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Course outline
STATISTICS FOR CHAPTER ONE: INTRODUCTION
1.1. Definition of Statistics
MANAGEMENT 1.2. Classification of Statistics
1.3. Application of Statistics
ONE (I) CHAPTER TWO: DATA COLLECTION AND PRESENTATION

2.1. Data Collection

2.1.1. Classification of Data
2.1.2. Methods of Data Collection
2.2. Tabular Methods of Data Presentation
2.2.1. Frequency Distributions (Absolute, Relative and
Cumulative Distributions)
2.3. Graphic Methods of Data Presentation (Histograms,
Content Polygons, Ogive, Pie-Charts, Bar and Line Graphs)
“Nothing comes from nothing!” Prusak, 2001
Manamno G. Feb, 2022 2

Cont’d Cont’d
CHAPTER THREE: MEASURES OF CENTRAL 4.2. Probability Distribution
TENDENCY AND DISPERSION 4.2.1. Definition
3.1. The Use of Summation Notation 4.2.2. Basic concepts- discrete and
3.2. Central tendency measures continuous
3.3. Measures of dispersion random variables, expected value and
CHAPTER FOUR: PROBABILITY AND PROBABILITY
variance of discrete random variables
DISTRIBUTION 4.2.3. Discrete probability distributions
4.1. Probability Theory (Binomial, Hyper-geometric and Poisson
4.1.1. Basic definitions Distributions).
4.1.2. Fundamental concepts: - experiment and 4.2.4. Continuous probability distributions
event, events and their relationships, conditional, (Normal Distributions.)
joint, the probability tree, Baye's Theorem.
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1.1 Definition of Statistics

 The word Statistics has originated from the Italian word “Statista”
or the German word “Statistik” each of which means a political
state.
 It is believed that Statistics have originated from two main
sources, namely, government records and mathematics. In
all the countries of ancient culture, like Egypt, Judea and Rome,
there is evidence to show that they had some system of
1.1 Definition of Statistics collecting Statistics.
1.2 Classification of Statistics  Since Statistical data were collected for governmental
purposes such as taxation and evaluation of military strength,
1.3 Application of Statistics Statistics was then described as the “Science of Kings” or “the
science of statecraft”.
 On the other hand, Statistics has been considered as a branch
of mathematics because most of the Statistical methods are
5 6 based on the mathematical theory of probability.

Cont’d Cont’d
 Although the term Statistics is defined in a number of  Statistics can also be defined as a method (singular
ways, all the definitions cover two basic aspects. That sense). It is also in the sense of its second definition
is, Statistics may be defined as: that we consider Statistics as a subject. With this
 Statistical data (plural sense): “Statistics refer to the regard, Statistics may be defined as:
aggregates of facts affected to a marked extent by  “Statistics is the science which deals with the
multiplicity of causes, numerically expressed, methods of collecting, classifying, presenting,
enumerated or estimated according to reasonable comparing (analyzing) and interpreting numerical
standards of accuracy, collected in a systematic manner data collected to throw some light on any sphere
for a pre-determined purpose and placed in relation to of enquiry.”
each other.”
 “Statistics is the collection, presentation, analysis and
 This definition makes it clear that Statistics (as numeric
interpretation of numerical data.”
data) should possess the following characteristics.
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Cont’d
 Summing up all the above definitions, one can define Statistics
Characteristics of Statistics
preferably as:
 Statistics is the study of the principles and methods used
 Aggregate of facts/data
in the collection, presentation, analysis and interpretation
of numerical data in any sphere of enquiry.  Numerically expressed
 The term statistics can refer to numerical facts such as
 Affected by different factors
averages, medians, percents, and index numbers that help
us understand a variety of business and economic  Collected or estimated
situations.
 Statistics can also refer to the art and science of collecting,
 Reasonable standard of accuracy
analyzing, presenting, and interpreting data.  Predetermined purpose
 Statistics is concerned with:
 Processing and analyzing data  Comparable
 Collecting, presenting, and transforming data to  Systematic collection
9 assist decision makers. 10

Key Definitions(Basic Terms) Key Definitions(Basic Terms)…

 Data is collections of observations (such as  Experiment: A planned activity whose results yield
measurements, genders, survey responses). a set of data.
o a set of known or given things, facts.
 Population (universe) is the collection of things  A parameter: is a summary measure computed to
under consideration. describe a characteristic of the population.
o a complete set of things we want to investigate.  A statistic: is a summary measure computed to
 Sample is a portion of the population selected for describe a characteristic of the sample.
analysis. o a set of numerical data or figures that have been
o Smaller number of items picked from population.
collected systematically.
 Variable: A characteristic about each individual
element of a population or sample.
11 o A quantity that varies, the opposite of a constant. 12

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Key Definitions(Basic Terms)… Key Definitions(Basic Terms)…

Example: A college dean is interested in learning about  The experiment would be the method used to
the average age of faculty. Identify the basic terms in select the ages forming the sample and determining
this situation.
the actual age of each faculty member in the
 The population is the age of all faculty members at sample.
the college.
 The parameter of interest is the “average” age of all
 A sample is any subset of that population. For
example, we might select 10 faculty members and faculty at the college.
determine their age.  The statistic is the “average” age for all faculty in
 The variable is the “age” of each faculty member. the sample.
 One data would be the age of a specific faculty
member.
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Functions of Statistics 1.2 Classifications of Statistics

 Data can be used in different ways.
 In the business world, statistics has these
 The body of knowledge called statistics is sometimes
important specific uses: divided into two main areas, depending on how data are
 To summarize mass business data used. The two areas are:
 To draw conclusions from those data Descriptive statistics
Inferential statistics
 To make reliable forecasts about business
 Descriptive statistics: consists of the collection,
activities organization, summarization, and presentation of data,
 To improve business processes which are otherwise quite on wieldy and voluminous.
 It facilitates comparison  It seeks to achieve this in a manner that
 It presents facts in more precise manner meaningful conclusions can be readily drawn
from the data.
15  It helps in policy making, etc. 16

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Cont’d
1.3 Applications in Business and Economics
 These include measures of central tendency,
 Accounting
dispersion, skewness, and kurtosis.
 Public accounting firms use statistical sampling
 Inferential statistics: consists of generalizing procedures when conducting audits for their clients.
from samples to populations, performing
 Finance
estimations and hypothesis tests, determining
relationships among variables, and making  Financial advisors use a variety of statistical information,
predictions. including price-earnings ratios and dividend yields, to guide
their investment recommendations.
 It consists of methods that are used for drawing
 Marketing
inferences, or making broad generalizations,
 Electronic point-of-sale scanners at retail checkout
about a totality of observations on the basis of
counters are being used to collect data for a variety of
knowledge about a part of that totality. marketing research applications.

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Cont’d Limitation of Statistics

 Production
 A variety of statistical quality control charts are used
 Statistics does not deal with individual fact
to monitor the output of a production process.  Statistical Methods can be applied only to
 Economics aggregate of facts
 Economists use statistical information in making  Statistical Inferences are not exact
forecasts about the future of the economy or some  Statistical inferences are true only on an average
aspect of it.
 Statistics can be misused and misinterpreted
 For instance, in forecasting inflation rates, economists
use statistical information on such indicators as the  Increasing Misuse bring distrust in statistics
Producer Price Index, the unemployment rate, and  Common men can not handle statistics
manufacturing capacity utilization.  Skilled personnel like statisticians can only work
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with statistical facts properly

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END OF CHAPTER ONE!

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