CHAPTER 1
INTRODUCTION
WHAT IS STATISTICS?
Definition
Statistics is a group of methods used to
collect, analyze, present and interpret the
data and to make decisions.
Two types of Statistics
Descriptive Statistics
Inferential Statistics
TYPES OF STATISTICS
Definition
Descriptive Statistics consists of methods
for organizing, displaying, and describing
data by using tables, graphs, and summary
measures.
TYPES OF STATISTICS
Definition
Inferential Statistics consists of methods
that use sample results to help make
decisions or predictions about a
population.
Characteristics of Statistics
➢ Statistics are aggregate of facts
➢ Statistics are affected to a marked extent by
multiplicity of causes
➢ Statistics are numerically expressed
➢ Statistics are enumerated or estimated according
to reasonable standards of accuracy
➢ Statistics are collected in a systematic manner
➢ Statistics are collected for a pre-determined
purpose
Limitations of Statistics
✓ Statistics does not deal with isolated
measurement.
✓ Statistics deals only with quantitative
characteristics.
✓ Statistical results are true only on an
average.
✓ Statistics is only a means.
✓ Statistics can be misused.
POPULATION VERSUS SAMPLE
Definition
A population consists of all elements – individuals,
items, or objects – whose characteristics are being
studied.
A portion of the population selected for study is
referred to as a sample.
Figure 1.1 Population and Sample
POPULATION VERSUS SAMPLE
Definition
A survey that includes every member of
the population is called a census. The
technique of collecting information from a
portion of the population is called a
sample survey.
BASIC TERMS
Definition
An element or member of a sample or
population is a specific subject or object
(for example, a person, firm, item, state,
or country) about which the information is
collected.
BASIC TERMS
Definition
A variable is a characteristic under study
that assumes different values for different
elements. In contrast to a variable, the
value of a constant is fixed.
BASIC TERMS
Definition
The value of a variable for an element is called
an observation or measurement.
A data set is a collection of observations on one
or more variables.
Table 1.1 Charitable Givings of Six Retailers in
2007
TYPES OF VARIABLES
1. Quantitative Variables
◼ Discrete Variables
◼ Continuous Variables
2. Qualitative or Categorical Variables
Quantitative Variables
Definition
A variable that can be measured numerically is called
a quantitative variable. The data collected on a
quantitative variable are called quantitative data.
For example: number of students present in a class,
number of cars in a parking lot, GPA of a students
Quantitative Variables: Discrete
Definition
A variable whose values are countable is called
a discrete variable. In other words, a discrete
variable can assume only certain values with
no intermediate values.
For example: people visiting a bank on any day,
number of cars of a family, students in a class
Quantitative Variables: Continuous
Definition
A variable that can assume any numerical value
over a certain interval or intervals is called a
continuous variable.
For example: age, height, weight, time
Qualitative or Categorical Variables
Definition
A variable that cannot assume a numerical value but
can be classified into two or more non-numeric
categories is called a qualitative or categorical
variable. The data collected on such a variable are
called qualitative data.
For example: hair colour, gender, religious status, eye colour,
economic status, student ID, Education Level, Car number.
Figure 1.2 Types of Variables
SUMMATION NOTATION
A sample of prices of five Statistical books:
$75, $80, $35, $97, and $88
The variable price of a book: x
Price of the first book = x1 = $75
Price of the second book = x2 = $80
Adding the prices of all five books gives
75+80+35+97+88 = x1+x2+x3+x4+x5 = Σx
Example 1-1
Annual salaries (in thousands of dollars) of
four workers are 75, 90, 125, and 61,
respectively. Find
(a) ∑x (b) (∑x)² (c) ∑x²
Example 1-1: Solution
(a) ∑x = x1 + x2 + x3 + x4
= 75 + 90 + 125 + 61
= 351 = $351,000
(b) (∑x)² = (351)² = 123,201
(c) ∑x² = (75)² + (90)² + (125)² + (61)²
= 5,625 + 8,100 + 15,625 + 3,721
= 33,071
Example 1-2
The following table lists four pairs of m and
f values:
Compute the following:
(a) Σm (b) Σf² (c) Σmf (d) Σm²f
Example 1-2: Solution
Table 1.4
(a) (b) (c) (d)
Thank you
