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Questions and Answers
Which measure of central tendency can be affected significantly by outliers in a data set?
What type of chart is best for displaying the proportion of categories in a dataset?
In which scenario would you use dummy coding?
Which of the following would not be considered a measure of dispersion?
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What is the purpose of cross-tabulation?
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Which statistical method would be best for summarizing data through counts of occurrences?
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When asked to code responses for 'visited' or 'not visited' for a list of restaurants, which of the following is the correct way to represent 'Eat not visited'?
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Which of the following is an example of a closed-ended question?
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What is one key reason to use referral sampling in a survey?
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Which of the following statements about qualitative sampling is true?
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In the data validation process, why is it suggested to be conservative when excluding responses?
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What is the first step in the quantitative data analysis process?
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What should be done if an informant's response time is exceptionally quick, indicating potential carelessness?
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What purpose does exporting quantitative survey data as numeric values serve?
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What is a key characteristic of probability sampling?
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In which situation is non-probability sampling considered most effective?
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What type of sampling would likely produce a more representative sample for a quantitative study?
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What is a characteristic of convenience sampling?
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Why might researchers choose to use non-probability sampling despite its limitations?
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What is the significance of using a sampling frame in probability sampling?
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What is snowball sampling primarily used for?
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Which type of studies typically benefit from non-probability sampling techniques?
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Study Notes
Dummy Coding
- When dealing with multiple response questions, use dummy coding to represent each answer choice.
- Assign a '1' to indicate the answer choice was selected and '0' to indicate it was not selected.
Coding Quantitative Data
- Qualtrics automatically assigns values to Likert scales, graphical rating scales, and semantic differentials.
- Ensure the values are coded correctly and consistently.
Descriptive Statistics
- Descriptive statistics summarize and present raw data, providing insights about the sample and observations.
- Use numbers, tables, charts, and graphs to effectively communicate these summaries.
Frequency Distribution
- Shows how often each value or category appears in the data.
Measures of Central Tendency
- Describe the typical or central value in a dataset.
- Mean: The average of all values.
- Median: The middle value when data is ordered from smallest to largest.
- Mode: The most frequently occurring value.
Measures of Dispersion
- Describe the spread or variability of the data.
- Range: The difference between the highest and lowest values.
- Standard Deviation: Measures how spread out the data is around the mean.
Charts
- Bar chart: Compares different categories or groups using bars of varying heights or lengths.
- Pie chart: Represents proportions of a whole using slices of a circle.
Cross-Tabulation
- Tables that show the joint distribution of two or more variables.
- Helpful for exploring relationships between variables (e.g., brand loyalty and gender).
- Each cell in the table represents a unique combination of categories.
Sample Size
- Industry-standard rules of thumb recommend 100 survey participants and 10 interview respondents.
Qualitative Sampling
- Qualitative samples are not representative.
- Focus on ensuring the sample is from the target population.
- Avoid using sampling methods that don't align with the target segment (e.g., recruiting Lidl shoppers when the target segment is adventurous foodies).
Connecting Sampling to Data
- In your work, clearly explain how you found respondents from your target segment.
- Document the channels used for survey distribution and interview recruitment.
- Convince the audience that the chosen methods effectively reached individuals similar to the target segment.
Quantitative Data Analysis
- Download data from Qualtrics as numeric values.
- Inspect the data for any inconsistencies or errors.
- Consider excluding outliers or data that appears to be invalid or careless, but be conservative.
Validating Data
- Identify potentially careless responses by checking response time or completeness.
- Create a variable to exclude suspicious responses from analysis.
Coding Quantitative Data Assigning values to answers
- Ensure values are assigned correctly and meaningfully according to the scale type.
Probability Sampling
- Units are selected randomly.
- Produces representative samples.
- Suitable for quantitative studies, large samples, high budgets, and heterogeneous populations.
Non-Probability Sampling
- Researcher selects respondents based on specific criteria.
- Not representative.
- Suitable for qualitative studies, homogenous populations, low-budget studies, and situations where a sampling frame is unavailable.
Convenience Sampling
- Respondents are chosen because they are readily available.
- Examples: University students, people on the street, online questionnaires.
Snowball Sampling
- Initial respondents refer others from the target population for inclusion in the study.
- Useful for locating individuals with specific characteristics or for identifying rare populations.
Open-ended Questions
- Allow respondents to freely express their thoughts and ideas in their own words.
- Example: "What is important to you when buying cosmetics?"
Close-ended Questions
- Provide pre-defined answer choices.
- Example: "Do you consider price important when buying cosmetics? Yes/No."
Interview Guide
- An interview is a structured conversation with a specific objective, not a casual chat.
- Recruit respondents using snowball sampling to reach individuals who are likely to know others in the target segment.
- This method helps locate specific characteristics within the population.
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