Here, we look at methods for producing graphical representations of. The process of data analysis includes checking the interview schedule, sorting out information, summarizing the data in tabular form, analyising the facts, interpreting the results or converting data into statements, proposition or conclusion and report writing and presentation. Many of the most appropriate types of data presentation techniques used to visualise raw geographical data are shown on this page. Nov 10, 2016 data security is the practice of protecting data in storage from unauthorized access, use, modification, destruction or deletion. For a novice, there is no difference between a static presentation and a data driven presentation. Data presentation types type picture description proscons table a table shows the raw data presented in rows and columns. Techniques for data collection technical workshop on survey methodology. First, it is a visual way to look at the data and see what happened and make interpretations.
Data presentation and analysis or data analysis and presentation. Statistical methods19 in combination with graphical representation form a powerful tool to analyze and communicate information processed data. You need to look up specific values users need precise values. Second, it is usually the best way to show the data to others. Chapter 6 methods of data collection introduction to methods.
Chapter 1 data representation techniques shodhganga. In analysis, we tend to use the same techniques everywhere because we. Widely used format and data presentation techniques are mentioned below. Data presentation and data representation are terms having similar meaning and importance.
Secondary data statistics not gathered for the immediate study at hand, but for some other purpose. Reading lots of numbers in the text puts people to sleep and does little to convey. As text raw data with proper formatting, categorisation, indentation is most extensively used and very effective way of presenting data. Program staff are urged to view this handbook as a beginning resource, and to supplement their knowledge of data analysis procedures and methods over time as part of their ongoing professional development. Objectives to introduce the key factors for successful presentation delivery to prepare effective visual aids to deliver successful presentations to evaluate presentation delivery.
Finally, the pdf is a file format developed by adobe systems adobe. For example, if we wanted to measure aggressive behavior in children, we could collect those data by observing children with our eyes, by using. In this article, the techniques of data and information presentation in. When data are more quantitative, such as 7 out of 10 cells were dead, a. The bar chart is one of the most common methods of presenting data in a. Any of several methods of designating classes may be used depending in part on the nature of the data. Enabling environment for sustainable enterprises in indonesia hotel ibis tamarin, jakarta 46 may 2011 presentation by mohammed mwamadzingo, iloactrav geneva 1 the research process topic statement of the research problem objectives research questions. A frequency table is used to summarize categorical or numerical data. Data security is the practice of protecting data in storage from unauthorized access, use, modification, destruction or deletion. Geography resources for teachers royal geographical society.
Text is the principal method for explaining findings, outlining trends. Oral presentation techniques 2 oral presentation techniques. Geography data presentation techniques and methods. With large amounts of data graphical presentation methods are often clearer to understand.
We want to have indications of the data variability. The most common way of presentation of data is in the form of statements. It is a messy, ambiguous, timeconsuming, creative, and fascinating process. Frequency tables are useful methods of presenting data. It is a level of information security that is concerned with protecting data stores, knowledge repositories and documents.
There are many variations on the basic bar chart, such as divided bar chart, percentage bar chart and bipolar analysis. In the collection of data we have to be systematic. Not everyone in your audience likes to crunch numbers. The designations employed and the presentation of material in this health information product, including maps and other illustrative materials, do not imply the expression of any opinion whatsoever on the part of. Your findings can be presented with a range of graphical and mapping techniques. Adding visual aspect to data or sorting it using grouping and presenting it in the form of table is a part of the presentation. Tuftes five secrets find good examples and copy them. Tuftes five secrets find good examples and copy them order data by performance, not alphabetically convert numbers to graphics whenever possible demonstrate your interest establish your credibility. Tools and techniques of data collection guide to social work. Data presentation and analysis forms an important part of all academic studies, commercial, industrial and marketing activities as well as professional practices. This chapter gives some guidelines and techniques for water quality data analysis and presentation. Data collection techniques data collection techniques allow us to systematically collect information about our objects of study people, objects, phenomena and about the settings in which they occur. Should be used for small datasets for comparison, e.
Emphasis is placed on the simpler methods, although the more complex. Pie chart, bar chart, line graphs, geometrical diagrams 1. But alone it does not really gives us an idea of how the data is distributed. If data are collected haphazardly, it will be difficult to answer our research. Various methods of data presentation can be used to present data and facts. Data presentation and analysis forms an integral part of all academic studies, commercial, industrial and marketing activities as well as professional practices. Learn 5 ways to make your audience understand your message in 2 seconds or less. Chapter 6 methods of data collection introduction to. Learn vocabulary, terms, and more with flashcards, games, and other study tools. Isopleth maps differ from choropleth maps in that the data is not grouped to a predefined unit like a city district. Start studying data presentation methods advantages and disadvatages. Data presentation methods advantages and disadvatages. The range is the difference between the highest and lowest values in a set of data.
Effective data presentation skills are critical for being a world class financial analyst. Techniques for data presentation are broadly classified in two ways. When you present numbers on your slides, you can expect two types of reactions from your audience. Data presentation the purpose of putting results of experiments into graphs, charts and tables is twofold. In this article, the techniques of data and information presentation in textual, tabular, and graphical forms are introduced. The data rich, information poor syndrome is common in many agencies, both in developed and developing countries. This requires focusing on the main points, facts, and recommendations that will prompt necessary action from the audience.
The following are common data security techniques and considerations. A student guide to the a level independent investigation non examined assessment nea download a copy of our guide. Sampling is a procedure, where in a fraction of the data is taken from a large set of data, and the inference drawn from the sample is extended to whole group. The presentation itself is mostly the same, and the data on it, is dynamic. Data can be presented in various forms depending on the type of data collected. Qualitative data analysis is a search for general statements about relationships among categories of data. When data are more quantitative, such as 7 out of 10 cells were dead, a table is the preferred form. Its purpose is to guide the proposal writer in stipulating the methods of choice for his study and in describing for the reader how the data will inform his research questions. Raw data data sheets are where the data are originally recorded. Data analysis is the process of bringing order, structure and meaning to the mass of collected data. Data presentation guide best visuals, charts and storytelling. Famous quote from a migrant and seasonal head start mshs staff person to mshs director at a. The mean represents the central tendency of the data set.
A frequency distribution is a table showing how often each value or set of values of the variable in question occurs in a data set. When viewed by light microscopy, all of the cells appeared dead. How the researcher plans to use these methods, however, depends on several considerations. Pros shows all data precise cons can be hard to interpret or see patterns pie chart a pie chart shows data as a. Before the calculation of descriptive statistics, it is sometimes a good idea to present data as tables, charts, diagrams or graphs. Search for evidence using all tools available confirmatory.
It is necessary to make use of collected data which is considered to be raw data which must be processed to put for any. Exploratory data analysis pioneer john tukey new approach to data analysis, heavily based on visualization, as an alternative to classical data analysis see its bio two stage process. Presentation of data requires skills and understanding of data. The tools provided to automatically generate the images below are all very quick and easy to use. Lines of equal value are drawn such that all values on one side are higher than the isoline value and all values on the other side are lower, or. The range is the difference between the highest and lowest values in a. Introduction to methods of data collection by now, it should be abundantly clear that behavioral research involves the collection of data and that there are a variety of ways to do so.
Objectives to introduce the key factors for successful presentation delivery. Primary data data originated by the researcher for the purpose of the investigation at hand. In the absence of data on the subject, a decision taken is just like leaping into the dark. The key to understanding the different facets of data mining is to distinguish between data mining applications, operations, techniques and algorithms. Criteria and goals first, we need to look at what data presentation and communication mean in terms of what we expect from the techniques.
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