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30+mba-第46章

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The median 
The median is the value occurring at the centre of a data set。 Recasting the 
figures in Table 11。1 puts product 4’s selling price of £15 in that position; 
with two higher and two lower prices。 The median es into its own in 
situations where the outlying values in a data set are extreme; as they are 
in our example; where in fact most of the products sell for well below £21。 
In this case the median would be a be。。er measure of the central tendency。 
You should always use the median when the distribution is skewed。 You 
can use either the mean or the median when the population is symmetrical 
as they will give very similar results。 
The mode 
The mode is the observation in a data set appearing the most o。。en; in this 
example it is £10。 So if we were surveying a sample of the customers of the 
pany in this example; we would expect more of them to say they were 
paying £10 for their products; though; as we know; the average price is 
£21。
Quantitative and Qualitative Research and Analysis 251 
Variability 
As well as measuring how values cluster around a central value; to make 
full use of the data set we need to establish how much those values could 
vary。 The two most mon methods employed are the following。 
Range 
The range is calculated as the maximum figure minus the minimum figure。 
In the example being used here; that is £40 – £10 = £30。 This figure gives 
us an idea of how dispersed the data is and so how meaningful; say; the 
average figure alone might be。 
Standard deviation from the mean 
This is a rather more plicated concept as you need first to grasp the 
central limit theorem; which states that the mean of a sample of a large 
population will approach ‘normal’ as the sample gets bigger。 The most 
valuable feature here is that even quite small samples are normal。 The 
bell curve; also called the Gaussian distribution; named a。。er Johann Carl 
Friedrich Gauss (1777–1855); a German mathematician and scientist; shows 
how far values are distributed around a mean。 The distribution; referred to 
as the standard deviation; is what makes it possible to state how accurate 
a sample is likely to be。 When you hear that the results of opinion polls 
predicting elections based on samples as small as 1;000 are usually reliable 
within four percentage points; 19 times out of 20; you have a measure of 
how important。 (You can get free tutorials on this and other aspects of 
statistics at Web Interface for Statistics Education (h。。p://wise。cgu。edu)。) 
Figure 11。2 is a normal distribution that shows that 68。2 per cent of 
the observations of a normal population will be found within 1 standard 
Figure 11。2 Normal distribution curve (bell) showing standard deviation 
Mean 
–3 SD –2 SD –1 SD 0 +1 SD +2 SD +3 SD 
2。1% 2。1% 
13。6% 13。6% 
34。1% 34。1%
252 The Thirty…Day MBA 
deviation of the mean; 95。4 per cent within 2 standard deviations; and 
99。6 per cent within 3 standard deviations。 So almost 100 per cent of the 
observations will be observed in a span of six standard deviations; three 
below the mean and three above the mean。 The standard deviation is an 
amount calculated from the values in the sample。 Use this calculator ( 
easycalculation/statistics/standard…deviation。php) to work out the 
standard deviation by entering the numbers in your sample。 
Forecasting 
Sales drive much of a business’s activities; it determines cash flow; stock 
levels; production capacity and ultimately how profitable or otherwise a 
business will be; so; unsurprisingly; much effort goes into a。。empting to 
predict future sales。 A sales forecast is not the same as a sales objective。 An 
objective is what you want to achieve and will shape a strategy to do so。 A 
forecast is the most likely future oute given what has happened in the 
past and the momentum that provides for the business。 
The ponents of any forecast are made up of three ponents and to 
get an accurate forecast you need to depose the historic data to be。。er 
understand the impact of each on the end result: 
。 Underlying trend: This is the general direction; up; flat or down; over 
the longer term; showing the rate of change。 
。 Cyclical factors: These are the short…term influences that regularly superimpose 
themselves on the trend。 For example; in the summer months 
you would expect sales of certain products; swimwear; ice creams and 
suntan lotion; for example; to be higher than; say; in the winter。 Ski 
equipment would probably follow a reverse pa。。ern。 
。 Random movements: These are irregular; random spikes up; or down; 
caused by unusual and unexplained factors。 
Using averages 
The simplest forecasting method is to assume that the future will be more 
or less the same as the recent past。 The two most mon techniques that 
use this approach are: 
。 Moving average: This takes a series of data from the past; say the last 
six months’ sales; adds them up; divides by the number of months and 
uses that figure as being the most likely forecast of what will happen 
in month 7。 This method works well in a static; mature marketplace 
where change happens slowly; if at all。 
。 Weighted moving average: This method gives the most recent data more 
significance than the earlier data since it gives a be。。er representation of 
Quantitative and Qualitative Research and Analysis 253 
current business conditions。 So before adding up the series of data each 
figure is weighted by multiplying it by an increasingly higher factor as 
you get closer to the most recent data。 
Exponential smoothing and advanced 
forecasting techniques 
Exponential smoothing is a sophisticated averaging technique that gives 
exponentially decreasing weights as the data gets older and conversely 
more recent data is given relatively more weight in making the forecasting。 
Double and triple exponential smoothing can be used to help with different 
types of trend。 More sophisticated still are Holt’s and Brown’s linear exponential 
smoothing and Box…Jenkins; named a。。er two statisticians of those 
names; which applies autoregressive moving average models to find the 
best fit of a time series。 
Fortunately; all an MBA needs to know is that these and other statistical 
forecasting methods exist。 The choice of which is the best forecasting technique 
to use is usually down to trial and error。 Various so。。ware programs 
will calculate the best…fi。。ing forecast by applying each technique to the 
historic data you enter。 Then wait and see what actually happens and use the 
