Techniques for data analysis Technical workshop on survey - - PDF document

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Techniques for data analysis

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Technical workshop on survey methodology: Enabling environment for sustainable enterprises in Indonesia

Hotel Ibis Tamarin, Jakarta 4-6 May 2011 Presentation by Mohammed Mwamadzingo, ILO/ACTRAV Geneva

The research process

• Topic
• Statement of the problem
• Objectives
• Research Questions
• Literature review
• Data collection
• Data Analysis
• Report writing

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Data analysis

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The data analysis process includes

• data sorting,
• data editing,
• data coding,
• data entry,
• data cleaning,
• data processing and
• interpretation of the results.

Data analysis

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• 1. Data Sorting-involves the rearrangement of

the collected data to allow systematic

• handling. It’s the beginning of detection,

correction and avoidance of errors

• 2. Data Editing-Involves reading through the

filled questionnaires (primary data), records to spot any inconsistencies and/or errors which

• ccurred during data collection..

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Data analysis

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• Data coding-Process of creation of dummy

variables names (short names assigned to each study variable). The code allows the researcher to minimize errors during data entry and processing and provides easy interpretations of results.

• Data Entry-the actual keying of data according

to the assigned codes. It requires a high degree of keenness and patience.

Data analysis

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• Data Cleaning-Involve conducting a final check
• n the data file for accuracy, erroneous data,

completeness and consistency.

• Data Processing-subjected the prepared data

to the software processor which then manipulates/ computes/processes the data and output results.

• Interpretation of results-understanding of the
• utput relative to the subject matter.

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Data analysis

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Hypothesis testing The statistical inferential procedure in which a statement based on some experimental or

• bservational study is formulated, tested, and

then put through a decision process. The decision process either accepts or rejects the statement

Data analysis

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Tests for testing of Hypothesis

• Correlation studies
• Regression Analysis
• Chi-square test
• One sample T-test
• Independent T-test
• Paired sample T-test
• F-Test

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Data analysis

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Presentation of data analysis

• Analysis of the Response Rate

How many questionnaires were issued, how many where returned and what is that response rate

• Analysis of the Background Information

Analyze the background information of the questionnaire. i.e. sex, education, age, marital status, etc

• Quantitative Analysis

Analyze and present results of the closed-ended questions

• Qualitative Analysis

Analyze and present results of the open-ended questions