Klimek,+K

__**Population VS Urban/Public Transportation**__ For this page, I will be researching the correlation between population in Canada and revenues made by transportation companies from 1995-2000. This short period of time can give us a snapshot into the lives of people who chose to take part in public transport and the companies that supply their services. The industries covered are urban transit systems, interurban/rural bus transportation, school bus transportation, charter bus industry, shuttle services and scenic and sightseeing transportation by bus. //With population steadily rising in all provinces and territories, will revenues in the transportation sector rise also?// "Canadians are highly mobile, with 13 million traveling to and from work each day,making six trillion trips each year and as many trips again for recreational purposes (Parsons,2003)". My hypothesis is that with the increasing population in Canada, citizens will turn to more public modes of transportation, inturn raising revenues for transport. In this report, the independent variable will be the population, while the revenues pulled in by the transportation sector will be considered dependant. Factors affecting the choice to ride or not ride public transit could be due to overcrowded roads, poor infrastructure, environmentalism, gas prices and one's financial situation. I predict a positive, strong correlation between population and transportation revenues.

Stats Canada shows that from 1995 to 2000, the Canadian bus industry had a 23% increase in revenue. In 2000, the bus industry managed to pull in $3.98 billion dollars, up from $3.24 billion in 1995. Urban transit accounted for 51% of the total bus revenues in 2000, which had grown from 49% in 1995. In 2000, the transit industry handled over 1.5 billion passengers, and increase of 4.2% from the previous year.

The publication found at [] shows data from 1995 to 2000, and informs us that data was collected using existing surveys. The surveys were conducted as a questionnaire. The site took data from various companies in different sectors of the transportation industry. They only sent questionaires to companies that had annual gross operating revenues of over $200,000. Problems that may have occurred in this questionaire could be errors such as non-response bias, sampling bias and response bias. Companies may not have answered questions truthfully, therefore it is possible response bias is present. In regards to non-response bias, companies may have opted out of this survey. Sampling bias may have occurred because the ministry did not allow public sectors of transportation with less than $200,000 revenue to participate. The document I read from the Ministry of Transportation talked about four potential sampling errors: "**I. Coverage Errors** Coverage errors arise when the survey frame does not adequately cover the target population. As a result, certain units belonging to the target population are either excluded (undercoverage) or counted more than once (overcoverage). In addition, out of scope units may be present in the survey frame (overcoverage).
 * Sampling**
 * II. Response Errors**Response errors occur when a respondent provides incorrect information as a result of misinterpretation of the survey questions, gives wrong information by mistake, orbecause of reluctance to disclose the correct information. Some errors are apparent and are caught during editing e.g. misplaced decimal points or inordinate amounts reported in one area. However, some errors are small and may be undetected.
 * III. Non-response Errors**Non-response errors can occur when a respondent does not respond at all (total non-response) or only responds to some questions (partial non-response). With the donor imputation strategy these errors may have a serious effect if non-respondents are systematically different from respondents in survey characteristics and/ r the non-response rate is high.
 * IV. Processing Errors**Processing errors may arise during data capture, coding, editing, imputation, and other types of data handling. Only by following strict quality controls can these errors be minimized. Examples of steps taken to minimize these errors are: a well-planned edit system that conducts checks to ensure that entered totals equal the sum of components; persistent follow-up of nonrespondents to reduce the need for imputation; and fully descriptive procedures manuals to ensure consistency in manual operations. Transportation Division constantly reviews data quality procedures and carries out data quality reviews."

//Below is the Make up of the surveys for years 1999 and 2000. These charts show how many companies with gross revenues over 2 million dollars took part in this survey.// 1999
 * Industrial Survey Population**

2000
 * Industrial Survey Population**




 * [[image:Population.gif width="359" height="338"]]

Population In Canada**

** One Variable Data:**

From the graphs above, we can see population shows a positive strong correlation, while the number of scheduled passengers may be considered to be a positive, strong/moderate correlation.

Mean, Median, Mode and Standard Deviation for my data can be found in this document:


 * Two Variable Data:**

All my work for the correlation coefficient can be found in the following word document



Summary Power Point on Data Culminating:



Brainstorming ideas & Bibliography: