# Introduction to research Analyzing and interpreting research data

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Introduction to research 1703423-2 Analyzing and interpreting research data
Dr Naiema Gaber

Analyzing and interpreting research data The learning objectives
After this lecture the student will be able to: Define data analysis procedures Describe how to prepare and organize the data for analysis Explain the coding process of the data Differentiate the types of Statistics Determine ways of representing and reporting the findings Discuss how to interpret the findings Identify methods of validating the accuracy and credibility of the findings Describe how to draw conclusions

DATA ANALYSIS PROCEDURES
Data analysis is an eclectic process. Occurs simultaneously with data collection, data interpretation and report writing. Is based on the on data reduction and interpretation It can be manual or computerized

Preparing data for analysis
 scoring: assigning a total to each participant’s instrument  tabulating: organizing the data in a systematic manner  coding: assigning numerals (e.g., ID) to data

How do You Prepare and Organize the Data?
Develop a matrix to organize the material Organize material by type Keep duplicate copies of materials Transcribe (copy out) data Prepare data for hand or computer analysis (and select computer program) Educational Research 2e: Creswell

How do you Explore and Code the Data?
Obtain a general sense of the data by performing a preliminary exploratory analysis Memo ideas Consider whether more data are needed Coding the data Educational Research 2e: Creswell

Identify text segments – ask “what is this person saying?” Bracket text segment Assign code word Reduce redundancy (unemployment data) Collapse codes into themes Educational Research 2e: Creswell

A Visual Model of the Coding Process in Qualitative Research
Reduce Codes to 5-7 Themes Initially read through data Divide text into segments of information Label segments of information with codes Reduce Overlap and redundancy of codes Collapse codes into themes Many Pages of Text Segments 30-40 codes Codes reduced to 20 Educational Research 2e: Creswell

How do You Use Codes to Build Description?
Describe People Events Activities Processes Educational Research 2e: Creswell

Managing Data Regardless of data type, managing data involves
familiarizing yourself with appropriate software developing a data management system systematically organizing and screening data entering the data into a program ‘cleaning’ your data do right statistics (descriptive or Inferential) O'Leary, Z. (2005) RESEARCHING REAL-WORLD PROBLEMS: A Guide to Methods of Inquiry. London: Sage. Chapter 11.

Statistics It’s important for researchers to be familiar with the language and logic of statistics, and be competent in the use of statistical software. O'Leary, Z. (2005) RESEARCHING REAL-WORLD PROBLEMS: A Guide to Methods of Inquiry. London: Sage. Chapter 11.

Descriptive Statistics
Descriptive statistics are used to summarize the basic feature of a data set through measures of central tendency (mean, mode, and median) dispersion (range, quartiles, variance, and standard deviation) distribution (skewness and kurtosis) O'Leary, Z. (2005) RESEARCHING REAL-WORLD PROBLEMS: A Guide to Methods of Inquiry. London: Sage. Chapter 11.

Inferential Statistics
Inferential statistics allow researchers to assess their ability to draw conclusions that extent beyond the immediate data, e.g. if a sample represents the population if there are differences between two or more groups if there are changes over time if there is a relationship between two or more variables O'Leary, Z. (2005) RESEARCHING REAL-WORLD PROBLEMS: A Guide to Methods of Inquiry. London: Sage. Chapter 11.

Selecting Statistical Tests
Selecting the right statistical test relies on knowing the nature of your variables their scale of measurement their distribution shape types of question you want to ask O'Leary, Z. (2005) RESEARCHING REAL-WORLD PROBLEMS: A Guide to Methods of Inquiry. London: Sage. Chapter 11.

How to present data Graphs (frequency polygon, pie chart, boxplot, stem-and-leaf chart) Measures of central tendency (modem, median, mean Measures of variability (range, quartile deviation, variance, standard deviation) Measures of relative position (percentile ranks, standard scores) Measures of relationship (Spearman Rho, Pearson r

How do You Represent Findings?
Comparison table Descriptive table Hierarchical tree Figures/diagrams Drawings Educational Research 2e: Creswell

How do You Interpret Findings?
Interpretation is not neutral Reflect about the personal meaning of the data Compare and contrast personal viewpoints with the literature Address limitations of the study Make suggestions for future research Educational Research 2e: Creswell

How do You Validate the Accuracy of Your Findings?
Member checking: Members check the accuracy of the account Triangulation: Using corroborate evidence External: Hiring the services of an individual outside the study to review the study Educational Research 2e: Creswell

Drawing Conclusions Your findings and conclusions need to flow from analysis and show clear relevance to your overall project Findings should be considered in light of significance current research literature limitations of the study your questions, aims, objectives, and theory O'Leary, Z. (2005) RESEARCHING REAL-WORLD PROBLEMS: A Guide to Methods of Inquiry. London: Sage. Chapter 11.

Summary of the lecture steps of data analysis include:
Preparing data for analysis by scoring, tabulating and coding. Managing Data, by choosing the appropriate software, developing a data management system, systematically organizing and screening data, entering the data into a program and the Selecting right statistical test Interpret Findings Validate the accuracy of findings Draw Conclusions present data

Feedback questions Put T if the statement is true and F if it is false 1- The analysis of the data is as important as any other component of the research process T F 2-Data analysis is an eclectic process based on the on data reduction and interpretation 3- The first step in data analysis is to describe, or summarize, the data using descriptive statistics 4- To test a hypothesis adequately, more than descriptive statistics are normally needed 5- Tabulating: organizing the data in a systematic manner

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