Correlation Analysis Sample Clauses

Correlation Analysis. Each card, symbol, number, or stop position is independently chosen without regard to any other card, symbol, number or stop position, drawn within that game play. Each card, symbol, number, or stop position is considered random if it meets the 99 percent confidence level using standard correlation analysis.
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Correlation Analysis. Shown is a scatterplot with histograms for the respective axes. Statistics and other plot elements adapt dynamically to certain user-­‐triggered events.
Sample 1
Correlation Analysis. The coordinated nature of the comparison programme led to a dataset in which there are significant correlations between individual frequency ratio measurement results. Prior to this project, correlations had been essentially ignored by the joint Frequency Standards Working Group (WGFS) of the Consultative Committee for Time and Frequency (CCTF) and Consultative Committee for Length (CCL) in calculating optimised frequency values and uncertainties for secondary representations of the second, even though this can lead to biased frequency values and underestimated uncertainties. NPL and INRIM therefore collaborated to prepare guidelines on the evaluation and reporting of correlation coefficients between frequency ratio measurements, which are available on our project website. These guidelines discuss ways in which correlations between frequency ratio measurements may arise, and describe how they can be quantified. Worked examples are presented based on measurement data available in the published literature and include several examples of very significant correlations that were neglected in the 2017 update to the list of CIPM recommended frequency values. Suggestions are also presented as to how the information necessary to compute the correlation coefficients might be gathered from the groups performing such measurements, for future updates to the list. These guidelines were shared with the WGFS and strongly influenced the 2021 update to the list of recommended frequency values (section 4.4.1), ensuring that it was underpinned by a more robust analysis of the available data. The guidelines were also used by other members of the consortium to compute the correlation coefficients between the various frequency ratios measured in this project. In total 313 non-zero correlation coefficients were evaluated between pairs of frequency ratio measurements, of which 135 had a magnitude ≥ 0.1 and 40 had a magnitude ≥ 0.5. A graphical representation of the correlation coefficients between the 20 different remote ratios measured via satellite links in the 2022 campaign is shown in Figure 7.
Sample 1

Related to Correlation Analysis

  • 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

  • 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.

  • LIMITATIONS ON REVERSE ENGINEERING, DECOMPILATION AND DISASSEMBLY You may not reverse engineer, decompile, or disassemble the Software, except and only to the extent that such activity is expressly permitted by applicable law notwithstanding this limitation.

  • 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.

  • 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.

  • Conformity Assessment Procedures 1. Each Party shall give positive consideration to accepting the results of conformity assessment procedures of other Parties, even where those procedures differ from its own, provided it is satisfied that those procedures offer an assurance of conformity with applicable technical regulations or standards equivalent to its own procedures.

  • Audit and Testing 4.1 The Contractor shall conduct tests of the processes and countermeasures contained in the Security Plan ("Security Tests") on an annual basis or as otherwise agreed by the Parties. The date, timing, content and conduct of such Security Tests shall be agreed in advance with the Authority.

  • Random Drug Testing All employees covered by this Agreement shall be subject to random drug testing in accordance with Appendix D.

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  • 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.

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