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11+ Data Analysis Report Examples – PDF, Docs, Word, Pages
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Are you sure you want to Yes No. Yolanda Osborne Writing a good research paper isn't easy and it's the fruit of hard work.Matplotlib minor grid not showing
For help you can check writing expert. My professor asked me to write a research paper based on a field I have no idea about. My research skills are also very poor. I chose a writer who matched my writing style and fulfilled every requirement I proposed.To browse Academia. Skip to main content. Log In Sign Up.
Download Free PPT. Download Free PDF. Presentation, Analysis and Interpretation of data. Lovely Ann H Azanza.
Be able to present the results of your collected data. Make good analysis of the tabulated or graphically presented data, 3. Draw implications or inferences and generations from the analysis and interpretation of findings.
This chapter presents the findings of the study. Presentation should be clear and scholarly done and may come in the form of tables, figures or charts.
Analysis refers to the skill of the researcher in describing, delineating similarities and differences, highlighting the significant findings or data and ability to extract information or messages out of the presented data. The Format The immediate purpose of writing a research report is to tell other scientists about your work, about the new knowledge you have discovered.
The research report should be clear enough that any scientist could replicate your study without telephoning you to ask for details.
A Guide To The Methods, Benefits & Problems of The Interpretation of Data
In addition, the research must be explained clearly enough that a scientist could evaluate its merits and flaws, solely on the basis of the written word. The American Psychological Association APA has strict guidelines for the editorial style and organizational format of written research reports. There are accepted conventions for the mechanics of writing the report.Honda ecu identification
For example, how will you write the title of your table? Should the table number be written in Arabic or Roman numeral?
Will the title be indented and in capital letters or in small letters except the first letter of the key words? A more detailed discussion of the APA will be found in the last module dealing with references.Python pipe operator
Organization of your presentation The organization of the presentation and interpretation of findings vary according to the research method used.
In descriptive research, especially the survey type, the presentation of results follow a pattern. The findings presented will follow the sequence of the sub-problems raised in Chapter 1. It would be a good idea if reports assist in the analysis, interpretation and clarification of the next materials. Properly chosen, carefully drawn, and accurately presented, they can make many of the statements appearing in the body of the report more meaningful. Do not present your findings by recasting your sub- problems in Chapter 1.
Remember that your whole Chapter 4 is the exposition of the answers of findings to your research questions specially stated in Chapter 1. Your answers become the subheadings of your Chapter 4.
Examples: For Research Problem 1. What is the profile of the respondents in terms of age, sex, educational attainment, civil status and position? Your subheading in Chapter 4 should be: 1.To browse Academia.
Skip to main content. Log In Sign Up. Download Free PDF. Rodny Baula. These are presented in tables following the sequence of the specific research problem regarding the Effectiveness of Beat Patrol System in of San Manuel, Pangasinan.
The profile of the respondents was tabulated and computed according to the following: classification, age, sex, civil status, religion, educational attainment and occupation.
They also pointed out that the police force is not enough to protect the interest of the people in terms of safety. However, they are doing their best to protect the whole community of San Manuel, Pangasinan that is why they have a Beat Patrol System.
Under the age ranging years old, it got the highest frequency of and a percentage of 49 while, 19 years old to younger got the lowest frequency of 11 and a percentage of 2. This implies that age ranging 20 to 40 is more dominant compared to the youngsters. On the other hand, in sex, female got the highest frequency of with a percentage of 54 while, male got the frequency of with a percentage of This indicates that female are more conscious regarding to their safety compared to male.
It has been said that they are more conscious and they are family oriented. However, in civil status, married respoondents got the highest frequency of with a percentage of This implies that that married man is committed to give the basic necessity or physiological needs of man. They tend to find other ways for them to leave in this sinful world. Reyesstated that married man experiencing some difficulties in their lives because of these difficulties they tend to find some alternative to be able to survive.
In Religion, Roman Catholic got the highest frequency of with a percentage of These findings can be supported through observation and statistics that the majority of Filipino people believe to the doctrine of Roma Catholica.
Bardes and Oldendickexplained that in the course of studying the distribution of opinions among religious denomination, research have found that affiliation with a religion is not a very good predictor of opinion for many individuals. They also stated that Catholics differ considerably from the protestant Evangelicals because their views are considerably more liberal especially on social welfare issues.
This indicates that after attending in high school, majority of people of San Manuel cannot send their child in college because of lack of resources.
According to the police officers of this municipality, the reason why they cannot afford to send their child in tertiary after high school is poverty and because of this factor, majority of law violators are high school graduate. Finally, in occupation, housekeeper got the highest frequency of with a percentage of 26 while, pensioner got the lowest frequency of 2 with the percentage of 0.
