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Learn it your way
A short class with Sarah and her students. The other ways are under More.
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Let's start with framing multiple-choice questions. Does anyone know what a multiple-choice question is?
It's a question where you choose an answer from several options.
Exactly! Now, when framing questions, it's important to make sure options are clear. For example, can someone give me an example of a question?
How often do you use computers?
Good! Now, how would you frame the options for that question?
We could say: Daily, Weekly, Monthly, or Never.
Perfect! Use the acronym CAAP: Clear, Accurate, Appropriate, and Precise for crafting your questions.
Can you give us an example of a poor question?
Sure! A poor question would be: 'How much time do you waste on computers every day?' The word 'waste' is judgmental. What would be a more neutral way to ask?
How much time do you spend on computers daily?
Exactly! Remember to avoid bias!
Now let’s discuss some statements about data collection. Are we ready?
Yes! What’s the first statement?
Statement one: 'Data collected by investigators is called secondary data.' True or False?
That’s false, right? It should be called primary data.
Correct! Remember, primary data is collected firsthand. How about the next statement: 'Telephone surveys are suitable for literate populations.'?
That sounds true!
Yes, it is! Always consider your audience when selecting a method.
It seems easy to mislabel data types!
It can be! That's why understanding them is key to data collection.
In this session, we are going to talk about biases in survey questions. Why is this important?
Bias can skew our data!
Exactly! Poorly worded questions can lead to non-response errors or influence responses. For example, how about this question: 'Don’t you think smoking should be banned?' Why is it problematic?
It hints that you should agree!
Correct! It’s leading. What’s a better way to ask this question?
Do you think smoking should be banned?
Yes! It’s neutral. Remember, we want to gather honest feedback!
Firsthand collected information for a specific purpose.
Previously collected data used for new analysis.
Crafting questions for accuracy and neutrality.
A tendency impacting data interpretation negatively.
Mistakes occurring due to data sample selection.
When you ask, make it clear, avoid terms that may appear dear.
Imagine a survey at a school where one student asked: 'Don't you love this new cafeteria food?' This led to skewed results. Instead, if they asked, 'How do you feel about the cafeteria food?' that would gather more honest feedback.
Remember the acronym C.A.S.E: Clear, Accurate, Specific, English for good questioning.
B.A.S.E.: Bias Avoidance in Survey Execution.
Term
What is primary data?
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Term
What is bias in surveys?
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Data collected firsthand for a specific purpose.
Data that has been previously collected and processed by others.
A tendency to favor one outcome over others, affecting data accuracy.
A question that provides several answer options for the respondent to choose from.
A type of question that allows respondents to determine the accuracy of a statement.
This section engages students with exercises that deepen Their understanding of data collection techniques.
The exercises section presents a variety of tasks, including framing questions and evaluating survey designs. It challenges students to think critically about data collection methods and phrasing while ensuring they grasp essential concepts.
The 'EXERCISES' section encourages students to apply their understanding of data collection methods through various exercises. These exercises range from framing multiple-choice questions about data collection to evaluating true or false statements regarding data sources and survey methods. By engaging with these exercises, students not only reinforce their knowledge of primary and secondary data types but also learn about survey design intricacies. The tasks emphasize the importance of well-phrased questions and the understanding of sampling and non-sampling errors in statistical data gathering. The exercises ultimately prepare students for practical data collection scenarios in real-world situations.