Transcript ECN 211 Statistics for Economics I

ECN 211
Statistics for Economics I
LECTURE 1
Assist. Prof. Evrim Turgutlu
What are statistics?
 A way to get information from data.
 A broad range of techniques, procedures for gathering,
organizing, analyzing and displaying quantitative data.
Assist. Prof. Evrim Turgutlu
Key concepts
Population: It represents all the elements of some
specified type.
E.g. All the households in a country: a population of
households
All the economics students in Turkey: a population of
economics students
Gathering data on every item in a population such as all
the households in a country is in many situations too
costly or too time consuming. In such cases,information
is obtained from part of a population.
Sample: A set of elements consisting a part of a
population is called a sample of the population.
Assist. Prof. Evrim Turgutlu
Population vs. sample
E.g. A sample of households in a country
A sample of economics students in Turkey
Assist. Prof. Evrim Turgutlu
Key concepts
 Parameter: A descriptive measure of a population.
 Statistic: A descriptive measure of a sample.
Assist. Prof. Evrim Turgutlu
Kinds of statistics

1.
2.
There are two main kinds of statistics:
Descriptive statistics: These are used to describe a set of
quantitative data.
It deals with organizing, summarizing and presenting data in a
convenient and informative way.
There are graphical and numerical techniques in descriptive
statistics.
Inferential statistics: It is the process of making an
estimate, prediction or decision about a population based on
sample data.
In order to achieve this goal a sample should be selected in a
manner such that each element of the population has an
equal chance of being included in the sample. Also selection of
one member should have no effect on the selection of any
other member.
Assist. Prof. Evrim Turgutlu
Key concepts
Variable: It is any characteristic of a population or sample
that is of interest to us.
E.g. What are the main characteristics of an economy?
GDP, Inflation, unemployment, interest rate...
Data: They are actual measures of variables.
Assist. Prof. Evrim Turgutlu
Types of data
1.
Quantitative data: Values are real numbers and
arithmetic calculations are valid. E.g. Age, income,
weight...
2. Qualitative data: Values are names of possible
catgories. E.g. Gender, race, occupation...
3. Ranked data: Values represent the ranked order of
responses. E.g. Quality of a product 1. Excellent, 2.
Good, 3. Fair, 4. Poor
!!! Knowing the type of data being used is important
because it is one of the factors that determines the
statistical techniques should be used.!!!
Assist. Prof. Evrim Turgutlu
Types of data
Data can be classified according to whether observations are
measured at the same time (cross-sectional data) or
whether they represnt measurements at successive points in
time (time-series data).
Assist. Prof. Evrim Turgutlu
DESCRIPTIVE STATISTICS
When you have a huge mass of data, reducing them yo an
easily comprehended summary is a very important thing.
First, we will learn about those techniques.
Assist. Prof. Evrim Turgutlu
FREQUENCY DISTRIBUTION
Frequency distributions organize and summarize data by
displaying in a table how often specific scores were
obtained.
Step 1. Constructing frequency distribution table
Step 2. Constructing charts and graphs that give visual
representation of patterns which exist in data sets.
Assist. Prof. Evrim Turgutlu
FREQUENCY DISTRIBUTION
Frequency distribution is a tabular summary of a set of data
showing the frequency (or number) of items in each of
several nonoverlapping classes.
Assist. Prof. Evrim Turgutlu
FREQUENCY DISTRIBUTION
Example: Consider the
quantitative data. The data
provide the weekly earnings of
20 manufacturing workers in
dollars.
What information can you get
from these dta?
12
14
14
18
15
15
18
17
20
27
22
23
22
21
33
28
14
18
16
13
Assist. Prof. Evrim Turgutlu