Study Unit
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Outcomes
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Assessment Criteria
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After completion of this course, participants will: |
Participant will be assessed on the following criteria: |
MODULE 1 (US 262539):
UTILISE ALTERNATIVE METHODS TO COLLECT DATA
At the end of the learning cycle, the learners will demonstrate knowledge and understanding of:
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Data collection methods.
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Principles of data collection.
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Stages of planning a survey.
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Design and evaluate questions for simple survey objectives.
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1. Compare various data collection methods. |
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Describe different data collection methods to compare their advantages and disadvantages.
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Evaluate a specific data collection method used in a survey is a view of the survey objectives and resource constraint.
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Select a data collection method for a survey is in view of the survey objectives and resource constraint.
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Explain the difference between primary and secondary data sources to distinguish methods of data collection in each case.
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2. Explain the basic principles of data collection. |
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Explain the meaning of the term survey to distinguish it from other data collecting activities such as census and experiment.
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Identify a given data collecting activity as a census, a survey, an experiment or an administrative data collection.
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Describe the various stages of primary data collection to highlight the advantages and disadvantages of different approaches used at each stage.
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Define the key functions of an enumerator to reflect the qualities of a good enumerator.
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Designate the key functions of a supervisor to reflect the qualities of a good field supervisor.
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3. Explain the main stages in planning a survey. |
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Outline the basic terms associated with surveys to prepare for survey planning activities.
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State the main stages in planning a survey in order to reflect a comprehensive survey process.
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Explain the importance of sensitivity to social profile in planning a survey to reflect the way it affects data collection.
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4. Design and evaluate questions for simple survey objectives. |
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Construct a few survey questions in order to obtain information relevant to the survey objectives.
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Examine survey questions to assess their relevance to the survey objectives.
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Modify survey questions in order to improve the chance of obtaining reliable responses.
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MODULE 2 (US 262559):
SELECT AND USE SAMPLING METHODS
At the end of the learning cycle, the learners will demonstrate knowledge and understanding of:
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Identify population,
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Select sampling frame
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Define different methods of sampling
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Compare methods of sampling
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Use different sampling methods.
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Design sample for given survey objective and resource constraint.
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1. Identify population, select sampling frame, and potential errors. |
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Discuss the relationship between a population and an associated sampling frame in order to determine the coverage.
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Identify possible sampling and non-sampling errors in order to select the most suitable sampling frame.
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Describe list frames and area-based frames in order to facilitate the selection of the most suitable frame.
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Identify an appropriate population for a given context so as to facilitate the planning of a survey.
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Compare sampling frames in order to select the best for a given context.
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2. Define and compare different methods of sampling. |
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Define probability and non-probability sampling methods and compared in order to justify the use of probability sampling.
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Identify the sampling method used in a study in order to evaluate the validity of survey results.
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Discuss the advantages and disadvantages of different sampling methods in a given context in order to select the best method.
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3. Use different sampling methods. |
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Describe the way a sampling method is used in a given context in order to assist the planning of field work.
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Select a random sample in accordance with a given sampling method in order to implement a survey plan.
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Use statistical software to select a random sample.
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4. Design a sample for given survey objective and associated resource constraint. |
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Select a suitable sampling method in order to realize the survey objective with minimal sampling error.
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Calculate the sample size under given cost and error constraints.
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Evaluate the sampling method used in a given study in order to determine the validity of the study results.
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MODULE 3 (US 10061):
PLAN FIELDWORK TO MEET REQUIRED DEADLINES AND BUDGET
At the end of the learning cycle, the learners will demonstrate knowledge and understanding of:
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A comprehensive understanding of techniques and methods for writing field instructions.
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A basic understanding of techniques and methods for verbal and written communication.
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An all rounded and generic understanding of the industry, the product and the industry role players
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1. Writing field instructions. |
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Confirm that field instructions are clear, concise and specific to the original brief.
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Insist that field instructions include training costs and trip/schedule details.
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Write field instructions in the required format and agree on timeframes.
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2. Selecting appropriate interviewers/moderators for the target population and interview complexity |
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Reflect on respondent's response to different types of interviewers.
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Study expertise in subject matter required by the interviewer.
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Deliberate expertise required by measuring instrument.
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3. Planning cost-effective field schedules. |
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Confirm that field Schedule meets timing constraints.
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Insist that field Schedule meets budget constraints.
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Consider complexities of the sample when planning field Schedules.
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MODULE 4 (US 262557):
APPLY THE TECHNIQUES OF DATA PROCESSING
At the end of the learning cycle, the learners will demonstrate knowledge and understanding of:
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Code, enter, verify and validate data.
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Check and edit data.
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Impute missing values under supervision.
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Transform the structure of data and tabulate the data.
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1. Code, enter, verify and validate data. |
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Classify and code responses from an open question into numerical values.
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Review the questionnaire to ensure that the minimum data required are reported.
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Verify and validate data using a variety of methods to ensure the accuracy of data.
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Capture data from paper questionnaires into an electronic file using the available means.
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Construct frequency tables to validate data.
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Discuss quality control measures in order to assess and evaluate the quality of data.
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2. Check and edit data. |
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State reasons for editing census and survey data to justify the editing stage of data processing.
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Identify and describe types and sources of errors to reflect on what to look for during editing.
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Explain and implement different types of edits for a given data set.
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Discuss the effectiveness and limitations of the various types of edits to reflect on data quality issues.
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Write computer commands to perform automatic data editing.
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Use available software to perform micro and macro edits to identify errors in data files.
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Discuss risks associated with editing to highlight the issues to be careful with.
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3. Transform the structure of data and tabulate the data. |
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Transform the data structure used to input data for tabulation.
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Construct appropriate tables to summarize data.
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Change the data structure to one that is suitable for statistical packages.
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Prepare data for storage and archiving
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