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Deacon, Christopher G. – Physics Teacher, 1992
Describes two simple methods of error analysis: (1) combining errors in the measured quantities; and (2) calculating the error or uncertainty in the slope of a straight-line graph. Discusses significance of the error in the comparison of experimental results with some known value. (MDH)
Descriptors: Error of Measurement, Goodness of Fit, High Schools, Higher Education
Dickmeyer, Nathan; Hughes, K. Scott – 1980
In order to assist college and university officials evaluating their institution's financial condition, a simplified workbook approach is presented. The approach encourages administrators to systematically examine the financial condition of their colleges with a tested and specified set of data-gathering and computational steps. The workbook…
Descriptors: College Administration, College Planning, Comparative Analysis, Educational Finance
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Shibli, Abdullah – College Teaching, 1992
In college courses in statistics and computer programing, learning can be enhanced when students are required to express formulas and notations in writing. This approach helps improve concept formation, comprehension, problem solving, and ability to draw conclusions and interpretations. Attention to syntax and form is important. (MSE)
Descriptors: College Instruction, College Mathematics, Comprehension, Computer Science
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Turner, Charles – Journal of Student Financial Aid, 1997
Comparison of federal need-analysis formulas for student financial aid in 1992-93 and 1993-94 focused on elimination of home/farm equity from calculations, parent contributions, and Pell Grant awards. Results suggest higher unmet need and lower Pell Grant awards, and imply that the most needy students may lose gift assistance to more affluent…
Descriptors: Comparative Analysis, Educational Economics, Federal Programs, Higher Education
Garcia, Juan G.; And Others – 1978
Price indices related to specific expenditure categories are necessary for realistic budget projections in higher education. Given the erratic inflationary behavior of the past seven years, and the uniqueness of higher education expenditures, realistic inflation prediction requires a balanced combination of analytic forecasting and intuitive…
Descriptors: Budgeting, College Administration, Cost Indexes, Educational Economics
Joyce, Colleen D. – US Census Bureau, 2005
The U.S. Census Bureau's Small Area Income and Poverty Estimates (SAIPE) Program produces poverty and income estimates for states, counties, and school districts on an annual basis. These estimates provide updated income and poverty statistics, which are used for the administration of federal programs and the allocation of federal funds to local…
Descriptors: Poverty, Income, Federal Legislation, Federal Programs
Steen, Ralph W.; And Others – 1979
Explained and illustrated is the formula funding system used for colleges and universities in Texas. This system is considerably more complicated than the formulas used in other states. Data for institutions in the state system for fiscal 1978 are presented; actual appropriations are used rather than requests, and formula-produced amounts are…
Descriptors: Adult Education, Ancillary Services, Budgeting, Budgets
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Fowler, William J., Jr., Ed. – National Center for Education Statistics, 1999
The National Center for Education Statistics (NCES) commissioned the papers in this publication to address advances in measuring education inflation and adjusting for it, as well as to examine the emergence of a new focus on school spending, rather than school district spending, as well as new, private sources of funding for public education, and…
Descriptors: Educational Finance, Cost Indexes, Investment, Productivity
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