Learning objective

Recognize how adding a constant to each data point and multiplying each data point by a constant affects the median and interquartile range.

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Cambridge IGCSE StatisticsTransformations of data sets

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Recognize how adding a constant to each data point and multiplying each data point by a constant affects the median and interquartile range

This point belongs to Transformations of data sets, especially Transformations of data sets outcomes.
You need to be able to recognize how adding a constant to each data point and multiplying each data point by a constant affects the median and interquartile range.
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Paper 1 structured question: Transformations of data sets

Paper 1Statistical Techniques3 marks

Description

Dataset Transformation

Consider a dataset where each data point is increased by 7.

a
Calculate the new median if the original median was 15.
Your answer
Aim for approximately 1 distinct marking point.
[1]
b
Explain why the interquartile range remains unchanged.
Your answer
Aim for approximately 2 distinct marking points.
[2]

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Related learning objectives

Recognize how adding a constant to each data point and multiplying each data point by a constant affects the mean and standard deviation.
Transformations of data sets outcomes
Understand how introducing new values or removing existing values from a distribution affects a statistical measure, such as whether the median increases, decreases, or remains unchanged.
Transformations of data sets outcomes
Calculate the mean and standard deviation of a data set, including finding the mean of a second data set formed by combining two data sets with known means and standard deviations.
Transformations of data sets outcomes
Utilize means and standard deviations of distributions to scale data values for comparison and interpretation, including standardizing data to a mean of 0 and a standard deviation of 1.
Transformations of data sets outcomes
Compare distributions by examining measures of central tendency and dispersion, such as identifying which distribution has higher values or is more consistent based on known means and standard deviations.
Transformations of data sets outcomes

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