Follow the instructions in the table below to download your steps data from. Sep 07, 2014 in data analysis, there are procedures and tools to be employed depending on the type of research as well as the nature of the data to be analysed. Additional data book pages for the optional modules are available. Well chosen and well implemented methods for data collection and analysis. The designations employed and the presentation of material in this health. The mean represents the central tendency of the data set. No doubt, that it requires adequate and effective different types of data analysis methods, techniques, and tools that can respond to constantly increasing business research needs. There are different ways on how you can approach data analysis. The purpose of data analysis is to extract useful information from data and taking the decision based upon the data analysis. It also provides techniques for the analysis of multivariate data, speci. Data analysis is a process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusions and supporting decisionmaking. Descriptive analysis refers to the description of the data from a particular sample. However, this process can provide a lot of benefits especially if you want to. The presentation itself is mostly the same, and the data on it.
In addition to explaining the basis of quantitative analysis, the site also provides. Information technology it has developed rapidly during the last two decades or so. Your data analysis should be complete with all the information that can help you validate particular business moves or decisions. A financial presentation shows data that are gathered from actual sources, which means that it shows a nearly accurate representation of the companys situation in terms of its finances. Consensus baseline cluster 1 cluster 2 cluster 3 cluster 4 outliers consensus proportion 0. Data analysis is a process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusion and supporting decisionmaking. The analysis of the quantitative data was done with the help of ms excel and the qualitative data was analysed by converting the interviews into transcript using maxqda and through manual thinking. Data presentation for qualitative data is pretty straightforward.
Quantitative research methods are characterised by the collection of. At this point its a good idea to go up to file in the toolbar, click save as, and save this data. Regardless of the instrumentsmethods used in data collection, and whether the data is from sample or population, the first step in data analysis is to describe the collected data. 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. Statistics is the key element of any research activity, thus, implementing statistics at each step hypothesis development, study design, sampling data collection, data analysis, presentation of. Data presentation types type picture description proscons table a table shows the raw data presented in rows and columns. Continuous data continuous datais numerical data measured on a continuous range or scale.
Analytics covers a broader scope of knowledge areas and processes. 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. Descriptive statistics are numerical values obtained from the sample that gives meaning to the data. Data presentation the purpose of putting results of experiments into graphs, charts and tables is twofold.
For a novice, there is no difference between a static presentation and a data driven presentation. When you present numbers on your slides, you can expect two types of reactions from your audience. A common language for researchers research in the social sciences is a diverse topic. The purpose of this study was to identify factors contributing to.
Moreover, a financial presentation may also discuss the financial goals, objectives, and expectations of the company being set so that appropriate measures and procedures will be followed. Objectivesafter studying this lesson you are expected to. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and. Examine missing data by variable by respondent by analysis if no problem found, go directly to your analysis if a problem is found. Be able to present the results of your collected data. Examples of continuous data are a persons height or weight, and temperature. It is a messy, ambiguous, timeconsuming, creative, and fascinating process.
Data analysis, interpretation, and presentation anna loparev intro hci 022620 qualitative vs. Its overall emphasis has been on the processes, stages, and goals of conventional. Ready means that the data are as complete, errorfree, and readable as possible. Presentation of data requires skills and understanding of data. The purpose of putting results of research into graphs, charts and tables is twofold. Introduction to data analysis for auditors and accountants. The range is the difference between the highest and lowest values in a set of data. The decision is based on the scale of measurement of the data. Pros shows all data precise cons can be hard to interpret or see patterns pie chart a pie chart shows data as a. What we want to do is give the reader a sense of the process of data analysisa learning process achieved througb comparing. Data collection and analysis methods in impact evaluation page 2 outputs and desired outcomes and impacts see brief no. But if your organization is at terrible risk, now is the time to use our templates. Doing qualitative data analysis introduction once you have collected data, what do you do with it.
