Lecture 1[Mododecompatibilidad]

Techniques of Statistical

Analysis I

Lect_1: Breaking-ice session

Bruno Arpino

_{Practical information}

_{Course goals}

_{Course content}

Outline

2

_{Course content}

_Instructor:

Bruno Arpino

E-mail: [email protected]

https://sites.google.com/site/brunoarpino

_{Office hours:}

Some practical information

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_{Office hours:}

Monday 18:00 -19:00 or by appointment

Building Jaume I - room 20.182

_{Communications and materials will be given through the}

“Aula Global” (provided I will be able to use it!)

Suggestions

before the lecture…

_{take an “Happy Pill”}

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_{Provide the basic statistical knowledge for}

quantitative data analysis

in social science

research

_{Make students able to structure and conduct}

Course goals

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_{Make students able to structure and conduct}

autonomously an empirical research project with the

use of the statistical software

Stata

_{Support the compulsory “Final Research Project” due}

at the end of the master’s degree and provide a

_{Design - Planning/Implementing a study}

_{How to choose people (subjects) for the study, and how many?}

_{Description – Graphical and numerical methods for}

summarizing the data

Statistics provides methods for

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summarizing the data

_Inference

_{– Methods for making statements about a}

population (total set of subjects of interest), based on a

sample (subset of the sample on which study collects

data)

_{It’s not a statistical course stricto sensu}

_{It’s a course about statistical methods}

_applied

_to

social science

Focus will be on

What this course is and is not about...

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Focus will be on

_{INTERPETATION of results (also from software}

output)

_{Andy Field: …You need stats to answer questions. Scientists are}

curious people, and you probably are too. … to answer interesting questions, you need two things: data and an explanation of those data…

http://www.well.ox.ac.uk/~kanishka/Lectures/OUCS/Notes/Chapter%201%20-Why is my evil lecturer forcing me to learn

statistics?

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http://www.well.ox.ac.uk/~kanishka/Lectures/OUCS/Notes/Chapter%201%20-%20Discovering%20Statistics%20using%20SPSS%20by%20Andy%20Field.pdf

_{To measure the real world}

_{To assess relationship between variables}

_{To find empirical evidence to support theoretical hypothesis To make informed decisions}

_{The sexy job of the next 10 years (Hal Varian, chief economist at}

The research process

Statistics

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_{From: Any Field, DISCOVERING STATISTICS USING SPSS, Ch. 1. Available at:}

http://www.well.ox.ac.uk/~kanishka/Lectures/OUCS/Notes/Chapter%201%20-%20Discovering%20Statistics%20using%20SPSS%20by%20Andy%20Field.pdf

_{United Nations Population Information Network}

http://www.un.org/popin/data.html

Some data from the web

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_Google

_{What is the percentage of people that consider}

themselves Democrats?

_{Is the average income of immigrants lower than that of}

natives?

Examples of questions you will be

able to answer

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natives?

_{How (if at all) is happiness associated with income, job}

satisfaction, family situation, social life, religious beliefs,

political ideology?

_{Predict how the weather will be tomorrow}

(“Prediction is very difficult, especially about the

future.” Niels Bohr)

Unfortunately you will not be able to ...

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_{Predict who will win the Champions League}

_{Basic knowledge of descriptive statistics (mean,}

variance, graphs…)

_{Maths required: 4 basic arithmetic operations, square}

root, logarithms

Prerequisites

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_{1. Principles of}

_{Statistical Inference}

_{. Estimators}

and their properties. Confidence interval and test of

hypothesis for a mean and for a proportion.

Comparing means and proportions. ANalysis Of

Variance (ANOVA).

Course content

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Variance (ANOVA).

or … How to use information on a sample to make

(probabilistic) statements about a population

_2.

_{Linear regression}

_{model in social science}

research. Ordinary Least Square (OLS)

estimator. Assumptions. Interpretation of the

coefficients. Model building. Goodness of fit.

Transformation of variables. Categorical

Course content (cont’d)

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Transformation of variables. Categorical

explanatory variables. Interactions.

_{3. When the OLS is not appropriate: some examples.}

Introduction to longitudinal and multilevel modelling

or… “If anything can go wrong, it will” (Murphy's law)

Course content (cont’d)

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or… “If anything can go wrong, it will” (Murphy's law)

_Slides

Statistical

Methods for the Social Sciences

Compulsory readings

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Bacon.

