This document provides an introduction to statistics. It defines statistics as collecting, organizing, presenting, analyzing, and interpreting data to assist in making more effective decisions. Descriptive statistics are used to summarize and describe data through tables, graphs and charts. Inferential statistics are used to make estimates, predictions, or generalizations about a population based on a sample. The document discusses why samples are used instead of entire populations, defines key statistical concepts like population and sample, and types of variables including nominal, ordinal, interval, and ratio levels of measurement.

1. UNIVERSITAS GADJAH MADA
INTRODUCTION
TO STATISTICS I
Valentino Risali, M.Sc
Department of
Economics

2. WHAT IS STATISTICS?
C O L L E C T I N G
A N A L Y Z I N G
O R G A N I Z I N G
P R E S E N T I N G
I N T E R P R E T I N G
D A T A
A S S I S T I N
M A K I N G M O R E
E F F E C T I V E
D E C I S I O N S

3. • Collecting: find and collect the data from the objects or
measurements. We can use questionnaire via Gform and
then transfer the data to Excel. Interview is another
method to collect data.
• Organizing: classify the data into their type or arrange
data to a specific order.
• Presenting: using the tables or diagrams to present the
data to public. From tables and diagrams we hope that
public could read and understand the data easily.
• Analyzing: using statistical methods to examine our
hypothesis.
• Interpreting: write the result of analysis into a statement.

4. WHY
STUDY
STATISTICS? Uncertainty is the
basis of statistics
Lots of our decisions are based on
uncertainties. Therefore, we need
statistics to make decision in a
situation of uncomplete information.

5. Descriptive
Statistics
methods
consisting of
organizing,
summarizing,
and presenting
data in the form
of tables,
graphs, and
charts
Inferential
Statistics
provide an
estimate, a
prediction, a
decision, or a
generalization
about the
population
based on
information
contained in a
sample.

6. Descriptive
Statistics
EXAMPLE : THE SALE OF APPLES IN USA
VARIES BY REGION. IT IS MOSLY SOLD IN
THE NORTH SIDE. FOLLOWED BY EAST,
SOUTH, AND WEST REGION.

7. Inferential
Statistics
EXAMPLE : THE AVERAGE NATIONAL EXAM
(UJIAN NASIONAL) SCORE OF ALL 9TH
GRADER IN INDONESIA BASED ON A
CERTAIN NUMBER OF SAMPLE

8. Population vs Sample

9. 1. The cost of studying all the items in a
population may be prohibitive.
2. Destruction of item being studied may be
required.
3. Not possible to test or inspect all members of a
population being studied.
4. Contacting the whole population would be
time consuming.
Why take a sample instead of
studying every member of the
population?

10. Population
THE COLLECTION
OR SET OF ALL
OBJECTS OR
MEASUREMENTS
THAT ARE OF
INTEREST TO
COLLECTOR
A SUBSET OF DATA
SELECTED FROM A
POPULATION
Sample
Population
Sample

11. Population Sample

12. Fricker’s is a family restaurant chain located primarily in the southeastern part of
the US.
Recently, the owner and founder, developed a new spicy flavor.
Before replacing the current flavor, he wants to be sure that patrons will like the
spicy flavor better.
To begin his taste test, Bernie selects a random sample of 15 customers.
Each sampled customer is given a small piece of the current chicken and asked to
rate its overall taste on a scale of 1 (did not like the flavor) to 20 (liked
the flavor).
Next, the same 15 participants are given a sample of the new chicken with the
spicier flavor and again asked to rate its taste on a scale of 1 to 20.
The results are reported here.
Is it reasonable to conclude that the spicy flavor is preferred?

13. Parameters
NUMBER CALCULATED ON
POPULATION DATA THAT
DESCRIBES A
CHARACTERISTICS OF THE
population

14. CASE STUDY
• A researcher of PLN selected residential
customer at random to estimate the amount
of electrical services last month.
• From a sample of 20 customers, he finds
that on average the amount charged to a
customer was Rp 100.000.
Identify the population and its parameters,
and the sample in the situation!

15. ANSWERS
• Population
all customers who used the service of PLN.
• Population parameter
the average amount charged to all users.
• Sample
the 20 customers surveyed by the researchers.
• The inference of interest
to estimate the amount charged per customers
on all customers

16. Types of Variables

17. Types of Variable

18. Types of Variable

19. Cross-section vs Time Series

20. Level of Measurements

21. Level of
Measurements

22. Nominal Data
Data that is classified into categories and cannot be
arranged in any particular order.
Properties:
1. Observations of a qualitative variable can only be
classified and counted.
2. There is no particular order to the labels.
Example: eye colour, religion, gender

23. Ordinal data
Data arranged in some order, but the differences between
data values cannot be determined or are meaningless
Properties:
1. Data classifications are represented by sets of labels or
names (high, medium, low) that have relative values.
2. Because of the relative values, the data classified can be
ranked or ordered.
Example: Class Ranking, education level

24. Interval data
Magnitude and equal interval between adjacent units but does
not have an absolute zero point. Similar to the ordinal level, with
the additional property that meaningful amounts of differences
between data values can be determined. There is no natural zero
point
Properties:
1. Data classifications are ordered according to the amount of
the characteristic they possess.
2. Equal differences in the characteristic are represented by
equal differences in the measurements.
Example: Exam Score, Temperature

25. Ratio data
Properties:
1. Data classifications are ordered according to the
amount of
characteristics they possess
2. The zero point and the ratio between two numbers is
meaningful.
Example: Price comparison of food, monthly income of
doctors

26. Thank You !!!
Questions?
Comments?

27. Link for access the Excel file of
Lind’s book:
www.mhhe.com/Lind18e