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SPS215 STATISTICS FOR SOCIAL SCIENCES
Full Course Title:
Statistics for Social Sciences
Statistika i drustvene nauke
Course Code:
Course Level/BiH cycle:
ECTS credit value:
SPS215
I cycle; 1st year
6
Student work-load:
For the whole semester:
Length:
Faculty/School/Department:
Lectures
Tutorial /
Practical training
Project
Individual
learning
TOTAL
45
30
30
45
150
Fall 2014
FASS; Social Sciences
Course leader:
Assist. Prof. Dr Ali Caksu (assisted by Sen. Assist. Velid Draganovic)
Contact details:
Office:
F3.14
e-mail:
vdraganovic@ius.edu.
ba
Office hours:
Mon 12:00-13:00
AM
Tue 10:00-13:00
PM and by appt.
Phone:
033 957 329
Site:
Lectures: IUS main campus building – F1.24
Tutorial: F1.24
Host Study Program:
Social and Political Sciences
Course status:
Programme required course;
Pre-requisites:
None
Access restrictions:
I cycle students only
Assessment:
Homeworks, quizzes, project paper,presentations, exams.
Date validated:
September 20, 2013
Course aims:
The aims of this course are:
To enrich students statistical literacy.
To develop students' understanding of various variables and scales of measurement.
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To enable students to perform basic methods of inferential statistics.
To develop students’ ability to choose inferential testing methods appropriate to real life
situations related to fields of their scientific and research interests.
To develop students' ability to interpret outputs from computer packages and
programmes.
To assist students to develop analytic and comparative skills.
Learning outcomes:
Indicative syllabus content:
Learning delivery:
Assessment Rationale:
Assessment Weighting:
Essential Reading:
On successful completion of this course IUS student will be able:
1. To demonstrate statistical literacy.
2. To recognise different types of variables and generate appropriate scales of their
measurement.
3. To perform basic inferential statistics methods and tests.
4. To distinguish and choose inferential testing methods appropriate to real life
situations related to fields of their scientific and research interests.
5. To interpret outputs from computer packages and programmes.
6. To demonstrate analytic and comparative skills.
This is an introductory course in the statistics for social sciences purposefully designed for
students of political sciences and international relations. This course provides an introduction to
descriptive and inferential statistics, with the purpose of preparing students for performing and
consuming quantitative research. The course covers the following topics: the sample mean and
variance, random variables, elementary finite probability, normal probability distribution;
sampling, point and interval estimation, hypothesis testing; regression, correlation, t-test,
bivariate distributions and chi-square tests.
This course employs a range of teaching and learning methods (lecturing, written assignments,
presentations, peer presentation analyses, group discussions, solving exercises). Students have
three hours lectures and two hours practical training a week. Students are also expected to realise
a project and present it. Learning will consist of knowledge acquisition and practical knowledge
gained from the class discussions and debates. Consultations and regular homework assignments
will guide students’ individual learning and students’ progression in acquiring required knowledge
and practice will be additionally checked through quizzes and final exams.
In order to enable students to develop a critical and evaluative understanding of real life issues
and ability to analyze them from a quantitative viewpoint, they are expected to demonstrate
commitment and diligence at any time. Appropriate assessment methods to help students to stay
focused and active, and fully benefit from the Program include presentations, project paper
writing, homeworks, exercise based quizzes, theoretical quizzes, exams. Those methods will check
their critical, analytical and comparative skills and acquisition of statistical terms and concepts, as
well as their ability to apply them to real life issues which are interesting for research.
Presentations:
10%
Paper and homeworks: 30%
Quizzes:
20%
Final exam:
40%
Hinton, Perry, (2004), Statistics Explained: A Guide for Social Science Students, 2nd ed., Routledge
Agresti, A., Finlay, B., (2009) Statistical Methods for Socical Sciences, 4th ed. Pearson
Recommended readings:
Sirkin, Mark, (editor), (2005), Statistics for the Social Sciences, 3rd ed., Sage Publications
Healey, Joseph F., (2008), Statistics: A Tool for Social Research, 8th ed., Wadsworth Publishing
Gravetter, Frederick J., Wallnau, Larry B., (2008), Statistics for the Behavioral Sciences, 8th ed.,
Wadsworth Publishing
Intranet web reference:
N/A
Important notes:
Expected knowledge of:
1. Writing and communication ability
2. Practical knowledge of basic mathematical operations
3. Basic logical operations
Course policies:
Assignments: Each student should complete their assignment on time.
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Lateness in Assignments: The due date and time for each homework will be specified on
the assignment handout itself. Late submissions will be penalized by gradual decrease
in homework grades, 15% decrease for each working day.
Academic Integrity: Any cheating on examinations or quizzes or offering the work of
another as one's own in an assignment is regarded as a serious offence to the academic
integrity.
Important dates:
Quiz 1: 06/11/13
Quiz 2: 11/12/13
Final exam: 15th week (17/01/14)
Quality Assurance:
Student surveys, discussion on course, student appeals, e-mails, direct (formal) feedback at the
end of the semester by students, assistants and other colleagues
Course schedule:
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Week
Lesson
/ Date
1
Topics to be covered
Class activities
Lab
Problems/
Readings
activities Assignments
(Homework)
08/10/14 Course Introduction

