Transcript OMD - Samba

Statistics in SPSS
Lecture 1
Petr Soukup, Charles University in Prague
Basic Info
Info
Teacher: Petr Soukup (Dep. of Sociology)
 Consultation hour : Tue,9.30-10.30,
Jinonice, 3065
 Email: [email protected]


Student’s introduction
Info

Syllabus : see SIS (code JSM406)
https://is.cuni.cz/studium/eng/predmety/index.
php?do=predmet&kod=JSM406

Literature:
– Field, A. (2000). Discovering statistics using SPSS for Windows
:advanced techniques for the beginner. London : Sage. 2006, 2009
editions (2nd or 3rd)
– Norušis,M., J. (2005).SPSS 13.0 :statistical procedures companion.
New Jersey: Prentice Hall.
– Czech students: Mareš, Rabušic, Soukup. Analýza sociálněvědních dat
(nejen) v SPSS. 2015. muniPRESS, Brno. (ch. 2 – ch. 10)
Requirements

Grading will be based on homework assignments (8
mandatory assignments, each worth 5 points) and a final inclass exam (worth 60 points). Students may earn up to 100
total points.





Final grades:
86 - 100 points = grade 1
71 - 85 points = grade 2
60 - 70 points = grade 3
< 59 points = not passed

Note: It is expected that student is familiar with social science
reseach (have read some text about it or passed some course)
Main goal

Introduction to social science statistics

Introduction to SPSS environment

Final: Students are able to analyze social science
data for their purpose (e.g. preparation of thesis)

More topics can be found in Advanced courses
(IES and ISS at the Faculty)
Intro to statistics
Statistics

Different meaning of the the expression

Is it important? Why?

Is it difficult ? Why?

Is it boring?
Basic branches of statistics

Descriptive stats

Probability*

Mathematical stats (Statistical inference)
* nearly absent in the course (nice and small book:
John Haigh: Probability – A very short
Introduction, Oxford, 2012)
Special branches of statistics

Sampling theory

Time Series Analysis

and many others
Intro to descriptive stats
Basic concepts

Variable

Opposite of variable?

Examples of variables?
Types of variables
(different measurements)

Nominal (NOMEN)

Ordinal (ORDO)

Cardinal (scale)

Examples
Descriptive stats I

Why we use descriptive stats?

Different tools for individual types of variables
Descriptive stats II

Central tendency (What is typical value?)

Dispersion/Variance (Are there many
differencies or not?)

Distribution (Skewness and Kurtosis) – Is the
distribution of values symmetric and with high
peak or assymeric and flat?

Pictures and examples
Central tendency

Mode - nominal

Median - ordinal

Mean (Average) – cardinal

Logic of statistical procedures according to type
of variables

Graphical presentation of mean and median (why
mean is used so often?)
Review of statistical SW
Statistical software

What is statistical SW?

General vs. Specialized

Other tools for stats
General statistical software

IBM SPSS Statistics (v. 24) http://www01.ibm.com/software/analytics/spss/

Stata (v. 14) for universities, possibility to add do files
http://www.stata.com/

SAS (v. 10) not only for stat, for professionals
http://www.sas.com/en_us/home.html

Statistica (v. 12) – very nice graphics
http://www.statsoft.com/

R-project – the best and free (https://www.r-project.org/ )
Specialized statistical software

usually for one procedure or for the family of
close approaches

E.g. AMOS from IBM for structural equation
modelling (http://www03.ibm.com/software/products/en/spss-amos)
Other tools for stat

Mainly spreadsheets can do quite a lot from stats

Excel – functions, Data analysis tool and many
add-ins (free and commercial as well)

Calc (from Open Office) – only functions (the
same as in MS Excel)

All stats in JSM406 can be computed via Excel
or Calc (only outputs would not be so friendly
and nice)
HW
HW1


Try to describe three variables of different types,
i.e. one nominal, one ordinal and one cardinal
(scale)
For nominal and ordinal variables define possible
values (answers)
Thanks for your attention