Applied statistics lecture 1 - Introduction

1. 1
Introduction to applied statistics
& applied statistical methods
Prof. Dr. Chang Zhu1
Aim
• Basic concepts about statistical analysis
• Apply the theories and techniques for
data analysis
• Apply the SPSS software to conduct data
analysis
• Interpret the output of data analysis

2. 2
Learning approach
• Theory/concepts integrated with practical
application/exercises
Planning
• Content and assignment

3. 3
• SPSS (originally, Statistical Package for the
Social Sciences)

4. 4
Working with data
• Starting with SPSS
Working with SPSS
• Data view
• Variable view

5. 5
Handling data
• Open
• Opening a datafile
• Open an excel file
• Import data
• Transform excel file to spss file
• Save
Data input: an example
•
Variable name Coding value
Student ID ID 1-50
Gender gender 1=male,
2=female
Economic level Econ 1=low,
2=middle
3=upper class
Reading level ReadLevel 1=low, 2= middle,
3= high

6. 6
Getting to know your data
• What are variables?
• Which types of variables are they?
• What are cases?
Variable names
• A variable
• a quantitative expression of a construct
• can be measured
• can vary
e.g. age, gender, educational background,
studying subject….

7. 7
Variable names in SPSS
• A variable name must be
• unique
• only in certain format: Eg. school, or
sch_name; not school-name, school
name
Type of variables
• Numeric: numbers
• String: letters, and numbers
Important to know: if it is a string
variable, you cannot compute it or
conduct numeric operations

8. 8
Type of variables
• Nominal
• Ordinal
• Interval (scale)
• Ratio (scale)
Type of variables
• Nominal
• Ordinal
• Interval
• Ratio
Categorical Data
Continuous Data
Scale

9. 9
Nominal and Ordinal
Categories
• Nominal Variables
– No meaningful Order in Choice
– E.g, gender (male, female)
profession (teacher, doctor, …)
Nominal and Ordinal
Categories
• Ordinal Variables
– Related in a Meaningful Sequence
– The order matters but not the difference between
values
– E.g, the order of winning in a competition (1, 2, 3)
hotel stars (1, 2, 3, 4)

10. 10
Categorical Data
Nominal and Ordinal Variables collect data
• Require Respondents to Choose from
o Independent categories
o Mutually exclusive categories
• Questions which ask for choice from 1 or
more categories
Interval Variables
• Same as Ordinal but always equally spaced
categories
• Cannot identify a Start Point on the scale
used; No absolute measure
•Inefficient ................................Efficient
1.........2................3..............4..............5
•No agreed definition of ‘Efficiency’

11. 11
Ratio Variables
• Ratio scales are like interval scales, but they
have true zero points.
• E.g. How many meetings did you attend this
week? (0, 1, 2, 3)
Continuous data
Interval and Ratio variables (Scale) collect data
• responses can be related to each other
• range of possible answers have an equal
distance between each other

12. 12
Measurement in SPSS
• In SPSS, there are three options for a
measurement:
• Nominal, Ordinal and Scale (either interval or
ratio)
Handling data
• Scoring
• Code/Recode
• Label
• Compute
• Split
• Select cases

13. 13
Compute
Recode
•

14. 14
PointCarré
• Introduction to Applied Statistics and
Applied Statistical Methods
• Example data
Exercise
• Computer SPSS Exercise:
Creating 4-6 variables in SPSS
Specify the correct measurement of the
variable
Create at least 10 cases
Calculate Mean, SD, Median, ….
Recode, compute….

15. 15
Exercise
• (more experienced students)
– Selecting of data
– Splitting of data
– Explore
– Graphics
– Charts
Assignment
• Create your own sample data
• Min. 10 variables
• Min. 50 cases

16. 16
• Questions?