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Techniques of Data Presentation
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Introduction

Data presentation could be done in many different ways. Many channels can be used to convey the information after data collection. The raw data is analyzed by the researcher, and numerous opinions from the targeted population are obtained this way. Data analysis is the method of developing solutions to the problems through the examination and explanation of data. The basic stages in analyzing the data involve the identification of issues, determination of the availability of suitable data, deciding on the appropriate methods for answering the questions of interest, applying the techniques and assessing, summarizing and sharing the results.** **The analyst requires understanding the relevant issues he is presenting in order to be effective.

The example of the survey given was a national representative; they dialed the telephone numbers randomly. They had a sample size of 1051 parents who had children aging 6 months to 6years. It was conducted from September 12 through November 21, 2005. The research was conducted by the Kaiser Family Foundation, in consultation with Princeton Survey Research Associates. The fieldwork was conducted in English and Spanish by Princeton Data Resource. The sampling error margin was +/-3 percentage points. The margin of error was found to be relatively high. The response rate was at 33%. The research took place during the day and in the eligible households interviewers asked to speak with parents who spent most time with the targeted kid.

The techniques that can be used to present data should be completely effective and efficient for the presentation. One should also include information regarding the quality of the results. The standard errors, confidence intervals and the coefficients of variation provide the reader important information about the quality of data. Choice of indicator may differ depending on where the article is published. The references should also be accurate, consistent and referenced in the text. Data Presentation Methods Data can be summarized and presented in numerous forms. They include the following:

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1.
**Tabulation.** This method deals with presentation of data in tabular form. A table is an array of information in rows and columns. Tabulation shrinks a large quantity of data and brings out the different outlines in data, in an attractive form. It allows comparison to be made easily amongst classes of data. It takes up a smaller amount space than data presented in narrative form. Tables have these contents:

a) A title at the top recounting the content of the table. The title gives identification of what is to be expected in the table.

b) The caption-column heading.

c) The stubs- row headings.

d) Footnote - this is brief descriptive information about the table. It has a brief description of what is found in the table.

e) Elements of measurement. The units of measure used in the table should also be stated clearly for better understanding of the table.

f) The source at the bottom of the page may sometimes be the footnote. This gives the user of the table the convenience that the tables information is genuine.

For enhanced visual impact, facts can be denoted in the form of: Pictogram, Pie Chart, Bar Chart, Histogram and Line graph. While using graphs and tables to communicate, the messages always use headings. Headings capture the meaning, because these assist readers in understanding the information in the tables and charts by discussing it in the text. The overall presentation adds to the clarity of the data in the tables and avoids misinterpretation. This includes spacing; the wording, placement and the appearance of titles; row and column headings and other labels.

a) **Pictogram** presents pictorial symbols that represent the data of interest. It is a picture diagram. A key is usually given on the value of each pictorial symbol. The data is usually presented in artistic and appealing form to the users. In the research conducted by the Kaiser Family Foundation, the data could have also been presented in the form of a pictogram.

b) **Pie Chart** also known as **circle graph**. Pie charts consist of circles, divided into sectors, which are proportionate to the data. The sum of angles in a circle is 360 degrees. An overall of all cases is found, and the percentage of each case is found in relation to 360 degrees. Pie charts are usually not for more than five categories. It is a convenient way of showing the sizes of elements figures in proportion to each other and the overall total.

c) **Bar Chart** consists of disjointed rectangular bars drawn such that the height is equal to the frequency. The bars can be horizontal or vertical. Contrasting to the pie chart, it is simpler making comparison of the heights than of sectors. These are widely used by analysts to show the comparisons between the different elements included in the research.

d) **Histogram** it is similar to the bar chart but that the bars are linked to one another. The area of each rectangular bar is comparative to its frequency. The line connecting the midpoint of one bar to the other is known as the frequency polygon.

e) **Line Graph Data** can similarly be represented in the form of a line graph. The points on the line, denoted by any symbol designate the occurrence of the phenomenon of interest.

Dot Plot

It is a way of summarizing data, frequently used in exploratory data analysis to explain the major features of the distribution of the data in an appropriate form. A dot plot can assist detect any strange observations, or any gaps in the data set.

Conclusion

The knowledge of data collection procedures is necessary in simplicity of the data presentation. Equally, it is important to have adequate knowledge in the methods for data presentation, analysis and interpretation of the gathered data.