technique that’s forecast as closest to the actual oute。 Professor Hossein 
Arsham of the University of Baltimore (h。。p://home。ubalt。edu/ntsbarsh/ 
Business…stat/otherapplets/ForecaSmo。htm#rmenu) provides a useful tool 
that allows you to enter data and see how different forecasting techniques 
perform。 Duke University’s Fuqua School of Business; consistently ranked 
among the top 10 US business schools in every single functional area; 
provides this helpful link (duke。edu/~rnau/411home。htm) to all its 
lecture material on forecasting。 
Causal relationships 
O。。en; when looking at data sets it will be apparent that there is a relationship 
between certain factors。 Look at Figure 11。3。 It is a chart showing the 
monthly sales of barbeques and the average temperature in the preceding 
month for the past eight months。 
It’s not too hard to see that there appears to be; as we might expect; a 
relationship between temperature and sales; in this case。 By drawing the 
line that most accurately represents the slope; called the line of best fit; we 
can have a useful tool for estimating what sales might be next month; given 
the temperature that occurred this month (Figure 11。4)。 
The example used is a simple one and the relationship obvious and 
strong。 In real life there is likely to be much more data and it will be harder 
to see if there is a relationship between the ‘independent variable’; in this 
254 The Thirty…Day MBA 
case temperature; and the ‘dependent variable’; sales volume。 Fortunately; 
there is an algebraic formula known as ‘linear regression’ that will calculate 
the line of best fit for you。 
There are then a couple of calculations needed to test if the relationship 
is strong (it can be strongly positive or even if strongly negative it will still 
be useful for predictive purposes) and significant。 The tests are known as 
R…squared and the Students t…test; and all an MBA needs to know is that 
they exist and you can probably find the so。。ware to calculate them on your 
puter already。 Otherwise you can use Web…Enabled Scientific Services 
& Applications (wessa/slr。wasp) so。。ware; which covers almost 
every type of statistical calculation。 The so。。ware is free online and provided 
Figure 11。4 Sca。。er diagram – the line of best fit 
Figure 11。3 Sca。。er diagram example 
0 
200 
400 
600 
800 
1000 
1200 
1400 
1600 
0 20 40 60 80 100 
Temperature (F) 
Sales units (ooo's) 
0 
200 
400 
600 
800 
1000 
1200 
1400 
1600 
0 20 40 60 80 100 
Temperature (F) 
Sales units (000's)
Quantitative and Qualitative Research and Analysis 255 
through a joint research project with K。U。Leuven Association; a network of 
13 institutions of higher education in Flanders。 
For help in understanding these statistical techniques; read The Li。。le 
Handbook of Statistical Practice by Gerard E Dallal of Tu。。s; available free 
online (tu。。s。edu/~gdallal/LHSP。HTM)。 At Princeton’s website (h。。p:// 
dss。princeton。edu/online_help/analysis/interpreting_regression。htm) you 
can find a tutorial and lecture notes on the subject as taught to its Master of 
International Business students。 
QUALITATIVE RESEARCH AND ANALYSIS 
Qualitative research is a well…entrenched academic tradition in sociology; 
history; geography and anthropology; it is widely used in the medical 
and political fields。 It has made much less of a mark in business; perhaps 
because of its image as a so。。er; more ethereal discipline。 That situation is 
changing with the growing realization that while quantitative research can 
reveal what issues are important and even where they lie; it is of rather 
less use in understanding why they have e about or what to do about 
them。 Qualitative research es into its own particularly when these are 
important factors: 
。 plex issues: Quantitative methods are useful for separating out 
and measuring individual factors; say what percentage of customers 
are dissatisfied with a product or service and how many will defect。 
Qualitative methods can help get an understanding of the linkages 
between these factors and the peting tensions they arouse。 
。 Stakeholders’ differences: Not everyone involved in an organization 
sees ma。。ers from the same perspective。 O。。en the aggregation nature of 
quantitative methods makes it difficult to fully appreciate the position 
of less powerful stakeholders。 Qualitative research gives individuals a 
voice in the analytical process。 
。 Significant remendations: When the consequences of research are 
likely to result in remendations with significant consequences; 
for example changing work pa。。erns; shu。。ing down a unit or altering 
pay and conditions; qualitative research allows a。。itudes and feelings 
towards potential courses of action to be explored; leading hopefully to 
a less contentious oute。 
Researchers used to quantitative analysis frequently dismiss qualitative 
research as ‘unscientific’ and ‘anecdotal’。 It certainly doesn’t have to succumb 
to such criticism; as the array of tools used in qualitative research is 
large and the tools have a well…documented and rigorous methodology for 
their application。
256 The Thirty…Day MBA 
Observation 
The power of observation as a method of gathering data lies in the inconsistency 
between what people will say in an interview; or on a questionnaire; 
and what they actually do。 It’s not that people are necessarily lying; it’s 
just that their capacity for self…deception is o。。en high。 Customers may feel 
foolish admi。。ing they have difficulty finding their way around a shop and 
so would not record that fact。 That doesn’t mean that they don’t have a 
problem and that a pany would not gain valuable information from 
finding out about it。 
So observations can give valuable insights into how things look from an 
outsider such as a customer; supplier or prospective employee。 But such 
insights will only be representative of the time the researcher was observing 
and may not be indicative of the general level of service。 They are o。。en used 
to provide contextual information alongside some other research method。 
Observations themselves generally e in one of two forms: 
。 Participating observation: This is where the observer takes part in at 
least some aspect of what is being assessed in order to get a be。。er understanding 
of insider views and experiences。 This; for example; could 
involve going through the whole procedure of making a purchase or 
using a service; rather than standing on the sidelines watching others。 
This is the methodology used in mystery shopping。 
。 Pure observation: Here the observer stays aloof from the situation under 
assessment so 
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