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The primary data analysis is approached from the standpoint of what is required by your professor in your course and can be used later, if allowed, in journals. As a student, you would want your work to be impeccable and spectacular enough to be used by others for research. Common mistakes to avoid include use of standard error of the mean instead of standard deviation, use of standard deviation with skewed data, failure to describe any statistical test used (especially in a medical discipline) and multiple comparisons. Most students completing a Masters dissertation will need to include a methodology and analysis section. Your primary data Analysis - Correct statistical analysis of data is one of the most difficult aspects of your dissertation. No matter whether you are using a specific data analysis program such as SPSS or Linux, or whether you take a purely descriptive and non-technical approach, the analysis of primary data can be an intimidating and arduous task. If you plan to use a quantitative statistical analysis as part of your research project, every aspect of your experimental design must be checked against the statistical test you plan to apply. Students, particularly at master’s level, often come across serious problems when it comes to applying a valid and informative statistical test because their method did not meet the requirements of the test. For a student who fails to understand the above fundamentals well, our Company has a writing center which helps give Services like Undergraduate Dissertation Revising, MBA Dissertation Correction, Formatting and Reviewing Help by our brilliant Tutors. Please Review My Master’s Dissertation or have a look at my work and Proofread My Dissertation Paper, are some of the questions often posted at our Dissertation Proofreading Site. We give these queries the seriousness it deserves and accords it the appropriate help from our experienced Dissertation Proofreading Assistants. Our aim is to help you grow in your writing skills and therefore we give the ‘dos’ and ‘don’t’ strategies in writing to keep you in check.
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Outline of Analyzing Data: (chapter 4 or 5)
This is the process by which data is evaluated using both analytical and critical reasoning to study each element of the data obtained to get a helpful interpretation of the data.
Main Data Classification Methods by Our Data Analysts:
Qualitative data - This type of data involves explanation in statements and cannot be presented in forms of numbers. Qualitative data can be observed but cannot be measured.
Quantitative data – It is usually presented in numbers or quantified. Involves data that can be measured and be expressed in numeric values.
After data is collected, cleaned and analyzed, it becomes useful as it can be used in making of decisions in almost every sector in the research field.
Once data has been analyzed, it is helpful in it provides insights on how a problem identified can be solved and also creates a deeper comprehension of the problem.
Data Analysis Process
1. Data Interpretation:
This involves the explanation of the results of the research from the instruments used to collect data such as questionnaires and data that has been gathered from written sources which are then demonstrated graphically using graphs, models, curves, and figures.
The discussion involves a detailed explanation of what the findings of the research state. This process also entails providing indicative conclusions of the research findings.
3. Critical Data Analysis
Critical analysis is subjective writing where the writer evaluates the text. The writer creates a comparison of his work with other peoples’ work and pointing out its weaknesses and strengths and also explaining the meaning of the collected data.
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