Nndata presentation and analysis procedures pdf

The purpose of putting results of research into graphs, charts and tables is twofold. Presentation of data requires skills and understanding of data. Top tips on analysing data and presenting findings for your. Create marketing content that resonates with prezi video. Introduction to statistics 2 statistics statistics is the body of techniques used to facilitate the collection, organization, presentation, analysis, and interpretation of data for the purpose of making better decisions. Qualitative data analysis is a search for general statements about relationships among. Adding visual aspect to data or sorting it using grouping and presenting it in the form of table is a part of the presentation. The informationtheoretic and bayesian methods offer alternative approaches to data analysis and inference compared to traditionally used methods. Textual statements with numerals or numbers that serve as supplements to tabular presentation 5. Purpose of this training to increase your skills in analysis and interpretation of the information you collect to increase your ability to report your findings to a variety of audiences to learn how to make evaluation results actionable three steps to data analysis keep it simple aim for a systematic effort keep your audience in mind pay attention. First, it is a visual way to look at the data and see what happened and make interpretations. The natural way of presenting this type of data is by using a frequency distribution that is, a tabulation or tally of the number of observations in the data set that fall into each group. Sasstat software provides two approaches for modeling longitudinal data. Data presentation and analysis or data analysis and presentation.

It involves understanding flows of resources in different sectors of the economy as depicted in figure 1. Be able to present the results of your collected data. Taking a handson approach, each of these key areas is. Data representations, analysis, and interpretation sas. Pros shows all data precise cons can be hard to interpret or see patterns pie chart a pie chart shows data as a.

Data presentation types type picture description proscons table a table shows the raw data presented in rows and columns. Ppt data analysis, interpretation and presentation. Data presentation the purpose of putting results of experiments into graphs, charts and tables is twofold. Learn the 5 tips to make your presentation clearer and more memorable. Data graphics are a good way to communicate important data in your reports. The decision is based on the scale of measurement of the data. Oct 28, 2012 presentation and analysis and interpretation of data 1. Presenting outcomes data clearly and effectively paul chandler, volunteer data analyst, astt, baltimore maryland. For example, in fall, 1994, i asked the members of the data analysis and modeling. These two go hand in hand, and it will be difficult to provide a complete differentiation between the two. An introduction for the life and medical sciences is an invaluable text allowing students to develop appropriate key skills when designing experiments, generating results, analysing data and ultimately presenting findings to academics and referees. The theory of change should also take into account any unintended positive or negative results.

Common mistakes in data presentation perceptual edge. Data analysis, interpretation and presentation overview qualitative and quantitative simple quantitative analysis simple qualitative analysis tools to support data analysis theoretical frameworks. The purpose of this study was to identify factors contributing to. Chapter to appear in stevens handbook of experimental. Most presenters use vague slide titles like our sales performance. Next, i discuss a collection of topics that represent some supplements andor alternatives to the kinds of standard analysis procedures about which i will have just complained. Delete the cases with missing data try to estimate the value of the missing data. Closeup, anchor and dabur, as the p value is less than the significance level 0. Although one might argue that any desired information could be obtained solely through interviews, it is important to note that. Is the process of organizing data into logical, sequential and meaningful categories and classifications to make them amenable to study and interpretation. Data collection and analysis methods in impact evaluation page 2 outputs and desired outcomes and impacts see brief no. Download data analysis powerpoint templates and backgrounds for presentations in microsoft powerpoint. Analysis, presentation, and interpretation of data by gie. Statistical analysis of longitudinal data requires an accounting for possible betweensubject heterogeneity and withinsubject correlation.

Qualitative analysis expresses the nature of elements and is represented as. Presentation, analysis and interpretation by jenny. Activities 1, 3, and 4 should be evaluated by appropriateness of presentation and strength of reasoning that supports the choice. Mastering business data collection, analysis and presentation. Missing data analysis examine missing data by variable by respondent by analysis if no problem found, go directly to your analysis if a problem is found. The mastering business data collection, analysis and presentation training course will benefit employees and managers who are involved in collection, analysis and communication of business data and information and wish to be able to develop robust and justified business solutions and convince stakeholders to support their recommendations. Creation of word problems, graphs, and accompanying questions will demonstrate the quality of their representations of data.

