Survey Research with SPSS
Survey Research with SPSS
Course Code:
CIT 2733
Semester:
Spring 2003
Instructor:
Sungbong Park
Credits:
3
Prerequisites:
Courses covering introduction to statistics, varying by academic Departments
Program:
Day time
Course
This course is providing an essential introduction to various functions of
Description:
SPSS such as data management, analysis and plotting graph etc. in the
basis on statistics. It is especially focused on survey research that covers
critical topics such as to design a questionnaire, to code and enter responses,
to manipulate and analyse data and eventually to prepare a final report that
concisely and clearly summarizes results. At the end of course, group project
will be assigned to conduct virtual survey on the subject which group has
chosen.
Course Aims:
After completing this course, students will be able to
 Deal with their own social science survey results according to statistics.
 Process the various data analysis procedures that are most frequently used
in social science.
 Create an analysis file with this data-set in SPSS format.
 Organize raw data into interpretable results and possess report-writing skills
required to present the findings of social survey research.
Readings:
- Using SPSS for Windows: Analyzing and Understanding Data, Samuel B.
Green, Neil J. Salkind and Theresa M. Akey, Prentice Hall, 1997 (optional)
- Supplemental materials(handouts, lecture slides and assignments) that will
be posted on the “L:”drive, \\TEROUTE\LECTURE\Sungbong\ (mandatory)
Class
SPSS is so rare to be found that class time would be the only time to use this
requirements:
program. Hence, course demands faithful efforts for attendance. For the
record, total attendance and attitude in the class will be reflected by final
grade. As the works required are of both individual and group nature, it is
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Survey Research with SPSS
important that you plan in advance your assignments and leave yourself
sufficient time for group meetings, becoming familiar with new software. Please
review carefully the lecture materials updated lesson by lesson. If you regularly
attend classes and keep up with the assignments, you will be successful both
in mastering the software package and receiving a good grade. Since all
assignments are due on the day nailed on the syllabus, no late assignments
will be accepted. Even if accepted, your mark will be compromised. In the spirit
of equal treatment to the entire class, no exceptions will be granted.
Evaluation:
-Assignment #1, Mid-term exam #1 (individual, written) after 1st session (5 weeks)
-Assignment #2, Mid-term exam #2 (individual, written) after 2nd session (5 weeks)
-Group project (Group, written and verbal presentation) at the end of semester.
This will be substituted for final exam.
Grading
Assignments (2)
10%  2
weights:
Mid-term Exams (2)
20%  2
Group project
30%
Attendance and contribution
10%
TOTAL
Grading
Scale:
100%
90-100%
A+
67-69%
C+
85-89%
A
63-66%
C
80-84%
A-
60-62%
C-
77-79%
B+
57-59%
D+
73-76%
B
53-56%
D
70-72%
B-
50-52%
D-
below 50%
F
Group
The objective of this project is to provide students with some experience in
Project:
applying the concepts and methods of survey research to understanding social
phenomena in real world. The project team that consists of four or five persons
will conduct a survey on its own, analysis the results through SPSS™ and
make a final report (made up of PowerPoint slides). Verbal presentation by one
of the group members is required as well as previous submission of the report.
Feedback:
If you have any questions or concerns about the lecture contents, teaching, or
grading, please do not hesitate to discuss them with me.
Your suggestions for improvement will contribute to a better class both now
and in future. (Office hours by appointment)
Office
Telephone
E-mail
#326 (old building)
70-42-90
sungbong@kimep.kz
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Survey Research with SPSS
Course schedule
Week / Date
Lecture topics
Calendar
Session 1
Getting started with SPSS
Lesson1: Overall introduction to course
Jan. 14
1
-orientation of course
-basic definition of statistics
-overview of SPSS
Lesson2: Processing raw data
Jan. 16
-entering data
-data view vs. variable view
-open various data format
Lesson3: Modifying data value
Jan. 21
2
-using SPSS:TRANSFORM to adjust data
-recode variables
-adding cases and variables
Lesson4: Descriptive statistics to summarize data
Jan. 23
-frequency distributions
-graphical representation
-using FREQUENCIES procedure to summarize data
Lesson5: Point estimates and dispersion measures
Jan. 28
3
-measures of central tendency
-measures of dispersion (variability)
-DESCRIPTIVES procedure
Lesson6: Techniques for subgrouping data
Jan. 30
-CROSSTABS procedure for combining variables
-EXPLORE procedure for exploring distribution
-using DATA:Split File to conduct subgroup analyses
Lesson7: Creating a chart
Feb. 4
4
-using GRAPHS:INTERACTIVE for plotting
-creating chart in the form of bar, dot, line, pie etc.
