Demographic Analysis Clause Samples
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. 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, ▇▇▇▇▇▇, Chisago, Dakota, Hennepin, ▇▇▇▇▇▇, Scott, Washington) - vs- Non-Metro Counties (Blue Earth, Ohnsted, Otter Tail, St. ▇▇▇▇▇, ▇▇▇▇▇▇, ▇▇▇▇▇▇, 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...
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.
Demographic Analysis. 1.1. 3The 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:
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.