1.
Statistics is a group of
methods used to collect,
analyze, present, and interpret
data and to make decisions.
1
WHAT IS STATISTICS?
2.
1. Collection of Data
Gathering information through
direct or interview, indirect or
questionnaire, observation,
registration and experiment
method.
2
PROCESSES:
3.
2. Tabulation or presentation
of data
Organizing data into texts,
tables, charts or graphs
3
4.
3. Analysis of Data
Extracting relevant
information from the organized
collected data.
4
5. 4. Interpretation of Data
Drawing conclusions from the
analyzed data. It involves the
formulation of conclusion about a
large group based on the
gathered data from a small
group.
5
13.
Descriptive Statistics
consists of methods for organizing, displaying,
and describing data by using tables, graphs, and
summary measures.
Concerned with summarizing and describing
important features of numerical data without
attempting to infer
(measures of central tendency, variability of scores, skewness and kurtosis)
13
TYPES OF STATISTICS
14.
Inferential Statistics
consists of methods that use sample results to help
make decisions or predictions about a population.
demands a higher order of critical judgment and
mathematical methods
aims to give info about a large group without dealing
with each and every element of these groups
(testing of hypothesis, t-test, z-test, simple linear correlaton, analysis of variance, chi-square
test, regression analysis, and time series analysis)
14
TYPES OF STATISTICS
21. 6. It is an essential tool in education,
government, office of justice programs,
business and economics, medicine,
experimental psychology, sociology,
sports, actuarial work, criminology,
employment figure, heredity, insurance,
poverty, public opinion polling and census.
21
22.
A population consists of all elements
– individuals, items, or objects –
whose characteristics are being
studied.
The population that is being studied
is also called the target population.
22
POPULATION and SAMPLE
23.
A portion of the population
selected for study is referred
to as a sample.
23
POPULATION and SAMPLE
25.
A survey that includes every number
of the population is called a census.
The technique of collecting
information from a portion of the
population is called a sample survey.
25
POPULATION VERSUS
SAMPLE
26.
A sample that represents the
characteristics of the
population as closely as
possible is called a
representative sample.
26
POPULATION and SAMPLE
27. A sample drawn in such a way that
each element of the population has a
chance of being selected is called a
random sample.
If the chance of being selected is the
same for each element of the
population, it is called a simple random
sample. 27
POPULATION and SAMPLE
28. Table 1.1 2012 Sales of Seven U.S. Companies
28
BASIC TERMS
Company
2001 Sales
(millions of dollars)
Wal-Mart Stores
IBM
General Motors
Dell Computer
Procter & Gamble
JC Penney
Home Depot
217,799
85,866
177,260
31,168
39,262
32,004
53,553
An element or
a member
An observation
or measurement
Variable
29.
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.
29
BASIC TERMS
30.
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.
30
BASIC TERMS
31.
The value of a variable for an element
is called an observation or
measurement.
31
BASIC TERMS
32.
A data set is a collection of
observations on one or more
variables.
32
BASIC TERMS
33.
Quantitative Variables
Discrete Variables
Continuous Variables
Qualitative or Categorical Variables
33
TYPES OF VARIABLES
34.
A variable that can be measured
numerically is called a quantitative
variable. The data collected on a
quantitative variable are called
quantitative data.
34
Quantitative Variables
35.
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.
35
Quantitative Variables
36.
A variable that can assume
any numerical value over a
certain interval or intervals is
called a continuous variable.
36
Quantitative Variables
37.
A variable that cannot assume a
numerical value but can be classified into
two or more nonnumeric categories is
called a qualitative or categorical
variable. The data collected on such a
variable are called qualitative data.
37
Qualitative or
Categorical Variables
39.
Raw Data – data in its original
form
Array - data arranged
from highest to lowest or vice
versa
39
Raw versus Array
40.
A. Nominal Scale
B. Ordinal Scale
C. Interval Scale
D. Ratio Scale
40
Levels of Measurements
(classification of data)
41.
Example 1-1
Annual salaries (in thousands of
dollars) of four workers are 75, 42, 125,
and 61. Find
a) ∑x
b) (∑x)²
c) ∑x² 41
SUMMATION
NOTATION
43. The following table lists four pairs of m and f values:
Compute the following:
a) Σm
b) Σf²
c) Σmf
d) Σm²f
43
Example 1-2
m 12 15 20 30
f 5 9 10 16
44.
44
Solution 2-1
m f f² mf m²f
12
15
20
30
5
9
10
16
5 x 5 = 25
9 x 9 = 81
10 x 10 = 100
16 x 16 = 256
12 x 5 = 60
15 x 9 = 135
20 x 10 = 200
30 x 16 = 480
12 x 12 x 5 = 720
15 x 15 x 9 = 2025
20 x 20 x 10 = 4000
30 x 30 x 16 = 14,400
∑m = 77 ∑f = 40 ∑f² = 462 ∑mf = 875 ∑m²f = 21,145
Table 1.4
