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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

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Learning approach

• Theory/concepts integrated with practical

application/exercises

Planning

• Content and assignment

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• SPSS (originally, Statistical Package for the

Social Sciences)

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Working with data

• Starting with SPSS

Working with SPSS

• Data view

• Variable view

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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

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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….

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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

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Type of variables

• Nominal

• Ordinal

• Interval (scale)

• Ratio (scale)

Type of variables

• Nominal

• Ordinal

• Interval

• Ratio

Categorical Data

Continuous Data

Scale

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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)

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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’

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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

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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

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Compute

Recode

•

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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….

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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

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• Questions?