STATISTICAL RESEARCH

Analyzing The Data
1. In this stage, we interpret the data to find some conclusion.
2. The purpose of Data Analysis is to extract useful information from data and taking the decision based upon the data analysis
3. The major Data Analysis methods are:
  1. Text Analysis
  2. Prescriptive Analysis
  3. Diagnostic Analysis
Data Organizing
1. Here, we put the data in some systematic order.
2. Techniques for data organization include:
  1. Mind-mapping:
  2. Affinity diagrams.
  3. Card sorting
3. Data organization helps us to arrange the data in order that we can easily read and work..
Data Planning
1. A data planning process ensures that all aspects of data management are explored at the start of a project
2. Effective management of data provides researchers with many benefits as:
  1. Time saved through reduced duplication of effort
  2. increased researcher profile through data dissemination and re-use
  3. Decreased risk of loss, theft or inappropriate use of data
3. A data planning process is particularly important in the context of collaborative research projects.
Results Presentation
1. In this stage the data are presented by graphs, diagrams, tables, etc.
  1. When presenting the data, some form of a written report is essential
2. When presenting results, the format of the presentation should be tailored to address the aims and objectives of the survey and to satisfy the potential users of the results
3. The presentation needs to be effective, easy to understand and convey the main features of the data.
Data Collection
1. It refers to gather some statisticas facts by different methods.
  1. During data collection, the researchers must identify the data types, the sources of data, and what methods are being used.
    1. Among the effects of data collection done incorrectly, include the following:
      1. Erroneous conclusions that squander resource
      2. The study's inability to be replicated and validated
      3. Incapacity to correctly respond to research inquiries
3. The approach of data collection is different for different fields of study, depending on the required information
  1. Accurate data collecting is crucial to preserving the integrity of research, regardless of the subject of study or preferred method for defining data (quantitative, qualitative).
4. EXAMPLES
  1. Projective Technique.
  2. Questionnaires.
  3. Interviews.

Nächster

STATISTICAL RESEARCH

Beschreibung

Zusammenfassung der Ressource

Medienanhänge

ähnlicher Inhalt

	Erstellt von Hidalia Morales vor etwa 3 Jahre