What is the meaning of data interpretation

what is the meaning of data interpretation

Data Analysis - Overview

May 30, Data analysis and interpretation is the process of assigning meaning to the collected information and determining the conclusions, significance, and implications of the findings. "Data analysis is the process of bringing order, structure and meaning to the mass of collected data. It is a messy, ambiguous, time-consuming, creative, and fascinating process. It does not proceed in a linear fashion; it is not neat. Qualitative data analysis is a search for general statements about relationships among categories of data.".

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Are you sure you want to Yes No. Roselle Mae Causing. Show More. No Downloads. Views Total views. Actions Shares. No notes for slide. Presentation, analysis and interpretation of data 1. Chapter IV 2. Presentation 2. Analysis 3. Interpretation 3. Textual - statements with numerals datw numbers that serve as supplements to tabular presentation 5. Tabular - a systematic arrangement of related idea in which classes of numerical facts or data are given each row and their subclasses are given each a column in order to present the relationships of the sets or numerical facts or data in a definite, compact and understandable form 6.

The table should be so constructed that it xata the reader to comprehend te data presented without meanning to interpretqtion text; 2. The text should be so written that it allows the reader to understand the argument presented without referring to the table. Campbell, Ballou and Slade, 7. Graphical a chart representing the quantitative variations or changes of variables in pictorial or interprdtation form 8.

Bar graphs 2. Linear graphs 3. Pie graphs 4. Pictograms wgat. Statistical maps 6. Ratio charts 9. Calderon, Qualitative Analysis is not based on precise measurement and quantitative claims. PSSC: 51 Social analysis; 2. From the biggest to the smallest class; 3.

Most important to the least important; 4. Ranking of students according to brightness; Quantitative Analysis is employed on data that have been assigned some numerical value. What do the results of the study mean? This part is, perhaps, the most critical aspect of the research report.

How do we interpret the result s of our study? Tie up the results of the study in both theory and application by pulling together the: a. Examine, summarize, interpret and justify the results; then, draw inferences. Consider the following: Integrate your findings into a principle; 2. Integrate a theory into your findings; and 3. Use these findings to formulate an how to change credit card information on nook theory Recommend or apply alternatives As reflected in the table, there was 4.

As observed, there was indeed 5. Delving deeper into the figures In explaining this result, interprteation can be stated that 8. Is significantly related interpretatipn 9.

Is found to be determinant of Registered positive correlation with Is revealed to influence Has significant relationship with Is discovered to be a factor of And in viewing in what are sexually transmitted diseases sense, it can be stated that The result establishes the fact that This finding suggests that With this result, the researcher developed an impression that This finding also validates the findings of These findings wyat accept js framework of the study Nevertheless, this finding could be attributed to the fact that Probably, this was also influenced In the rational sense, the juxtaposition of The chapter is organized and divided into several main components or topics, each of which is titled according to the sub-problem or hypothesis statement.

Present only relevant data. In reporting data, choose the medium that will present them effectively. Presenting tables that can be presented as well in a few or in the text must be avoided. The textual presentation should supplement or expand the contents of tables and charts, rather than duplicate them. Only objective data embodied in tables are made the bases of discussion.

The analysis of the data should be objective and logical. In reporting statistical tests of significance, include information concerning the value of what is youth violence essay test, the degree of freedom, the probability level and the direction of the effect. The findings are compared and contrasted with that of other previous studies and interpretations are made thereof.

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Analyzing Data

Data (the plural form of the word datum) are scientific observations and measurements that, once analyzed and interpreted, can be developed into evidence to address a question. Data lie at the heart of all scientific investigations, and all scientists collect data in one form or another. The usual step proceeding data analysis is interpretation. Interpretation involves attaching meaning and significance to the analysis, explaining descriptive patterns, and looking for relationships and linkages among descriptive dimensions. Mar 15, Data analysis is the process of interpreting the meaning of the data we have collected, organized, and displayed in the form of a table, bar chart, line graph, or other representation. The process involves looking for patternssimilarities, disparities, trends, and other relationshipsand thinking about what these patterns might mean.

The world is becoming more and more data-driven, with endless amounts of data available to work with. Big companies like Google and Microsoft use data to make decisions, but they're not the only ones. Data analysis is used by small businesses, retail companies, in medicine, and even in the world of sports.

It's a universal language and more important than ever before. It seems like an advanced concept but data analysis is really just a few ideas put into practice. Data analysis is the process of evaluating data using analytical or statistical tools to discover useful information. Some of these tools are programming languages like R or Python.

Microsoft Excel is also popular in the world of data analytics. Once data is collected and sorted using these tools, the results are interpreted to make decisions.

The end results can be delivered as a summary, or as a visual like a chart or graph. The process of presenting data in visual form is known as data visualization. Data visualization tools make the job easier. There are several data analysis methods including data mining, text analytics, and business intelligence. Data mining is a method of data analysis for discovering patterns in large data sets using statistics, artificial intelligence, and machine learning.

The goal is to turn data into business decisions. What can you do with data mining? You can process large amounts of data to identify outliers and exclude them from decision making. Businesses can learn customer purchasing habits, or use clustering to find previously unknown groups within the data. If you use email, you see another example of data mining to sort your mailbox. Email apps like Outlook or Gmail use this to categorize your emails as "spam" or "not spam".

Data is not just limited to numbers, information can come from text information as well. Text analytics is the process of finding useful information from text. You do this by processing raw text, making it readable by data analysis tools, and finding results and patterns.

This is also known as text mining. Excel does a great job with this. Excel has many formulas to work with text that can save you time when you go to work with the data. Text mining can also collect information from the web, a database or a file system. What can you do with this text information? You can import email addresses and phone numbers to find patterns. You can even find frequencies of words in a document.

Business intelligence transforms data into intelligence used to make business decisions. It may be used in an organization's strategic and tactical decision making. It offers a way for companies to examine trends from collected data and get insights from it.

Data visualization is the visual representation of data. Instead of presenting data in tables or databases, you present it in charts and graphs. It makes complex data more understandable, not to mention easier to look at.

Increasing amounts of data are being generated by applications you use Also known as the "Internet of Things".

The amount of data referred to as "big data" is pretty massive. Data visualization can turn millions of data points into simple visuals that make it easy to understand. The visualization of Google datasets is a great example of how big data can visually guide decision-making. Data analysis is used to evaluate data with statistical tools to discover useful information.

A variety of methods are used including data mining, text analytics, business intelligence, combining data sets , and data visualization. The Power Query tool in Microsoft Excel is especially helpful for data analysis. If you want to familiarize yourself with it, read our guide to create your first Microsoft Power Query script. Is your Android phone overheating? Here's why your phone gets hot, how to cool it down, and keep it from heating up again.

Anthony Grant is a freelance writer covering Programming and Software. He's a Computer Science major dabbling in programming, Excel, software, and technology.

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