Standardising data and normal distribution - L5

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17 Terms

1
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What does standard deviation measure?

The average deviation of all values from the mean

2
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How is standard deviation displayed?

In brackets after the mean

3
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What should you do if the true value of a piece of data is unknown?

Record a missing value

4
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What are the 2 ways to transform data?

  • Scale the data

  • Standardise the data

5
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What is scaling the data?

Converting all of the data values into the same units

6
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What is standardising the data used for?

To be able to compare different sexes or not directly comparable categories

7
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What happens to the mean if data values are re-adjusted by adding or subtracting?

It increases or decreases by the value added or subtracted to each data value

8
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When you multiply or divide to scale data, what happens to the mean and standard deviation?

They both increase or decrease by the proportion being multiplied or divided by

9
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What does a z-score measure?

The number of standard deviations an observation is from the mean

10
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What does a z-score of 0 indicate?

A value that is equal to the mean

11
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How do you calculate a z-score?

(observation - mean)/standard deviation

12
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What is the mean of all z-scores always equal to?

0

13
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What is the standard deviation of all z-scores always equal to?

1

14
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What are 6 properties of normal distribution?

  • The curve is symmetrical about the mean

  • The mean is equal to the median

  • Most observations are closer to the mean

  • Few observations are at either extreme

  • Lines of the curve don’t touch the x-axis

  • The shaded area under the curve always equals 1.0

15
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What percentage of normally distributed data lien within ± 1 standard deviation of the mean?

68.2%

16
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What percentage of normally distributed data lien within ± 2 standard deviations of the mean?

95.4%

17
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In normal distribution, what is 1 z-score equal to?

34.1% or 0.341