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Chapter 4 – Statistics II

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1 Chapter 4 – Statistics II
04 Chapter 4 – Statistics II In this chapter you have learned about: Measures of centre (mean, mode and median) Sampling variability Measures of variation Measures of relative standing The normal distribution and the empirical rule Distributions

2 Advantages/disadvantages
04 Statistics II Measures of Centre Definitions We will look at three measures of centre: the mean, the mode and the median. The mean of a set of values is the sum of all the values divided by the number of values. The mode of a set of values is the value that has the greatest frequency (occurs most often). The median of a set of values is the middle value when the values are arranged in order. Deciding Which Average to Use Average When to use Advantages/disadvantages Mode Usually for categorical data. Advantages: Easy to find. Not affected by extreme values. Disadvantage: There is not always a mode. Median For numerical data. If there are extreme values. Advantages: Easy to calculate. Not affected by extreme values. Mean For numerical data. If there are not extreme values. Advantage: It uses all the data. Disadvantage: It is affected by extreme values.

3 04 Statistics II Measures of Variation Range and Interquartile Range
Definitions The range is the difference between the maximum value and the minimum value. Q1 The lower quartile of a ranked set of data is a value such that one-quarter of the values are less than or equal to it. Q2 The second quartile is the median of the data. Q3 The upper quartile of a ranked set of data is a value such that three-quarters of the values are less than or equal to it. The inter quartile range = Q2− Q1. Outliers are extreme values that are not typical of the other values in a data set. Standard Deviation Definition This is the measure of the average deviation or spread from the mean of all values in a set.

4 04 Statistics II Formula 𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 𝑠𝑒𝑡 𝑜𝑓 𝑣𝑎𝑙𝑢𝑒𝑠 𝜎= (𝑥−𝜇 ) 2 𝑛 𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 𝑓𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦 𝑡𝑎𝑏𝑙𝑒 𝜎= 𝑓(𝑥−𝜇 ) 2 𝑓 (F and T: P33) 𝜎 is the standard deviation means ′sum of ′ 𝑥 is the variable 𝜇 ( 𝑥 ) is the mean 𝑛 is the number of variables 𝑓 is the frequency Find (i) the range (ii) the standard deviation of {1, 5, 9, 14, 21} Why is the standard deviation a better measure of spread than the range? (i) The range = 21 − 1 = 20. Note: 𝒅=𝒙−𝝁. 1 5 9 14 21 10 81 25 1 16 121 𝑑 2 = 244 −9 −5 −1 4 11 (ii) 𝜇 ( 𝑥 ) = =10 𝜎= (𝑑 ) 2 𝑛 = =6∙99 The standard deviation is better because it uses all the numbers.

5 Note: 14–18 means 14 is included and 18 is not.
04 Statistics II One hundred students are given a maths problem to solve. The times taken to solve the problem are as follows: Using mid-interval values, estimate the mean of the distribution, and hence, estimate the standard deviation from the mean. Give your answers to two decimal places. Note: 14–18 means 14 is included and 18 is not. M.I.V. x f fx Mean Dev. 12 16 20 24 28 13 28 26 21 12 156 448 520 504 336 19∙64 −7∙64 −3∙64 0∙36 4∙36 8∙36 58∙3696 13∙2496 0∙1296 19∙0096 69∙8896 758∙8048 370∙9888 3∙3696 399∙2016 838∙6752 100 1,964 2,371∙04 𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 𝜎 = 𝑓 𝑑 𝑓 = 2,371∙ =4∙87 𝐸𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝑚𝑒𝑎𝑛 𝜇 = 𝑓𝑥 𝑓 = 1, =19∙64

6 Measure of Relative Standing
04 Statistics II Measure of Relative Standing Measures of relative standing are used to compare values within a data set or to compare values from different data sets. Percentiles In a class of 30 students John has scored 85% in the test. Twenty-four students scored lower than John. What is John’s relative standing in the group for this test? John’s percentile ranking = 24 30 ×100= 80 th percentile. 80% of the class scored lower than John in the test. z-Scores Dublin’s maximum February temperatures average 6∙5°C with a standard deviation of 0∙75°C, while in July the mean maximum temperature is 18°C with a standard deviation of 1∙5°C. In which month is it more unusual to have a maximum temperature of 10°C? February: 𝑧= 10−6∙5 0∙75 =4∙6 July: 𝑧= 10−18 1∙5 =−5 1 3 It is more unusual to have a maximum temperature of 10°C in July because > 4.6. Note that both z-scores are unusual values, as they lie outside -2 ≤ z ≤ 2.

7 The Normal Distribution and the Empirical Rule
04 Statistics II The Normal Distribution and the Empirical Rule The Empirical Rule In any normal distribution: 68% of the population lies within one standard deviation of the mean. Approximately 95% of the population lies within two standard deviations of the mean. Approximately 99∙7% of the population lies within three standard deviations of the mean. Approximately 68% of the distribution Approximately 95% of the distribution Approximately 99∙7% of the distribution


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