The minimum requirement as stated in the job description is at least college graduate. This finding can be supported through observation and based on the crime statistics of the Philippine National Police. It can be gleaned in the table that the respondents perceived the Level of Effectiveness of Police Beat System in San Manuel, Pangasinan is high with the overall average weighted mean of 3.
Texting, 2.Data analysis and interpretation have now taken center stage with the advent of the digital age… and the sheer amount of data can be frightening.
Through the art of streamlined visual communication, data dashboards permit businesses to engage in real-time and informed decision making, and are key instruments in data interpretation. Data interpretation refers to the implementation of processes through which data is reviewed for the purpose of arriving at an informed conclusion. The interpretation of data assigns a meaning to the information analyzed and determines its signification and implications.
The importance of data interpretation is evident and this is why it needs to be done properly. Data is very likely to arrive from multiple sources and has a tendency to enter the analysis process with haphazard ordering. Data analysis tends to be extremely subjective. That is to say, the nature and goal of interpretation will vary from business to business, likely correlating to the type of data being analyzed.
Yet, before any serious data interpretation inquiry can begin, it should be understood that visual presentations of data findings are irrelevant unless a sound decision is made regarding scales of measurement.
Before any serious data analysis can begin, the scale of measurement must be decided for the data as this will have a long-term impact on data interpretation ROI. The varying scales include:. Once scales of measurement have been selected, it is time to select which of the two broad interpretation processes will best suit your data needs.
When interpreting data, an analyst must try to discern the differences between correlation, causation and coincidences, as well as many other bias — but he also has to consider all the factors involved that may have led to a result. There are various data interpretation methods one can use.
The interpretation of data is designed to help people make sense of numerical data that has been collected, analyzed and presented. Having a baseline method or methods for interpreting data will provide your analyst teams a structure and consistent foundation.
Indeed, if several departments have different approaches to interpret the same data, while sharing the same goals, some mismatched objectives can result.Interactive reader and study guide answer key
Disparate methods will lead to duplicated efforts, inconsistent solutions, wasted energy and inevitably — time and money. In this part, we will look at the two main methods of interpretation of data: with a qualitative and a quantitative analysis. Qualitative data analysis can be summed up in one word — categorical. With qualitative analysis, data is not described through numerical values or patterns, but through the use of descriptive context i.
Typically, narrative data is gathered by employing a wide variety of person-to-person techniques. These techniques include:. A key difference between qualitative and quantitative analysis is clearly noticeable in the interpretation stage.
Quantitative analysis refers to a set of processes by which numerical data is analyzed. More often than not, it involves the use of statistical modeling such as standard deviation, mean and median.
Typically, quantitative data is measured by visually presenting correlation tests between two or more variables of significance. Different processes can be used together or separately, and comparisons can be made to ultimately arrive at a conclusion. Other signature interpretation processes of quantitative data include:. Now that we have seen how to interpret data, let's move on and ask ourselves some questions: what are some data interpretation benefits?
Why do all industries engage in data research and analysis? The purpose of collection and interpretation is to acquire useful and usable information and to make the most informed decisions possible. From businesses, to newlyweds researching their first home, data collection and interpretation provides limitless benefits for a wide range of institutions and individuals.
Data analysis and interpretation, in the end, helps improve processes and identify problems. It is difficult to grow and make dependable improvements without, at the very least, minimal data collection and interpretation. What is the key word? Vague ideas regarding performance enhancement exist within all institutions and industries. Yet, without proper research and analysis, an idea is likely to remain in a stagnant state forever i.
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I look forward to many opportunities to partner with MWD to provide my clients with the best of the best. This process has been an absolute pleasure.This course is really a ""dream come true"" for me. In the real sense- This course is at par to what the researchers are working on. The subject of identifying anomalies is a central task of academic historians, and this course allowed me the welcome luxury to reflect on their nature and methods of discovery.
I also appreciate the incorporation of technology into the Intro Stats program - it's one thing to know the equations. This gives your courses a relevance often lacking in online Intro Stats offerings. This is the single most useful course I have ever taken in regards to helping me in the workplace.
SQL alone, which I had zero prior experience, is needed for almost every data analytics job I see. R is also ubiquitous and very imporatant. Great to learn how to use both together. I am very thankful to the course and assistant teachers.
I can only add that the course worth its effort and tuition. Truly wonderful educational experience. Professor Babinec did a wonderful job of leading us through this material. It is obvious that he has a passion for this subject. His breadth of knowledge of and experience with cluster analysis added significantly to the course. He gave very helpful answers in the discussion forum. Anuja, our teaching assistant, was very supportive throughout the course as well.
The course material was challenging but fulfilling, helping us appreciate the subtleties of cluster analysis rather than thoughtlessly plunge ahead.
In summary, this was a very satisfying and useful course. Since we are manipulating tons of data at the customer level for more than 27 countries, R would be the perfect complement tool (we have been using SAS) for customer analytics.
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