_id":"7f1f70fc2a7231d1d7000028","treeId":"7f1f8de32a7231d1d700001b","seq":11073867,"position":4,"parentId":"7f1f65df2a7231d1d7000029","content":"the other variables"},{"_id":"7f1f5dc62a7231d1d700002a","treeId":"7f1f8de32a7231d1d700001b","seq":11075775,"position":5,"parentId":"7f1f65df2a7231d1d7000029","content":"correlations"},{"_id":"7f1f5aef2a7231d1d700002b","treeId":"7f1f8de32a7231d1d700001b","seq":11073890,"position":4,"parentId":"7f1f8c812a7231d1d7000021","content":"regression"},{"_id":"7f1f5aad2a7231d1d700002c","treeId":"7f1f8de32a7231d1d700001b","seq":11073911,"position":1,"parentId":"7f1f5aef2a7231d1d700002b","content":"caluculate p value"},{"_id":"7f1f40cb2a7231d1d700002d","treeId":"7f1f8de32a7231d1d700001b","seq":11073981,"position":2,"parentId":"7f1f5aef2a7231d1d700002b","content":"revised model"},{"_id":"7f1f40222a7231d1d700002e","treeId":"7f1f8de32a7231d1d700001b","seq":11073985,"position":1,"parentId":"7f1f40cb2a7231d1d700002d","content":"young male"},{"_id":"7f1f3c162a7231d1d7000031","treeId":"7f1f8de32a7231d1d700001b","seq":11073999,"position":2.5,"parentId":"7f1f5aef2a7231d1d700002b","content":"descriptive statistic table"},{"_id":"7f1f3d372a7231d1d7000030","treeId":"7f1f8de32a7231d1d700001b","seq":11073992,"position":3,"parentId":"7f1f5aef2a7231d1d700002b","content":"result table"},{"_id":"7f1f3e932a7231d1d700002f","treeId":"7f1f8de32a7231d1d700001b","seq":11073988,"position":5,"parentId":"7f1f8c812a7231d1d7000021","content":"discussion"},{"_id":"7f1f8c172a7231d1d7000022","treeId":"7f1f8de32a7231d1d700001b","seq":11073715,"position":5,"parentId":"7f1f8dd52a7231d1d700001d","content":"Conclusions"}],"tree":{"_id":"7f1f8de32a7231d1d700001b","name":"CE614","publicUrl":"ce614"}}