AQA · A-Level · Psychology

    Course version: 7182-2025 · Exams from 2027

    Find arithmetic means (to include: calculating the means for two…

    Full specification wording

    Handling data: Find arithmetic means (to include: calculating the means for two conditions using raw data from a class experiment)

    The mean is the total of the scores divided by how many scores there are.

    Checked against the AQA 7182-2025 specification (opens in a new tab) on .

    • Point 2 of 17
    • 4 key terms

    Study notes

    From the checked teaching notes for this specification point.

    The idea

    The mean is the total of the scores divided by how many scores there are. In an experiment, it is calculated separately for each condition to allow comparison. With eight participants recalling 7, 9, 12, 6, 10, 8, 11 and 9 words in the quiet condition, the total is 72 and the mean is 9.0 words. With 5, 4, 8, 6, 7, 5, 9 and 8 words in the noisy condition, the total is 52 and the mean is 6.5 words, a gap of 2.5 words in favour of quiet. Divide by the number of scores in that condition, never by the total number of people in the study, and keep the unit on the answer. Because every score is used, the mean is the most sensitive measure of central tendency, which is why one extreme score can drag it away from the bulk of the data.

    What earns the marks

    • The method written as a method: add all the scores in one condition, then divide by the number of scores in that condition. Write the sum out rather than only the final figure to show the working clearly.
    • Two conditions, two calculations: the answer sentence compares them, for example the mean number of words recalled was 9.0 in the quiet condition and 6.5 in the noisy condition, a difference of 2.5 words.
    • Units and precision: quote the result in the unit of the original measure and to an appropriate number of decimal places, typically one more than the raw data, so 6.5 words is acceptable and 6.500 words is not.

    Common mistakes and how to put them right

    • Adding the totals of both conditions and dividing by all the participants, which produces one overall figure and answers a question nobody asked.

    • Letting the divisor drift away from the data, by including a participant who withdrew or by treating a score of zero as no score at all and dividing by a smaller number.

    • Leaving the unit off, so a figure such as 6.5 sits on the page with nothing to say whether it counts words, seconds or errors.

    • Reporting the answer to five decimal places because that is what the calculator displayed.

    Exam tips

    • The data always arrive in a printed table, so put the total on the page first to demonstrate the initial step of the calculation.
    • A calculation is frequently followed by an instruction to say what the two figures show, which asks for the size and direction of the difference and not for a claim about statistical significance.
    • Check whether the question wants the result for each condition or for each participant group, because the two are not the same when group sizes are unequal.

    Try the lesson

    The start of the Handling data: Find arithmetic means (to include: calculating the means for two conditions using raw data from a class experiment) lesson, made from checked teaching notes for this specification point.

    Have a go first

    A psychologist records the number of words recalled by five participants in a memory test. The scores are 11, 12, 18, 14, and 20. What is the arithmetic mean of these scores?

    Listen

    The mean is the total of the scores divided by how many scores there are. In an experiment, it is calculated separately for each condition to allow comparison. With eight participants recalling 7, 9, 12, 6, 10, 8, 11 and 9 words in the quiet condition, the total is 72 and the mean is 9.0 words. With 5, 4, 8, 6, 7, 5, 9 and 8 words in the noisy condition, the total is 52 and the mean is 6.5 words, a gap of 2.5 words in favour of quiet. Divide by the number of scores in that condition, never by the total number of people in the study, and keep the unit on the answer. Because every score is used, the mean is the most sensitive measure of central tendency, which is why one extreme score can drag it away from the bulk of the data. A strong answer earns marks for these points. The method written as a method: add all the scores in one condition, then divide by the number of scores in that condition. Write the sum out rather than only the final figure to show the working clearly. Two conditions, two calculations: the answer sentence compares them, for example the mean number of words recalled was 9.0 in the quiet condition and 6.5 in the noisy condition, a difference of 2.5 words. Units and precision: quote the result in the unit of the original measure and to an appropriate number of decimal places, typically one more than the raw data, so 6.5 words is acceptable and 6.500 words is not. Justifying the choice of measure: this average is suitable for interval data with no extreme scores because it takes account of every value, and that reason is what is required when the calculation is followed by an explanation. Exam tip: The data always arrive in a printed table, so put the total on the page first to demonstrate the initial step of the calculation.

    See it

    A flowchart running from top to bottom. On the left, a node labelled 'Quiet condition scores' leads to 'Add all scores in the condition', which leads to 'Divide by the number of scores in that condition', which leads to 'Mean for quiet condition, with unit'. On the right, a parallel path runs from 'Noisy condition scores' to 'Add all scores in the condition' to 'Divide by the number of scores in that condition' to 'Mean for noisy condition, with unit'. Both mean nodes then lead into a single final node labelled 'Compare the two means'.
    It shows the same two-step mean calculation carried out separately for each condition, then the two means compared.

    Key words

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    measures of central tendency

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    raw data handling

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    condition by condition comparison

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    sensitivity to anomalies

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    See every definition
    measures of central tendency
    The mean is the most sensitive measure of central tendency because every score is used.
    raw data handling
    Add all the scores in one condition, then divide by the number of scores in that condition, writing the sum out to show the working.
    condition by condition comparison
    The mean is calculated separately for each condition to allow comparison, stating both means with their unit and the difference between them.
    sensitivity to anomalies
    Because every score is used, one extreme score can drag the mean away from the bulk of the data.

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