-creating a standard chart
Lesson8: Working with output
Feb. 6
-using the pivot table editor
-adjustment of graphs according to needs
-using predefined formats:TableLooks
Mid-term Ex. #1
Study guide
Lesson9: Additional functions in SPSS
Feb. 11 -time saving procedures with syntax
-how to get a tip from the help system
-creating custom menu items
5
Feb. 13
Mid-term Exam #1
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Assignment #1
Due on Feb. 20
Survey Research with SPSS
Session 2
Advanced analyses through SPSS
Lesson10: Probability distributions
Feb. 18 -definition of “Normal distribution”
-plotting normal curve with FREQUENCIES procedure
-sampling distribution of means
6
Lesson11: Inferential statistics
Feb. 20 -point estimation and sampling error
-confidence intervals
-Z-tests for comparing a large sample to a population distribution
Due of
Assignment #1
up to 6 p.m.
Lesson12: Comparison of two independent samples
Feb. 25 -t-test for comparing a small sample to a population distribution
-t-test for 2 independent samples
-ANALYZE:Compare Means procedure
7
Lesson13: Comparison of two related samples
Feb. 27 -independent vs. related observations
-t-test for 2 related(dependent) samples
- ANALYZE:Compare Means procedure
Ex. #1 results
announcement
Lesson14: Analysis of categorical data
Mar. 4
8
-Z-test of proportions
-independent vs. dependent and nominal vs. ordinal
-performing ANALYSIS:Nonparametic Tests
Lesson15: Measuring association between categorical
Mar. 6
variables
-defining the existence and strength of relationships
-nominal data: Chi Square, Goodman & Lambda
-ordinal data: Gamma & Kendall’s tau
Grouping of
project teams
Lesson16: Measuring association between continuous
Mar. 11
variables
-ordinal data: Spearman rho correlation
-nominal data: Pearson Product-Moment correlation
-CORRELATE:Bivariate Correlation procedure
9
Lesson17: Introduction to multiple regression
Mar. 13 -REGRESSION:linear and CORRELATE procedures
-the multiple regression model
-inferences for the slope and correlation
Mid-term Ex. #2
Study guide
Lesson18: Introduction to multivariate relationships
Mar. 18 -association and casuality
-controlling for other variables
-type of multivariate relationships
10
Mar. 20
Mid-term Exam #2
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Assignment #2
Due on Mar. 27
Survey Research with SPSS
Session 3
Multi-dimensional application of SPSS to various surveys
Lesson19: “Between” factor ANOVA designs
Mar. 25 -“Between Groups” single factor ANOVA design
-One-way ANOVA procedure
-multi-factor ANOVA designs
11
Lesson20: “Within” factor ANOVA designs
Mar. 27 -a priori and post hoc comparisons between group means in ANOVAs
-repeated measures: Single factor
-randomized block design: Two factors
Due of
Assignment #1
up to 6 p.m.
Lesson21: ANOVA designs with a covariate
Apr. 1
12
-analysis of covariate without interactions terms
-analysis of covariate with interactions terms
-comparing adjusted means
Lesson22: Mixed ANOVA designs
Apr. 3
-one between and on within factor design
-set up of the mixed ANOVA
- a priori and post hoc comparisons
Ex. #2 results
announcement
Lesson23: Case Study I
Due to submit
project proposal
(A4 1 page)
Apr. 8
-Psychology
13
Lesson24: Case Study II
Apr. 10
-Marketing 1
Lesson25: Case Study III
Apr. 15
-Marketing 2
14
Lesson26: Case Study IV
Apr. 17
-Marketing 3
Apr. 22
Presentation of group project 1
Apr. 24
Presentation of group project 2
15
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Filling up
course-evaluation
sheet