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1 Slide AQA - Business Statistics, Quantitative Analysis Peter Matthews FDA B&M 2011-12.

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Presentation on theme: "1 Slide AQA - Business Statistics, Quantitative Analysis Peter Matthews FDA B&M 2011-12."— Presentation transcript:

1 1 Slide AQA - Business Statistics, Quantitative Analysis Peter Matthews matthewsp@bpc.ac.uk FDA B&M 2011-12

2 2 Slide Today’s Aims Overview of numerical data properties Central Tendancy and how to calculate them Simple Variation and how to calculate Essentially Level 2 Maths

3 3 Slide

4 4 Central tendency

5 5 Slide Variation

6 6 Slide

7 7

8 8

9 9 Picture 1Picture 2Picture 3Picture 4Picture 5Picture 6Picture 7Picture 8Picture 9Picture 10 Danny54243122293425 3228 Alex45325022403920524521 Kerry52273826324223284230 Laura54343623444028323828 Josie50354025364227234429 Zenia50384822334329405522 Tasos52343040383620324032 Jessica48313528433825334243 Andrea46283220314325293723 Juan49364223302726274625 Amine45273924265223323528 Stefany4636331930 28293625 H1

10 10 Slide H2 Picture 1Picture 2Picture 3Picture 4Picture 5Picture 6Picture 7Picture 8Picture 9Picture 10 Sophie48355426384732494324 Tony52364127433229304827 Simon43364627344125313926 Jacob49403934453728273726 Georgie47345222394429485127 Megan52343927424532363130 Elliott42344419364025323826 Danielle56374220334428293430

11 11 Slide H3 Picture 1Picture 2Picture 3Picture 4Picture 5Picture 6Picture 7Picture 8Picture 9Picture 10 Chris C51363323414527383926 Amelia47404228374832294634 Verelle5128422544722384930 Jordan51283222373326233430 Harry51324327404625332832 Will52284925451027263632 Angelika47283520385423275624 Katie47293421385223325824

12 12 Slide 1- All the values are included in computing the mean. 2- A set of data has a unique mean. 3- The mean is affected by unusually large or small data values. 4- It is a measure of central tendency not a measure of variation Properties of the Arithmetic Mean

13 13 Slide

14 14 Slide

15 15 Slide

16 16 Slide So did I/You survive the Wrath that is Cheryl ?

17 17 Slide

18 18 Slide

19 19 Slide

20 20 Slide But Chez isn't happy yet

21 21 Slide But Chez isn't happy yet

22 22 Slide Average A measure of average is a number that is typical for a set of figures. Finding the average helps you to draw conclusions from data. The main types are mean, median and mode. 3 Different types

23 23 Slide A call centre claims to answer the calls on an average of 3 rings or less. Do you believe them ? Mode 7101080

24 24 Slide Median The median of a data set is the value in the middle when the data items are arranged in ascending order Whenever a data set has extreme values, the median is the preferred measure of central location. A few extremely large incomes or property values can inflate the mean. The median is the measure of location most often. reported for annual income and property value data. Just a note if you have an even amount of numbers a,b,c,d the median is b+c/2.

25 25 Slide

26 26 Slide

27 27 Slide

28 28 Slide Mode - The mode of a data set is the value that occurs with greatest frequency The greatest frequency can occur at two or more different values. If the data have exactly two modes, the data are bimodal. If the data have more than two modes, the data are multimodal.

29 29 Slide

30 30 Slide

31 31 Slide

32 32 Slide

33 33 Slide Variation

34 34 Slide ~ What does Average really tell us? 10 50 90 40 50 60

35 35 Slide Measures of Variability (Dispersion) It is often desirable to consider measures of variability (dispersion), as well as measures of location. For example, in choosing supplier A or supplier B we might consider not only the average delivery time for each, but also the variability in delivery time for each.

36 36 Slide Measures of Variability (Dispersion) Range Interquartile Range or Midspread Variance Standard Deviation Coefficient of Variation

37 37 Slide Range - The range of a data set is the difference between the largest and smallest data values. It is the simplest measure of variability. It is very sensitive to the smallest and largest data values.

38 38 Slide

39 39 Slide

40 40 Slide

41 41 Slide Interquartile Range or Midspread - The interquartile range of a data set is the difference between the third (upper) quartile and the first (lower) quartile. It is the range for the middle 50% of the data. It overcomes the sensitivity to extreme data values—it is not effected by the extreme values.

42 42 Slide The Five-Number Summary The five-number summary is a set of five descriptive statistics that divide the data set into four equal sections. The five numbers in a five number summary are: 1. The minimum (smallest) number in the data set. 2. The 25th percentile, aka the first quartile, or Q1. 3. The median (or 50th percentile). 4. The 75th percentile, aka the third quartile, or Q3. 5. The maximum (largest) number in the data set.

43 43 Slide Where are the quartiles of 3, 4, 4, 6, 8, 8,10, 10, 11, 12, 31 Lower quartile is the (n + 1) ÷ 4 th value.

44 44 Slide BBC Bytesize

45 45 Slide Who still likes me ?

46 46 Slide Where are the quartiles of 3, 4, 4, 6, 8, 8,10, 10, 11, 12, 31 Q1 = 5 Q2 = 8 Q3 = 10.5 Excel (q 1 is the 1/4(n+3)th

47 47 Slide 3, 4, 4, 6, 8, 8,10, 10, 11, 12, 31 IQR = 11 – 4 = 7 Range=31-3 = 28

48 48 Slide Variance The variance is computed as follows: The variance is computed as follows: The variance is the average of the squared The variance is the average of the squared differences between each data value and the mean. differences between each data value and the mean. Note: from now on I will just give out one formula, I will use sample (inferred) formula's and not population. Saves confusion

49 49 Slide Don’t worry We will return to the data, to calculate who was the closest at guessing ages.


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