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13-1 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e Chapter 13 Measures.

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Presentation on theme: "13-1 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e Chapter 13 Measures."— Presentation transcript:

1 13-1 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e Chapter 13 Measures of Variation Introductory Mathematics & Statistics

2 13-2 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e Learning Objectives Calculate common measures of variation (including the range, interquartile range, mean deviation and standard deviation) from grouped and ungrouped data Calculate and interpret the coefficient of variation

3 13-3 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.1 Introduction A measure of central tendency in itself is not sufficient to describe a set of data adequately A measure of dispersion (or spread) of the data is usually required This measure gives an indication of the internal variation of the data—that is, the extent to which data items vary from one another or from a central point Some reasons for requiring a measure of dispersion of a set of data: –As an indication of the reliability of the average value –To assist in controlling unwanted variation

4 13-4 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.2 The range The simplest measure of dispersion is the range It is the difference between the largest and smallest values in a set of data Range = largest observation – smallest observation Examples of uses of range include –Temperature fluctuations on a given day –Movement of share prices –Acceptable range of systolic and diastolic blood pressures

5 13-5 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.2 The range (cont…) Range is considered primitive as it considers only the extreme values, which may not be useful indicators of the bulk of the population Extreme values, called outliers, may often result from errors of measurement Outliers are defined as values that are inconsistent with the rest of the data Although the range is the quickest and easiest measure of dispersion to calculate, its should be interpreted with some caution

6 13-6 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.3 The interquartile range (midspread) Measures the range of the middle 50% of the values only Is defined as the difference between the upper and lower quartiles Interquartile range = upper quartile – lower quartile = Q 3 – Q 1 May be calculated from grouped frequency distributions that contain open-ended class intervals It is usually only used with a large number of observations

7 13-7 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.4 The mean deviation The mean deviation takes into account the actual value of each observation It measures the ‘average’ distance of each observation away from the mean of the data It gives an equal weight to each observation It is generally more sensitive than the range or interquartile range, since a change in any value will affect it

8 13-8 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.4 The mean deviation (cont…) The residual measures the actual deviation (or distance) of each observation from the mean A set of x values has a mean of residualThe residual of a particular x-value is: Example If the mean for a set of data is 3.22, find the residual for an observation of 4.38 Solution The residual of 4.38 is 4.38 – 3.22 = 1.16 Note: Residuals can be in the negative range. It shows that the observation is below the mean

9 13-9 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.4 The mean deviation (cont…) The mean deviation is defined as the mean of these absolute deviations: To calculate the mean deviation Step 1: Calculate the mean of the data Step 2: Subtract the mean from each observation and record the resulting differences Step 3: Write down the absolute value of each of the differences found in Step 2 (ignore their signs) Step 4: Calculate the mean of the absolute values of the differences found in step 3

10 13-10 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.4 The mean deviation (cont…) Example The batting scores of a cricketer was recorded over 10 completed innings to date. His scores were: 32, 27, 38, 25, 20, 32, 34, 28, 40, 29 Calculate the mean deviation of the cricketers’ scores Solution Step 1 The cricketers’ average number of runs is 30.5

11 13-11 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.4 The mean deviation (cont…) ScoreDeviation from mean Absolute value of deviation 32+1.51.5 27-3.53.5 29-1.51.5 Step 2 and 3 completed in the table Step 4

12 13-12 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.4 The mean deviation (cont…) Calculation of the mean deviation from a frequency distribution –If the data is in the form of a frequency distribution, the mean deviation can be calculated Where f = the frequency on an observation x = the sum on the frequencies = n

13 13-13 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.5 The standard deviation The most commonly used measure of dispersion is the standard deviation It takes into account every observation and measures the ‘average deviation’ of observations from mean It works with squares of residuals, not absolute values, therefore it is easier to use in further calculations The values of the mean deviation and standard deviation should be reasonably close, since they are both measuring the variation of the observations from their mean

14 13-14 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.5 The standard deviation (cont…) Population standard deviation –Uses squares of the residuals, which will eliminate the effect of the signs, since squares of numbers cannot be negative Step 1: find the sum of the squares of the residuals Step 2: find their mean. Step 3: take the square root of this mean. Where N = the size of the population The square of the population standard deviation is called the variance.

