RESEARCH DATA INTERPRETATION By Dr Zaryab Khalid Class

RESEARCH DATA INTERPRETATION By Dr. Zaryab Khalid Class: BS Botany Semester: 7 th Subject: Research Methodology

‘All meanings, we know, depend on the key of interpretation. ’ -George Eliot 2

Principles of Analysis and Interpretation �Data, as used in behavioral research, means research results from which inferences are drawn: usually numerical results, like scores of tests and statistics such as means, percentages, and correlation coefficients. �Analysis means the categorizing, ordering, manipulating, and summarizing of data to obtain answers to research questions. �Interpretation takes the results of analysis, makes inferences pertinent to the research relations studied, and draws conclusions about these relations.

Methods of data interpretation �Direct visual observations of raw data �After organizing the data in tables �After making Graphical representations �After calculations using numerical / statistical methods �After mathematical modelling

DAT �Data A is known to be crude information and not knowledge by itself. �The sequence from data to knowledge is: �from Data to Information, �from Information to Facts, and finally, �from Facts to Knowledge.

DAT �Data becomes information, when it becomes A relevant to your decision problem. �Information becomes fact, when the data can support it. �Facts are what the data reveals. �However the decisive instrumental (i. e. , applied) knowledge is expressed together with some statistical degree of confidence.

�Fact becomes knowledge, when it is used in the successful completion of a decision process. �massive amount of facts are integrated as knowledge.

�Usefulness and utility of research findings lie in proper interpretation. �Interpretation is a basic component of research. �After collecting and analyzing the data, the researcher has to accomplish the task of drawing inferences followed by report writing. �This has to be done very carefully, otherwise mis conclusions may be drawn and the whole purpose of doing research may get vitiated. �It is only through interpretation that the researcher can expose relations and processes that underlie his findings.

Meaning of Interpretation �Interpretation refers to the task of drawing inferences from the collected facts after an analytical and or experimental study. �In fact, it is a search for broader meaning of research findings. �The task of interpretation has two major aspects viz. , �the effort to establish continuity in research through linking the results of a given study with those of another, and the establishment of some explanation concepts.

�“In one sense, interpretation is concerned with relationships within the collected data, partially overlapping analysis. �Interpretation also extends beyond the data of the study to inch the results of other research, theory and hypotheses. ”

Interpenetration is the �Thus, interpenetration is the device through device which the factors that seem to explain what has been observed by researcher in the course of the study can be better understood and it also provides a theoretical conception which can serve as a guide for further researches.

Why Interpretation? �Interpretation is essential for the simple reason that the usefulness and utility of research findings lie in proper interpretation. �It is being considered a basic component of research process because of the following reasons:

Through interpretatio �It is through interpretation that the researcher can well understand the abstract principle that works beneath his findings. �Through this he can link up his findings with those of other studies, having the same abstract principle, and thereby can predict about the concrete world of events. Fresh inquiries can test these predictions later on. n �This way the continuity in research can be maintained.

Interpretation of the findings �The interpretation of the findings of exploratory research study often results into hypotheses for experimental research and as such interpretation is involved in the transition from exploratory to experimental research. �Since an exploratory study does not have a hypothesis to start with, the findings of such a study have to be interpreted on a post factum basis in which case the interpretation is technically described as ‘post factum’ interpretation.

Technique of Interpretation �The task of interpretation is not an easy job, rather it requires a great skill and dexterity on the part of researcher. �Interpretation is an art that one learns through practice and experience. �The researcher may, at times, seek the guidance from experts for accomplishing the task of interpretation.

The technique of interpretation � The technique of interpretationoften involves the following steps: ■ 1. ■ In fact, this is the techniqueof how generalization should be done and concepts beformulated. Researcher must give reasonable explanations of the relations which he/she has found and he/she must interpret the lines of relationship in terms of the underlying processes and must try to find out the thread of uniformity that lies under the surface layer of his diversified research findings.

2. Extraneous information, if collected during the study, must be considered while interpreting the final results of research study, for it may prove to be a key factor in understanding the problem under consideration.

