Importance Of Data Interpretation

Data interpretation is drawing conclusions and inferences from a comprehensive data presented numerically in tabular form by means of an illustration, viz. Graphs, Pie Chart e

According to C. William Emory, “Interpretation has two major aspects namely establishing continuity in the research through linking the results of a given study with those of another and the establishment of some relationship with the collected data. Interpretation can be defined as the device through which the factors, which seem to explain what has been observed by the researcher in the course of the study, can be better understood. Interpretation provides a theoretical conception which can serve as a guide for the further research work”.

With the increasing availability

Methods for data analysis and interpretation are needed that can cope with typical specifics of software engineering data.

(3) Combination of evidence:

Here, the focus is on aggregating evidence from multiple individual studies. Data or results from different individual studies are typically he

Bar Graphs:

A bar-diagram is essentially a graph converted into and presented in the form of rectangular blocks called as bars. These rectangular blocks have common width and hen

Pie Charts:

This is one of the most commonly used method of pictorial data interpretation. Pie charts show the relationship of parts to the whole. The central angle of a circle is 360°. The proportion that each part bears to the whole will be corresponding proportion of 360°, which is required to be calculated. Pie charts are useful for representing

(1) percentages of various elements with respect to the total

• Rigor is more difficult to maintain, assess, and demonstrate.

• The volume of data makes analysis and interpretation time consuming.

• It is sometimes not as well understood and accepted as quantitative research within the scientific community

• The researcher's presence during data gathering, which is often unavoidable in qualitative research, can affect the subjects' responses.

• Issues of anonymity and confidentiality can present problems when presenting findings

• Findings can be more difficult and time consuming to characterize in a visual way.

Quantitative Interpretation:

In quantitative data analysis you are expected to turn raw numbers into meaningful data through the application of rational and critical thinking. The same figure within data set can be interpreted in many different ways; therefore, it is important to apply fair and careful