Data Analysis Technique Sample Clauses

Data Analysis Technique. One purpose of statistical analysis as stated by Xxxxxxxxx (1977), is to reduce a mass of data into a more compact form that shows general trends and relationships between variables. He maintained that the objective of statistical analysis is to provide a quantitative way of distilling the essential features. The following technique was used in analysis the data: The Chi-Square (X2 ) Chi-Square, as a method for testing hypotheses, measures the reliability and significance of data to see whether deviations of the actual observations (observed frequency) from the expected is significant so that it may lead to the acceptance or rejection of the null hypothesis. Chi-square may be defined as the sum of the ratio of difference between observed and expected values (Xxxx, 1974). Its use involves the determination of the observed (actual) and the expected frequencies, the deviation squared, and the summations of the deviations squared divided by the summations of the deviations squared divided by the summations of the expected frequencies thus: Chi-Square (X2) = Σ (0-E)2 E Where O = Observed value (frequency); and E = Expected (value frequency) Therefore Chi-Square test was used to evaluate whether or not the values that have been empirically obtained differ significantly from those, which would be expected under a certain set of theoretical assumptions
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Data Analysis Technique. Data analysis technique is the process of reviewing all available data from various sources, such as interviews, observations, official documents, and images or photographs that have been obtained in the field during the study. Data analysis in qualitative research Kolokium Pendidikan Nusantara UTM-UNM 2018 55 conducted since before entering field, during field, and after finished in field. The way of data analysis in this method is as follows:
Data Analysis Technique. In order to ensure the quality of the data, the interviewer carefully supervised all stages of data collection. The interviewer was responsible for the accuracy of data collected in the field. She ensured that the data was collected in accordance within standards and guidelines of the research purpose. At the end of each day, the data were checked for consistency or missing information. Controls were programmed directly on the smartphones used for data collection, thus limiting the need for data cleaning. All completed surveys were double-entered using Microsoft Excel to verify accuracy of the data entry whenever possible. Back-up files of the database were created after each survey. Both Excel spreadsheets were compared and any inconsistency in the data was verified using the original questionnaires. For quality control, the check of the household surveys was programmed directly into the Open Data Kit software used for data collection to reduce the need for data cleaning, to limit the entry of incorrect data, and to ensure entry of data into required fields. After data entry and cleaning, the data was analyzed using EpiInfo 7.2 software and SAS
Data Analysis Technique. The researcher employs a qualitative data analysis approach in this study and utilizing the technique which indicates by Xxxxx and Xxxxxxxx. Data analysis is a time-consuming and challenging procedure in qualitative research. It is the process by which researchers methodically explore and organize their data in order to get a better understanding of the data and convey the results to others. According to Xxxxxxx (2010), "data analysis is a process of data management, arranging it into a good pattern, category, and fundamental unit." Qualitative analysis is a complicated, nonlinear process. In qualitative research, data analysis is frequently performed immediately or simultaneously with data gathering. However, Xxxxx and Xxxxxxxx indicate that the data analysis in this study may be divided into three steps: data reduction, data display, and drawing conclusions or interpretation. These are explained as follows:

Related to Data Analysis Technique

  • 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

  • Technology Research Analyst Job# 1810 General Characteristics Maintains a strong understanding of the enterprise’s IT systems and architectures. Assists in the analysis of the requirements for the enterprise and applying emerging technologies to support long-term business objectives. Responsible for researching, collecting, and disseminating information on emerging technologies and key learnings throughout the enterprise. Researches and recommends changes to foundation architecture. Supports research projects to identify and evaluate emerging technologies. Interfaces with users and staff to evaluate possible implementation of the new technology in the enterprise, consistent with the goal of improving existing systems and technologies and in meeting the needs of the business. Analyzes and researches process of deployment and assists in this process.

  • Protocols Each party hereby agrees that the inclusion of additional protocols may be required to make this Agreement specific. All such protocols shall be negotiated, determined and agreed upon by both parties hereto.

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

  • Drug Test Results 1. All records pertaining to department-required drug tests shall remain confidential, and shall not be provided to other employers or agencies without the written permission of the person whose records are sought. However, medical, administrative, and immediate supervisory personnel may have access to relevant portions of the records as necessary to insure the acceptable performance of the officer's job duties.

  • Disturbance Analysis Data Exchange The Parties will cooperate with one another and the NYISO in the analysis of disturbances to either the Large Generating Facility or the New York State Transmission System by gathering and providing access to any information relating to any disturbance, including information from disturbance recording equipment, protective relay targets, breaker operations and sequence of events records, and any disturbance information required by Good Utility Practice.

  • SHOP DRAWINGS, PRODUCT DATA AND SAMPLES 4.12.1 Shop Drawings are drawings, diagrams, schedules and other, data specially prepared for the Work by the Contractor or any Subcontractor, manufacturer, supplier or distributor to illustrate some portion of the Work.

  • Architecture The Private Improvements shall have architectural features, detailing, and design elements in accordance with the Project Schematic Drawings. All accessory screening walls or fences, if necessary, shall use similar primary material, color, and detailing as on the Private Improvements.

  • 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.

  • Templates The Applicant shall use Templates provided by Alberta Innovates to comply with its Required Reporting Metrics, Reports obligations, and with the Survey requirements. Because the Reports may contain technical or proprietary information about the Project or the Applicant, the Templates will specify when a section will be considered non-confidential. The content of sections that are marked as non-confidential can be disclosed in the public domain. All other sections will be considered confidential, and thus can only be disclosed to the Government of Alberta and to Funding Partners, if any, in confidence, but to no other party.

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