3. It is advisable, before embarking upon final interpretation, to , consult someone having insight into the study and who is frank and honest and will not hesitate to point out omissions and errors in logical argumentation. Such a consultation will result in correct interpretation and, thus, will enhance the utility of research results. 4. Researcher must accomplish the task of interpretation only after considering all relevant factors affecting the problem to avoid false generalization. He /she must be in no hurry while interpreting results, for quite often the conclusions, which appear to be all right at the beginning, may not at all be accurate.

Precautions in Interpretation �One should always remember that even if the data are properly collected analyzed, wrong interpretation would lead to inaccurate conclusions. �It is, therefore, absolutely essential that the task of , interpretation be accomplished with patience in an impartial manner and also in correct perspective.

For correct interpretation �Researcher must pay attention to the following points for correct interpretation: (i)At the outset, researcher must invariably satisfy himself that (a) the data are appropriate, trustworthy and adequate for drawing inferences; (b) the data reflect good homogeneity; and that (c)proper analysis has been done through statistical methods. (ii) The researcher must remain cautious about the errors that can possibly arise in the process of interpreting results.

Errors can arise due to false generalization �Errors can arise due to false generalization and/or due to wrong interpretation of statistical measures, such as the application of findings beyond the range of observations, identification of correlation with causation. and the like. �Another major pitfall is the tendency to affirm that definite relationships exist on the basis of confirmation of particular hypotheses.

Researcher must remain vigilant �In fact, the positive test results accepting the hypothesis must be interpreted as “being in accord” with the hypothesis, rather than as “confirming the validity of the hypothesis”. �The researcher must remain vigilant about all such things so that false generalization may not take place. �He/she should be well equipped with and must know the correct use of statistical measures for drawing inferences concerning his study.

�Researcher must always keep in view that the task of interpretation is very much intertwined with analysis and cannot be distinctly separated. �As such he must take the task of interpretation as a special aspect of analysis and accordingly must take all those precautions that one usually observes while going through the process of analysis viz. , precautions concerning the reliability of data, computational checks, validation and comparison of results.

Data Interpretation Methods �Data interpretation may be the most important key in proving or disproving your hypothesis. �It is important to select the proper statistical tool to make useful interpretation of your data. �If you pick an improper data analysis method, your results may be suspect and lack credibility.

Visually scanning the data �Before doing any statistical analyses of the data you have collected, look closely at the data to determine the best method of organizing it. �By visually scanning the data and reorganizing it, you may be able to spot trends or other anomalies that may help you in your analysis of the data.

STATISTICS �Statistics is a science assisting you to make decisions under uncertainties (based on some numerical and measurable scales). �Decision making process must be based on data neither on personal opinion nor on any belief.

What is Statistical Data Analysis? �Data are not information! To determine what statistical data analysis is, one must first define statistics. �Statistics is a set of methods that are used to collect, analyze, present, and interpret data.

Statistical methods �Statistical methods are used in a wide variety of occupations and help people identify, study, and solve many complex problems. �In the business and economic world, these methods enable decision makers and managers to make informed and better decisions about uncertain situations.

�Using statistics to determine relationships is paramount to the success of good research. �Using tools such as ANOVA, correlations, Fisher Exact Tests, regression, etc. can predict whether or not your research hypothesis is satisfied. �But, REMEMBER to select your p-value before you begin your research project. �Doing this will add credibility to your research.

�One other important point to remember when doing data analysis is to use parametric statistics instead of nonparametric statistics whenever possible. �Remember that parametric statistics relies on the assumptions of normality, which gives greater power than nonparametric testing. �Both parametric and nonparametric statistical tests are used for interpretation.

Statistics consists of the principles and methods for �Designing studies �Collecting data �Presenting and analysing data �Interpreting the results �Statistics has been described as �Turning data into information �Data-based decision making.

Scientists interpret data based on their �Scientists interpret data based on their background knowledge and experience; thus, different scientists can interpret the same data in different ways. �By publishing their data and the techniques they used to analyze and interpret those data, scientists give the community the opportunity to both review the data and use them in future research.