Demographic Analysis Sample Clauses

Demographic Analysis. The Polaris Minnesota Traveler Wants and Needs telephone survey database included demographic data such as the survey participant ’s age, gender, income range, etc. Statistical testing was performed to determine if there were any differences in the responses of paired demographic groups for the importance and satisfaction values. The results are tabulated in Appendix D. Any responses that showed a 95% confidence level for being statistically different are marked with an “X” and are organized for planning purposes in terms of “More Important” and “Less Satisfied”. The tested comparisons were as follows: ⚫ Metropolitan Counties (Anoka, Xxxxxx, Chisago, Dakota, Hennepin, Xxxxxx, Scott, Washington) - vs- Non-Metro Counties (Blue Earth, Ohnsted, Otter Tail, St. Xxxxx, Xxxxxx, Xxxxxx, Others) . Those who commute 10 miles or less to work -vs- Those who commute 10 miles or more to work . Those who travel during peak hours (6AM-9AM; 3PM-6PM) - vs- Those who travel during non- peak hours . Males -vs- Females . Age group: 18-34 -vs- Remaining ages . Age group: 35-54 - vs- Remaining ages . Age group: 55 and older -vs- Remaining ages . Income Level: Less than $30,000/year -vs- Remaining incomes . Income Level: $30,000-50,000/year -vs- Remaining incomes . Income Level: $50,000 or greater/year -vs- Remaining incomes . Employed -vs- Not-Working/Part-Time The results showed that no demographic group ’s responses for any of the wants and needs were both more important and less satisfied than those of its paired demographic group. Some of the most consistent differences include the following: Females rated nearly all the wants and needs as more important and nearly all more satisfied than did males. Non-workers or part-time workers rated most of the wants and needs as more important and most more satisfied than did full-time employed workers. Respondents younger than age 55 rated nearly all the wants and needs as less satisfied than did those 55 and older. Respondents earning less than $30,000 per year rated about half the wants and needs as more important and about half more satisfied than did those earning over $30,000 per year. Respondents earning more than $50,000 per year rated about one third of the wants and needs as less important and one third less satisfied than did those earning under $50,000 per year. Non-peak hour travelers rated some of the wants and needs as more important and some more satisfied than did those traveling during peak hour. The remaining demogra...
AutoNDA by SimpleDocs
Demographic Analysis. The MIG Team will collect demographic, socioeconomic, and travel data from available sources, such as the 2020 US Census and American Community Survey, California Household Travel Survey, etc. With the data gathered, the MIG Team will create a community profile for the plan area.
Demographic Analysis. For each loan, indicate the annual income, household size, loan amount, purchase price, loan type, property type, county, whether the property was existing or newly constructed, interest rate, targeted or non-targeted area, whether or not the borrower was a first time buyer, gender, DPA type, marital status, race/ethnicity; HLP averages: loan amount, average household income, purchase price, household size, age, second loan amount, and total percentage of loans with second mortgages.
Demographic Analysis. Collect demographic, socioeconomic, and travel data from available sources such as the 2010 US Census and American Community Survey, California Household Travel Survey, etc. This subtask includes a demographic assessment for each of the planning areas, and will be used to create a community profile for each planning area.

Related to Demographic Analysis

  • Statistical Analysis 31 F-tests and t-tests will be used to analyze OV and Quality Acceptance data. The F-test is a 32 comparison of variances to determine if the OV and Quality Acceptance population variances 33 are equal. The t-test is a comparison of means to determine if the OV and Quality Acceptance 34 population means are equal. In addition to these two types of analyses, independent verification 35 and observation verification will also be used to validate the Quality Acceptance test results.

  • Statistical Sampling Documentation a. A copy of the printout of the random numbers generated by the “Random Numbers” function of the statistical sampling software used by the IRO.

  • Data To permit evaluation of requests under paragraph (c) of this clause based on unreasonable cost, the Contractor shall include the following information and any applicable supporting data based on the survey of suppliers: Foreign (Nondesignated Country) and Domestic Construction Materials Cost Comparison Construction material description Unit of measure Quantity Cost (dollars) * Item 1: Foreign construction material Domestic construction material Item 2 Foreign construction material Domestic construction material [List name, address, telephone number, and contact for suppliers surveyed. Attach copy of response; if oral, attach summary.][Include other applicable supporting information.] [* Include all delivery costs to the construction site.]

  • DATA COLLECTION AND ANALYSIS The goal of this task is to collect operational data from the project, to analyze that data for economic and environmental impacts, and to include the data and analysis in the Final Report. The Recipient shall: • Develop a data collection plan. • Troubleshoot any issues identified. • Collect at least six months of data, including: o Throughput, usage, and operations data o Normal operating hours, up time, down time, and explanations of variations o Feedstock supply summary o Maximum capacity of the new fuel production system in diesel gallon equivalents (DGE) and ordinary units o Gallons of gasoline and/or diesel fuel displaced (with associated mileage information), along with value converted into DGE o Record of wastes from production processes (wastewater, solid waste, criteria emissions, etc.) o Expected air emissions reduction, for example:  Non-methane hydrocarbons  Oxides of nitrogen  Non-methane hydrocarbons plus oxides of nitrogen  Particulate Matter  Formaldehyde o Duty cycle of the current fleet and the expected duty cycle of future vehicle acquisitions, if applicable o Specific jobs and economic development resulting from this project o Levelized cost of fuel and finished fuel price o Analysis of total facility costs, operation and maintenance costs, marginal abatement costs • Comply with the Petroleum Industry Information Reporting Act (PIIRA) and complete CEC Form M810E and CEC Form M13 on a monthly basis for submission to the California Energy Commission’s PIIRA Data Collection Unit. • Provide a written record of registering with the Low Carbon Fuel Standard and Renewable Fuel Standard programs. • Identify any current and planned use of renewable energy at the facility. • Describe any energy efficiency measures used in the facility that may exceed Title 24 standards in Part 6 of the California Code Regulations. • Provide data on potential job creation, economic development, and increased state revenue as a result of expected future expansion. • Provide a quantified estimate of the project’s carbon intensity values or provide an Air Resources Board approved pathway carbon intensity. • Estimate annual life-cycle greenhouse gas emission reduction. • Compare any project performance and expectations provided in the proposal to Energy Commission with actual project performance and accomplishments. • Collect data, information, and analysis described above and include in the Final Report.

  • Study An application for leave of absence for professional study must be supported by a written statement indicating what study or research is to be undertaken, or, if applicable, what subjects are to be studied and at what institutions.

Draft better contracts in just 5 minutes Get the weekly Law Insider newsletter packed with expert videos, webinars, ebooks, and more!