# Part a data collection presentation and analysis

The data files for probability surveys frequently contain more than one weight variable, particularly if the survey is longitudinal or if it has both cross-sectional and longitudinal purposes.

### Data presentation wikipedia

Analysis of Complex Surveys. This includes spacing; the wording, placement and appearance of titles; row and column headings and other labeling. Representation, and This chapter concerns research on collecting, representing, and analyzing the data that underlie behavioral and social sciences knowledge. Change the format of data, i. Statistics Canada. Assess whether the survey design information can be incorporated into the analysis and if so how this should be done such as using design-based methods. Suitable data Ensure that the data are appropriate for the analysis to be carried out. Start with stating the Aim of study and the objectives required to reach the aim. For a design-based analysis consult the survey documentation about the recommended approach for variance estimation for the survey. Data is also required to forecast and estimate the change in the requirement of various resources and thus provide them accordingly. For an analytical product to be accessible, it must be available to people for whom the research results would be useful.

Presentation of results Focus the article on the important variables and topics. For, eg.

## Presentation analysis and interpretation of data in research

How is this study relevant? If analyzing data from a probability sample by design-based methods, use software specifically for survey data since standard analytical software packages that can produce weighted point estimates do not correctly calculate variances for survey-weighted estimates. Some Statistics Canada programs depend on analytical output as a major data product because, for confidentiality reasons, it is not possible to release the microdata to the public. Either have a section in the paper about the data or a reference to where the reader can get the details. However, methods that incorporate the sample design information will generally be effective even when some aspects of the model are incorrectly specified. Thompson, M. Will they satisfy the objectives? Do not forget to give credits and references in the end and where ever required. Consult the survey documentation and survey experts if it is not obvious as to which might be the best weight to be used in any particular design-based analysis. Chapman and Hall. Sampling: Design and Analysis. If the data from more than one survey are included in the same analysis, determine whether or not the different samples were independently selected and how this would impact the appropriate approach to variance estimation. As a good practice, ask someone from the data providing division to review how the data were used.

Some examples: Is a sharp monthly or yearly increase in the rate of juvenile delinquency or unemployment in a particular area a matter for alarm, an ordinary periodic or random fluctuation, or the result of a change or quirk in reporting method?

Data collection through primary survey needs to have well thought of sampling methods.

Assess whether the survey design information can be incorporated into the analysis and if so how this should be done such as using design-based methods. In the presentation of rounded data, do not use more significant digits than are consistent with the accuracy of the data.

## Importance of data presentation

Break the objectives in multiple parts and make a list of data to be collected, the sources of data, form in which data exist and needs to be obtained, conducting a primary survey for information which does not exist. The study of background information allows the analyst to choose suitable data sources and appropriate statistical methods. The data files for probability surveys frequently contain more than one weight variable, particularly if the survey is longitudinal or if it has both cross-sectional and longitudinal purposes. Appropriate methods and tools Choose an analytical approach that is appropriate for the question being investigated and the data to be analyzed. When analyzing data from a probability survey, there may be insufficient design information available to carry out analyses using a full design-based approach. As well, sufficient details must be provided that another person, if allowed access to the data, could replicate the results. Have the article reviewed by others for relevance, accuracy and comprehensibility, regardless of where it is to be disseminated. 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. This will help in reducing the efforts and increasing efficiency. What are the objectives of this analysis? Check details such as the consistency of figures used in the text, tables and charts, the accuracy of external data, and simple arithmetic. Satisfy any confidentiality requirements e. As a good practice, consider presenting the results to peers prior to finalizing the text. The one shown in the figure below is a combination of line and bar graph.

How will these answers contribute to existing knowledge? Since statistics is the largest and most prominent of meth- odological approaches and is used by researchers in virtually every discipline, statistical work draws the lion's share of this chapter's attention.

Skinner eds. Korn, E.

Rated 10/10
based on 70 review

Download