Data Analysis Technique Sample Clauses
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. In supporting this research, the author uses qualitative analysis techniques that are descriptive and tend to use inductive model data analysis. In analyzing, the author refers to the concept offered by ▇▇▇▇▇▇▇▇ (2006: 12), which is a qualitative research approach that uses a lot of extensive data collection, data obtained and presentation of results 29 . The purpose of this study is to qualitatively examine the impact of Indonesia's horticultural import restriction policy on the production of citrus farmers in Pakistan, especially in the context 28 Sugiono (2010), Memahami Penelitian Kualitatif, Bandung, Alfabeta, 20-22 29 ▇▇▇▇ ▇▇▇▇ ▇▇▇▇▇▇▇▇ (2022), Metode Penelitian Kualitatif, Padang, Sumatra Barat, PT. Global Eksekutif Teknologi of the Covid-19 pandemic, using qualitative research methods to understand its impact on trade relations, economic welfare, and regulatory challenges.
Data Analysis Technique. One purpose of statistical analysis as stated by ▇▇▇▇▇▇▇▇▇ (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 (▇▇▇▇, 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 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
Data Analysis Technique. The data analysis technique used in this study is multiple linear regressions, by including three independent variables consisting of environmental uncertainty (X1), organizational structure (X2), distribution network competence (X3), and onedependent variable, namely and the Quality of Information systems Management (Y). Furthermore, as a prerequisite, the regression model should be tested using the classical assumption test through normality test, multicollinearity test, and heteroscedasticity test. Furthermore, to test the research hypothesis tested partially (t-test) and simultaneously (F-test) and the coefficient of determination (R2-test).
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 conducted since before entering field, during field, and after finished in field. The way of data analysis in this method is as follows:
a) Data Reduction Data reduction is a form of analysis that is summarizing, classifying and directing data research results at Sadar Village. It also a way to remove things that are considered unnecessary in this study. Thus, the data obtained by researchers from the results of research in the field after reducing it, so then It will provide information or a clearer picture, making it easier for researchers to perform further data collection.
b) Data Display Presentation of data in this context is a collection of information that has been compiled which allows the conclusion and the taking of action. In order to present the presentation of data will help researchers understand about what happened and what then researchers should do next research. The most common form of data presentation in qualitative research is narrative text, graph, matrix and chart.
Data Analysis Technique. The researcher employs a qualitative data analysis approach in this study and utilizing the technique which indicates by ▇▇▇▇▇ and ▇▇▇▇▇▇▇▇. 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 ▇▇▇▇▇▇▇ (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, ▇▇▇▇▇ and ▇▇▇▇▇▇▇▇ 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: