Stay Tuned!

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Recommended Book: Introduction to Business
statistics, a computer integrated approach by Alan H.
Kvanli, C. Stephen Guynes and Robert J Pavur.

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“Statistics is the science comprising rules and
procedures for collecting, describing,
analyzing and interpreting numerical data”
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Johaina Khalid, IMS, University of
Peshawar 3
To inform the public, For example
Results show that crest toothpaste prevents
tooth decay
Results show that cigarette smoking is
dangerous for health.
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Johaina Khalid, IMS, University of
Peshawar 4

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Application of statistics in business include
Quality Control
Product planning
Forecasting
Yearly reports
Personnel management
Market Research
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Johaina Khalid, IMS, University of
Peshawar 5
Statistics has got 2 main branches
DescriptiveDescriptiveDescriptiveDescriptive statisticsstatisticsstatisticsstatistics::::
The branch of statistics in which you collect data and
describe them is called Descriptive Statistics.
For Example: Calculating the average of test scores
of each class.
InferentialInferentialInferentialInferential statisticsstatisticsstatisticsstatistics::::
The branch of statistics in which you analyze and
interpret data. It is used to form conclusions about a
large group – a population by collecting a portion of
it- a sample
For example: Taking a sample of 100 items from
each batch of production and inferring that the
complete batch is of satisfactory quality if there are
less than 3 defective items in each batch.3/14/2017
Johaina Khalid, IMS, University of
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PopulationPopulationPopulationPopulation is the set of measurements (generally
belonging to a group of people or objects) that is
of interest.
A samplesamplesamplesample is the portion of the population about
which information is gathered.
RandomRandomRandomRandom SampleSampleSampleSample:::: is the true representative of the
population. A method of sampling in which each
and every item in the population has the same
chance of being collected for the sample.
If the sample includes the entire population, then
such a sample is called censuscensuscensuscensus....
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Johaina Khalid, IMS, University of
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A characteristic (such as average) of the
population is referred to as a parameter.
A characteristic (such as average) of the
sample is called statistic.
ExampleExampleExampleExample
Average age of all the students in Ims is a
parameter, whereas average age of a sample of
100 students from IMS is a statistic.
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Johaina Khalid, IMS, University of
Peshawar 8

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There are two types of numerical data
DiscreteDiscreteDiscreteDiscrete datadatadatadata:::: The data set in which there are
only limited specific possible values
ExamplesExamplesExamplesExamples::::
3,5,2,1,4,2,5,2,4,4 (Coded responses from a
survey)
No of children in a family
No of calls received in a call centre in 1 hour
Throwing a single die twice and recording the
average of the two throws. Possible values are
1,1.5,2,2.5,3,3.5,4,4.5,5,5.5,6
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Johaina Khalid, IMS, University of
Peshawar 9
Continuous DataContinuous DataContinuous DataContinuous Data
The data set in which any value over a
particular range is possible. There are no gaps
in continuous data values.
Examples:Examples:Examples:Examples:
heights of students in a class
Weights of students in a class
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Johaina Khalid, IMS, University of
Peshawar 10

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1. NominalNominalNominalNominal DataDataDataData:::: are merely labels or assigned
values. For example
Sex (1= male, 2= female)
Colour of eyes (1- blue, 2= green, 3= brown)
Mobile phone service used ( 1 = ufone, 2=
Mobilink, 3= telenor, 4= warid, 5= Zong)
Nominal data is generally used for calculating
the ProportionProportionProportionProportion of data in each category.
2. OrdinalOrdinalOrdinalOrdinal DataDataDataData:::: can be arranged in order such
as best to worst. For example
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Peshawar 11
Grades of students in an exam (A to F)
Results of a cross country race (1 = fastest, 2=
runner up, …… 10= slowest)
3- IntervalIntervalIntervalInterval datadatadatadata:::: The data set in which the order as well
as difference between the values have meanings. It is
meaningful to add, subtract and average such data. For
Example,
Temperature
4- RatioRatioRatioRatio DataDataDataData:::: Ratio data have all the properties of
Interval data and a definite zero point too. To decide if
your data are interval or ratio, ask yourself whether
twice the value is twice the strength, for example, is
100 degree F twice as hot as 50 degree, NO but a 4
acre land is twice as large as 2 acres land, so latter one
in ratio data.. These includes areas, counts, volumes,
weights etc.
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Peshawar 12

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Note that Discrete data may be nominal,
ordinal, interval or ratio but continuous data
may only be interval or ratio.
The statistical techniques do not distinguish
between interval and ratio data
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Johaina Khalid, IMS, University of
Peshawar 13