Data Analysis In the meeting, the analysis that has led the College President to conclude that a reduction- in-force in the FSA at that College may be necessary will be shared. The analysis will include but is not limited to the following: ● Relationship of the FSA to the mission, vision, values, and strategic plan of the College and district ● External requirement for the services provided by the FSA such as accreditation or intergovernmental agreements ● Annual instructional load (as applicable) ● Percentage of annual instructional load taught by Residential Faculty (as applicable) ● Fall Full-Time Student Equivalent (FFTE) inclusive of dual enrollment ● Number of Residential Faculty teaching/working in the FSA ● Number of Residential Faculty whose primary FSA is the FSA being analyzed ● Revenue trends over five years for the FSA including but not limited to tuition and fees ● Expenditure trends over five years for the FSA including but not limited to personnel and capital ● Account balances for any fees accounts within the FSA ● Cost/benefit analysis of reducing all non-Residential Faculty plus one Residential Faculty within the FSA ● An explanation of the problem that reducing the number of faculty in the FSA would solve ● The list of potential Residential Faculty that are at risk of layoff as determined by the Vice Chancellor of Human Resources ● Other relevant information, as requested
SAMPLE (i) Unless agreed otherwise, wheeled or track lay- ing equipment shall not be operated in areas identified as needing special measures except on roads, landings, tractor roads, or skid trails approved under B5.1 or B6.422. Purchaser may be required to backblade skid trails and other ground disturbed by Purchaser’s Opera- tions within such areas in lieu of cross ditching required under B6.6. Additional special protection measures needed to protect such known areas are identified in C6.24.
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.
Packing Specifications 7.3.1 A pack will contain a minimum of one message record or a maximum of 99,999 message records plus a pack header record and a pack trailer record. One transmission can contain a maximum of 99 packs and a minimum of one pack.
COMPENSATION ANALYSIS After the expiration of the second (2nd) Renewal Term of this Agreement, if any, a Compensation Analysis may be performed. At such time, based on the reported Total Gross Revenue, performance of the Concession, and/or Department’s existing rates for similarly- performing operations, Department may choose to increase the Concession Payment for the following Renewal Term(s), if any.
ODUF Packing Specifications 6.3.1 The data will be packed using ATIS EMI records. A pack will contain a minimum of one (1) message record or a maximum of ninety-nine thousand nine hundred and ninety-nine (99,999) message records plus a pack header record and a pack trailer record. One transmission can contain a maximum of ninety-nine (99) packs and a minimum of one (1) pack.
Billing Specifications 55.6.1 The Parties agree that billing requirements and outputs will be consistent with the Ordering & Billing Form (OBF) and also with Telcordia Technologies Billing Output Specifications (BOS).
EODUF Packing Specifications 7.3.1 The data will be packed using ATIS EMI records. A pack will contain a minimum of one (1) message record or a maximum of ninety-nine thousand nine hundred and ninety-nine (99,999) message records plus a pack header record and a pack trailer record. One transmission can contain a maximum of ninety-nine (99) packs and a minimum of one (1) pack.
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 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. Formulas will be provided for calculations. A Final Report data collection template will be provided by the Energy Commission. The Recipient shall: • Develop data collection test plan. • Troubleshoot any issues identified. • Collect data, information, and analysis and develop a Final Report which includes: o Total gross project costs. o Length of time from award of bus(es) to project completion. o Fuel usage before and after the project.
