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9609 · 3.2.4

Market research data flashcards

Revision flashcards for Cambridge 9609 Market research data (syllabus 3.2.4). Flip, recall, then mark a real past-paper question.

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    Quantitative data?

    Numerical — can be statistically analysed (%, averages, charts).

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    Qualitative data?

    Non-numerical — opinions, reasons, descriptions from interviews/focus groups.

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    Quant advantage?

    Objective comparisons, large-sample trends, easy to graph.

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    Qual advantage?

    Explains 'why' behind numbers; uncovers unexpected insights.

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    Triangulation?

    Using multiple methods/data sources to cross-check findings.

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    Misleading charts?

    Truncated axes, small samples, leading questions distort conclusions.

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    What is quantitative data?

    Numerical data that can be measured and statistically analysed. It answers 'what', 'how many', or 'how much'. Examples include sales figures and survey results with closed questions.

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    What is qualitative data?

    Non-numerical, descriptive data that provides insights into opinions, attitudes, and motivations. It answers 'why'. Examples include focus group transcripts and in-depth interview notes.

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    Define triangulation in market research.

    The use of two or more research methods or data sources to study a single problem. It is used to increase the validity and reliability of the findings by cross-verifying them.

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    What is the key difference between validity and reliability in research?

    Validity refers to how well the research measures what it set out to measure (accuracy). Reliability refers to the consistency of the results; if the research were repeated, would it produce similar findings?

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    Name three methods of presenting quantitative data.

    Bar charts (for comparing categories), pie charts (for showing proportions of a whole), and line graphs (for showing trends over time).

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    What is the mean in data analysis?

    The average value, calculated by summing all values and dividing by the number of values. It can be skewed by outliers.

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    What is the median in data analysis?

    The middle value in a sorted dataset. It is less affected by outliers than the mean and is a good measure of central tendency.

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    What is the mode in data analysis?

    The most frequently occurring value in a dataset. It is useful for identifying the most popular option or category.

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    What is a key limitation of using only quantitative data?

    It shows 'what' is happening (e.g., sales are down) but not 'why' (e.g., poor customer service, new competitor). It lacks context and emotional depth.