15 13-15 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.5 The standard deviation (cont…) Sample standard deviation –It is rare to calculate the value of since populations are usually very large –It is far more likely that the sample standard deviation (denoted by s) will be needed. –Where: ( n – 1 ) is the number of observations in the sample

16 13-16 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.5 The standard deviation (cont…) A note on the use of (n − 1) in formulae –If the value of n is large, it will only make a slight difference to the answer whether you divide by n or (n − 1) –To calculate the value of s from a sample the calculator button will usually be indicated by one of  n−1 or x  n−1 or  x or  written either on it or near it –To calculate the value of  from a population, the calculator key will usually be indicated by one of  n or x  n or  x or  written either on it or near it

17 13-17 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.5 The standard deviation (cont…) Important points about the standard deviation –The standard deviation cannot be negative –The standard deviation of a set of data is zero if, and only if, the observations are of equal value –The standard deviation can never exceed the range of the data –The more scattered the data, the greater the standard deviation –The square of the standard deviation is called the variance

18 13-18 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.5 The standard deviation (cont…) Calculation of the sample standard deviation Step 1: Calculate the mean Step 2: For each x-value, find the value of the residual Step 3: Square the residuals Step 4: Calculate the sum of the squares of the residuals Step 5: Divide the sum found in step 4 by (n – 1) Step 6: Take the square root of the quantity found in step 5: this is the sample standard deviation

19 13-19 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.5 The standard deviation (cont…) Calculation of the standard deviation from a frequency distribution –If the data are in the form of a frequency distribution, –Calculate standard deviation using:

20 13-20 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.5 The standard deviation (cont…) Calculation of the standard deviation from a grouped frequency distribution –When calculating s from a grouped frequency distribution, we should assume that the observations in each class interval are concentrated at the midpoint of the interval –Where = the estimated mean of the same m = the midpoint of the class interval f = the frequency of the class interval

21 13-21 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.6 The coefficient of variation This is a measure of relative variability used to: –measure changes that have occurred in a population over time –compare variability of two populations that are expressed in different units of measurement It is expressed as a percentage rather than in terms of the units of the particular data

22 13-22 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.6 The coefficient of variation (cont…) The formula for the coefficient of variation (V) is: Where = the mean of the sample s = the standard deviation of the sample

23 13-23 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.6 The coefficient of variation (cont…) Example Calculate the coefficient of variation for the price of 400 g cans of pet food, given that the mean is 81 cents and s = 6.77 cents. Interpret the results. Solution This means that the standard deviation of the price of a 400g can of pet food is 8.36% of the mean price.

24 13-24 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e 13.7 Remarks Among the more important characteristics of the standard deviation are: –It is the most frequently used measure of dispersion, and because of its mathematical properties it has widespread use in problems involving statistical inference –If the mean cannot be calculated, neither can the standard deviation –Its value is affected by the value of every observation in the data –If the data have a number of extreme values, the value of the standard deviation may be distorted so as not to be a good ‘representative’ measure of dispersion

25 Summary Among the more important characteristics of the standard deviation are: –It is the most frequently used measure of dispersion, and because of its mathematical properties it has widespread use in problems involving statistical inference. –If the mean cannot be calculated. neither can the standard deviation. –Its value is affected by the value of every observation in the data. –If the data have a number of extreme values, the value of the standard deviation may be distorted so as not to be a good ‘representative’ measure of dispersion. 13-25 Copyright  2010 McGraw-Hill Australia Pty Ltd PowerPoint slides to accompany Croucher, Introductory Mathematics and Statistics, 5e


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