Data analysis, interpretation, and presentation anna loparev intro hci 022620 qualitative vs. Qda qualitative data analysis rfp request for proposals. In the third section data obtained from the analysis of the death attitude and death anxiety scales will be examined and the association between the two variables discussed. Second, it is usually the best way to show the data to others. Perceptual edge common mistakes in data presentation page 3 figure 1 shows an example on the left taken from visual minings website of a graph thats inappropriate for the message, compared to one that i made on the right to illustrate a more appropriate choice. C hapters 3 through 5 contain ed specific data reduction and quality control procedures for each data collection t echnique. Presentations, analysis and interpretation of data 125 chapter4 presentation, analysis and interpretation of data data analysis is the process of bringing order, structure and meaning to the mass of collected data. Data analysis with a good statistical program isnt really difficult. Bayesian analysis paradigms, followed by several general suggestions.

Explain the significance of these results and this analysis for the bleeding disorders community. It is a messy, ambiguous, time consuming, creative, and fascinating process. Reading lots of numbers in the text puts people to sleep and does little to convey. Qualitative analysis data analysis is the process of bringing order, structure and meaning to the mass of collected data. Generally, all quantified data are tallied first in talligram which are then converted into statistical tables for data presentation using hinduarabic numerals in the cells in place of tallies. Data collection research methodology is the system of collecting data for research projects, either theoretical or practical research. Top tips on analysing data and presenting findings for your education research project 3 the extent of similarity and disagreement for each statement, as was done in similar research by jones 2009. The procedures in earlier chapters were aimed at producing a common travel. Section two is the analysis of, and findings on, organisational types as generated by the main questionnaire. It does not require much knowledge of mathematics, and it doesnt require knowledge of the formulas that the program uses to do the analyses. Presentation and analysis and interpretation of data. Two questionnaires, one for diabetic patients and the other for. It is necessary to make use of collected data which is considered to be raw data which must be processed to put for any. The discussion provides interpretation of data and observations.

Data presentation and descriptive statistics paola grosso sne research group. This doesnt give the audience any clue about what to look for in the sea of numbers presented on the slide. Project results include a presentation of all relevant data in narrative, tabular, and graphical forms. It is a messy, ambiguous, timeconsuming, creative, and fascinating process. Chapter 3 presents the detailed analysis plan, including the hypotheses to be tested, impact estimation model, strategy for addressing multiple comparisons, subgroup analysis, addressing noshows and crossovers, and sample sizes and statistical power. Use the predesigned analyses to obtain your data analysis results faster and more reliably at the click of a button. Guidance is lacking on the presentation of results under these alternative procedures and on nontesting aspects. Observations observations are essential in qualitative studies because they allow the researcher to witness certain patterns of behavior. Ppt data analysis and interpretation level of measurement. A free powerpoint ppt presentation displayed as a flash slide show on id.

Should be used for small datasets for comparison, e. Qualitative data analysis free download as powerpoint presentation. We are going to talk about data presentation, analysis and basic statistics. There are a number of broader considerations that you need to take into account during the data analysis process. Qualitative data analysis qualitative research data. Ppt data analysis and interpretation free download as powerpoint presentation. Data analysis is defined by the statistician john tukey in 1961 as procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of mathematical statistics which apply to analyzing. View homework help collection and analysis presentation 1 from cja 335 at university of phoenix. Quantitative analysis numerical methods to ascertain size, magnitude, amount. Presentation and analysis and interpretation of data 1. Ppt methods of data presentation and analysis powerpoint. Data presentation and analysis forms an integral part of all academic studies, commercial, industrial and marketing activities as well as professional practices.

Figure 2 may now be converted into a statistical table for data presentation. Data presentation for qualitative data is pretty straightforward. Data analysis and presentation how is data analysis and. Objectivesafter studying this lesson you are expected to. Proposal for analysis of udc data, 2012 page 4 of 4 proposal for analysis of udc data appendix a. Before the calculation of descriptive statistics, it is sometimes a good idea to present data as tables, charts, diagrams or graphs. Consensus baseline cluster 1 cluster 2 cluster 3 cluster 4 outliers consensus proportion 0. Data presentation, analysis and interpretation school of management studies, cusat 105 result indicates that the most favourite brand, colgate has a significant difference over other brands. A quantitative, descriptive survey design was used to collect data from subjects. Data collection, presentation and analysis aa s is obvious, the basis of a resourcebased plan is data, and quite a lot of that.

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