How free trade agreements are gradually changing trading patterns on the peninsula by. In fact, analytics include analysis of data within its procedures. Pdf qualitative data collection, analysis and presentation. Not everyone in your audience likes to crunch numbers. Delete the cases with missing data try to estimate the value of the missing data. The results so obtained are communicated, suggesting conclusions, and supporting decisionmaking. Important concepts underpinning the analysis and presentation of experimental data are reinforced with worked examples followed by student exercises. However, this process can provide a lot of benefits especially if you want to know how separate components affect the data that you would like to observe and evaluate. The factor analysis grouped various items across sections of the questionnaire into relevant categories of reasons for. The theory of change should also take into account any unintended positive or negative results.
Data analysis is the process of bringing order, structure and meaning to the mass of collected data. Ensuring data quality also extends to ensuring appropriate data analysis and presentation of the data in. Analysis of the properties of a food material depends on the successful completion of a number of different steps. Qualitative and quantitative research techniques for. The who steps team provides a suite of data analysis tools to assist you. In data analysis, there are procedures and tools to be employed depending on the type of research as well as the nature of the data to be analysed. Data analysis can enable auditors to focus on outliers and exceptions, identifying the riskiest areas of the audit. Data analysis is defined as a process of cleaning, transforming, and modeling data to discover useful information for business decisionmaking.
Presentation, analysis and interpretation of data presented by. If youre giving a highlevel presentation to decisionmakers who need hard data and proper analysis, then this free template pack may be what youre looking for. Qualitative data analysis is a search for general statements about relationships among. A data analysis, like a business analysis report, must carry all the key points of your desired presentation. The first part, which is based on the results of the questionnaire, deals with a quantitative analysis of data. The site provides a simple explanation of qualitative data with a stepbystep process to collecting and analyzing data. The presentation itself is mostly the same, and the data on it, is dynamic. Technology has transformed business processes and created a wealth of data that can be leveraged by accountants and auditors with the requisite mindset. From the back cover this book is designed as a supplementary text for students beginning study in the physical sciences and engineering at tertiary institutions. Data graphics are a good way to communicate important data in your reports. Second, it is usually the best way to show the data to others. 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.
Data presentation and analysis forms an integral part of all academic studies, commercial, industrial and marketing activities as well as professional practices. Having to look over your data to check where you missed some points is complex. Qualitative data analysis qda is the process of turning written data. Data analysis, interpretation, and presentation pcori.
Data analysis with a good statistical program isnt really difficult. For example, in fall, 1994, i asked the members of the data analysis and modeling. Conclusions made from the analysis of quantitative data indicate. This chapter comprises the analysis, presentation and interpretation of the findings resulting from this study. In part, this is because the social sciences represent a wide variety of disciplines, including but not limited to psychology. By default, text has been kept to a minimum, so theres nothing to read off the slides. 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. Data analysis is a process of collecting, transforming, cleaning, and modeling data with the goal of discovering the required information. It does not require much knowledge of mathematics, and it doesnt require knowledge of the formulas that the program uses to do the analyses.
Reading lots of numbers in the text puts people to sleep and does little to convey. Each of the 9 slides included in this pack all include a number of charts and diagrams. Epi info is a free software package developed by the us centers for disease. In continuous data, all values are possible with no gaps in between. Its development has, in turn, impacted significantly on the techniques for designing and implementing survey processing systems. Oct 28, 2012 presentation and analysis and interpretation of data 1. First, it is a visual way to look at the data and see what happened and make interpretations. In other words, these summarize the data and describe sample characteristics. But alone it does not really gives us an idea of how the data is distributed. Manual of standard operating procedures for sample.
It is necessary to make use of collected data which is considered to be raw data which must be processed to put for any. How to do data presentation, analysis and discussion. Qualitative analysis data analysis is the process of bringing order, structure and meaning to the mass of collected data. Describe the data analysis processes in a qualitative study.
Ppt methods of data presentation and analysis powerpoint. 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. Learn 5 ways to make your audience understand your message in 2 seconds or less. Factor analysis of all items listed in the questionnaires was performed. This means that analytics helps an analysis method to be understood easier, and to be more effective. The analysis and interpretation of data is carried out in two phases.