Course Overview
Lecturing
No lab
activities
1
09/10/14
Discussion and analysis of key terms and
concepts
2
2
Descriptive statistics

Measures of position

Measures of spread
Lecturing
No lab
activities
15/10/14
2
16/10/14
3
22/10/13
Learning objectives
(After this lesson
student will be able to:)
Chapter 1, 1. Identify key terms and
concepts.
Introductio
2.
Identify variables and
n in Perry.
scales for their
(2004).
measurement
Statistics
3.
Explain how statistics
Explained.
is related to research
pp 1-5,
Chapter 5,
sampling
pp 47-57
1. Calculate sample mean
Chapter 2,
2. Recognize sample
Descriptive
mode and median
statistics in
3. Calculate sample
Perry.
standard deviation
(2004).
Statistics
Explained.
pp 6-23
Mind-mapping ethics
Probability and probability
Lecturing
distributions

Concept of probability Mind-mapping connection between event and
No lab
activities
Chapter 3,
Standard
1. Define main features of
probability distributions
2. Explain main features of
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

3
23/10/14
4
29/10/14
4
30/10/14
5
05/11/14
5
06/11/14
6
12/11/14
Basic probability rules probability in coordinate system
Conception
of
Group discussion
probability distribution
scores in
Perry.
(2004).
Statistics
Explained.
pp 25-34
normal probability
distribution
Exercise solving
Sampling and sampling
Lecturing
distribution

Concept of sampling

Normal distribution

Standard
normal
distribution
and
standard scores
No lab
activities
1. Explain concept of
Chapter 4,
sampling
Probability
2. Explain importance of
distribution
sampling distribution for
s in Agresti
inferential statistics
Finlay
(2009).
Statistical
Methods
pp 73-99
Exercise solving
Evaluation and tutorials
Tutorials, exercise solving
No lab
activities
Quiz 1
Confidence intervals



Concept of estimation
Point estimation
Confidence interval
Lecturing
No lab
activities
Chapter 5,
Statistical
inference:
Estimation
in Agresti
Finlay
1. Differentiate between
point and interval
estimation
2. Recognize main
components of
confidence interval and
5
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(2009).
Statistical
Methods
pp 107-133
6
13/11/14
7
19/11/14
Exercise solving
Confidence intervals



7
20/11/14
8
26/11/14
27/11/14
Lecturing
1. Recognize main types
Chapter 5,
of confidence intervals
Statistical
and apply them
inference:
2. Interpret calculated
Estimation
confidence interval
in Agresti
Finlay
(2009).
Statistical
Methods
pp 107-133
Confidence
interval
for mean
Confidence
interval
for proportion
Confidence
interval
for mean difference
Exercise solving
Hypothesis testing


8
calculate them
Lecturing, presentations
Mean hypothesis
Proportion hypothesis
No lab
activities
Chapter 6,
Hypothesis
testing with
one
sample in
Perry.
(2004).
Statistics
Explained.
pp 59-72
1. Explain the process
of hypothesis testing
2. Perform simple
hypothesis testing
Presentations
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9
03/12/14
9
04/12/14
10
10/12/14
10
11/12/14
11
17/12/14
Hypothesis testing
Lecturing, presentations, presentations

Mean
difference
analysis
hypothesis
No lab
activities
1. Perform bivariate
Chapter 8,
hypothesis testing
Hypothesis
2. Interpret results of
testing with
hypothesis testing
two
samples in
Perry.
(2004).
Statistics
Explained.
pp 81-92
Presentations
Evaluation and Tutorial
Exercise solving
No lab
activities
Quiz 2
Association
and
Lecturing
dependence:

Contingency tables

Chi-square test
No lab
activities
Chapter 8,
analyzing
Association
between
Categorical
Variables
in Agresti
Finlay
(2009).
Statistical
Methods
pp 221-247
1. Present data in
contingency table
2. Perform chi square test
of dependence between
two categorical variables
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11
18/12/14
12
24/12/14
12
25/12/14
13
31/12/14
13
01/01/15
14
07/01/15
Exercise solving
Correlation
and
Lecturing
Regression:

Linear relationships

Least
squares
prediction equation
No lab
activities
Chapter
1. Determine prediction
20, Linear equation
Correlation
and
Regression
in Perry.
(2004).
Statistics
Explained.
pp 261-281
Discussion
Correlation
and
Lecturing
Regression:

The linear regression
model

Measuring
linear
association:
correlation
No lab
activities
1. Apply prediction
Chapter
equation
20, Linear
2. Analyze coefficients of
Correlation
regression equation
and
Regression
in Perry.
(2004).
Statistics
Explained.
pp 261-281
Exercise solving
Introduction to advanced
Lecturing
topics:

ANOVA

Multivariate statistics
No lab
activities
Chapter
1. Discuss relationships
10,
between variables
Introductio
n to
Analysis of
Variance in
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Perry.
(2004).
Statistics
Explained.
pp 1-5
14
08/01/15
15
14/01/15 Review Week and Final
Examination
15/01/15
Class Discussions
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