Rajarata University of Sri Lanka Final Year Research Report

Rajarata University of Sri Lanka

Department of Languages

Faculty of Social Sciences and Humanities

Online Lectures

Year and Semester	Year-3 Semester-2
Subject	Research Report-10
Subject Code	TEF 3224
Course Unit	Discussion on Data Presentation and Analysis-1
Date	30.05.2020
Time	Practical: 9.00 am-11.00 am
Lecturer	D.N. Aloysius
Practical Hours	02                                            Total  No of  Hours: 20

Data Presentation and Analysis-1

Data analysis is the process of developing answers to questions through the examination and interpretation of data.  The basic steps in the analytic process consist of identifying issues, determining the availability of suitable data, deciding on which methods are appropriate for answering the questions of interest, applying the methods and evaluating, summarizing and communicating the results. 

Analytical results underscore the usefulness of data sources by shedding light on relevant issues. Some Statistics Canada programs depend on analytical output as a major data product because, for confidentiality reasons, it is not possible to release the micro data to the public. Data analysis also plays a key role in data quality assessment by pointing to data quality problems in a given survey. Analysis can thus influence future improvements to the survey process.

Data analysis is essential for understanding results from surveys, administrative sources and pilot studies; for providing information on data gaps; for designing and redesigning surveys; for planning new statistical activities; and for formulating quality objectives.

Results of data analysis are often published or summarized in official Statistics Canada releases. 

Principles

A statistical agency is concerned with the relevance and usefulness to users of the information contained in its data. Analysis is the principal tool for obtaining information from the data.

Data from a survey can be used for descriptive or analytic studies. Descriptive studies are directed at the estimation of summary measures of a target population, for example, the average profits of owner-operated businesses in 2005 or the proportion of 2007 high school graduates who went on to higher education in the next twelve months.  Analytical studies may be used to explain the behaviour of and relationships among characteristics; for example, a study of risk factors for obesity in children would be analytic. 

To be effective, the analyst needs to understand the relevant issues both current and those likely to emerge in the future and how to present the results to the audience. The study of background information allows the analyst to choose suitable data sources and appropriate statistical methods. Any conclusions presented in an analysis, including those that can impact public policy, must be supported by the data being analyzed.

Practical: How do you present and analyze your data?

Reference: Chambers, R.L. and C.J. Skinner (eds.) 2003. Analysis of Survey Data. Chichester. Wiley. 398 p.