(Whatever statistical text written for social scientists can substitute or complement the book by Agresti and Finlay. You can find some examples in the general bibliography)

Wells, C. (2003).

Regression with Stata

Data Analysis

Using Stata

Fernández Macías, and Fabrizio Bernardi (2009),

Cuadernos

Additional readings

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Fernández Macías, and Fabrizio Bernardi (2009),

Cuadernos

Metodológicos: Análisis de datos con Stata

.

_{Moore, D.S and G. McCabe (2006), Introduction to the}

Practice of Statistics, 5th edition. New York: W.H.Freeman

_{Lewis-Beck, M.S. Data Analysis: an introduction. SAGE}

Series on Quantitative Applications in the Social Sciences

n.103. University Press

General bibliography

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n.103. University Press

_{Dougherty, C. (2007), Introduction to Econometrics, third}

edition. New York: Oxford University Press.

_Three

_homework

_assignments.

_{They will be a mixture}

of conceptual and applied activities. Assignments will be

individual.

(20%)

_{An applied}

_{research project}

_.

_{Students are required to}

Assessment

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_{An applied}

_{research project}

_.

_{Students are required to}

design an applied research project. At the beginning of the

course, working groups (2-3 persons) will be established.

Details on the research project will be provided in a separate

handout.

(30%)

_{At the end of the course, students will demonstrate their}

achievements in a two-hour

final exam

(questions and

_{First, calculate a simple average of the 3 assignments grades.}

If, for example, the grades are 5, 6, 10 then the average is

(5+6+10) / 3 = 7

_{Then we need to calculate a weighed average of the three}

overall grade components. If, for example, the project grade is

8 and the overall exam grade is 6, then:

Overall grade calculation: an example

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8 and the overall exam grade is 6, then:

Overall grade = 7*0.2 + 8*0.3 + 6*0.5 = 6.8

Only the overall grade will be rounded (to the closest integer)

_{To pass, the overall grade must be not smaller than 5/10 AND}

8 Lab sessions

to be delivered the scheduled day

in class or sent by email

Schedule

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28 Sep Wed 15-17 40.245 LAB

29 Sep Thu 15-17 20.137 Lect

3

5 Oct Wed 15-17 40.245 LAB

6 Oct Thu 15-17 20.137 Lect

4

12 Oct Wed Holiday

13 Oct Thu 15-17 20.137 Lect Assignment 1

5

19 Oct Wed 15-17 40.245 LAB

20 Oct Thu 15-17 20.137 Lect

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in class or sent by email (by midnight of the

same day)

be sent by email by

the midnight of the day BEFORE the exam AND a paper copy delivered the day of the exam

5 20 Oct Thu 15-17 20.137 Lect

6

26 Oct Wed 15-17 40.245 LAB

27 Oct Thu 15-17 20.137 Lect

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2 Nov Wed 15-17 40.245 LAB Assignment 2

3 Nov Thu 15-17 20.137 Lect

8

9 Nov Wed 15-17 40.245 LAB

10 Nov Thu 15-17 20.137 Lect

9

16 Nov Wed 15-17 40.245 LAB

17 Nov Thu 15-17 20.137 Lect

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23 Nov Wed 15-17 40.245 LAB Assignment 3

24 Nov Thu 15-17 20.137 Lect

week 19-23 December.

Date to be confirmed!

Schedule (cont’d)

Date Time Room

19 Dec Mon t.b.c. t.b.c.

20 Dec Tue t.b.c. t.b.c.

21 Dec Wed t.b.c. t.b.c.

22 Dec Thu t.b.c. t.b.c.

23 Dec Fri t.b.c. t.b.c.

_{Students must attend at least 80% of the scheduled}

classes

_{80% of 20 = 16 classess}

Attendance

_{The joy of Stats}

http://www.gapminder.org/videos/the-joy-of-stats/

Do you think statistics is boring?

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_{Population growth explained with IKEA boxes}

… to you and me!

Good luck!!!

If something is not clear

(or you find mistakes in the slides)

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do not hesitate to come at office hours

or e-mail me