Didattica

Tutoring: Statistics

Department of Economics and Management “Marco Fanno”, University of Padua, Via Ugo Bassi 1, 35131, Padua, Italy - room 44.

01.10.2019

 

This course aims at introducing the basic concepts of applied statistics including probability, common distributions, descriptive statistics, statistical inference, and data analysis.

This course is designed for master students of Entrepreneurship Innovation and Business Administration (track in Management) at the Department of Economics and Management “Marco Fanno”, University of Padua.
This course is cohort-based, which means that there is an established start and end date, and that you will interact with other students throughout the course. In particular, students will be grouped such that one student having statistical background will study with three or four students who have no background on statistics.


Required Materials
• Book: OpenIntro Statistics, Diez, Barr and Cetinkaya-Rundel, third edition, 2015. The book is free to download from: https://www.openintro.org/download.php?file=os3&redirect=/stat/textbook/os3.php.
• Course notes available on Moodle.


Prerequisites
Students are encouraged to read the following documents in advance:
• OpenIntro Statistics, chapters: 1, 2, 3, (section 3.1), 4, 5 (sections 5.1, 5.2, 5.3), 6 (sections 6.1, 6.2, 6.3, 6.4), 7, 8.
• Online course: STAT 500-Applied Statistics, https://onlinecourses.science.psu.edu/stat500/1


Course Objectives
At the completion of this course, students will be able to:
1. Understand the role of statistics in doing the research.
2. Read and understand the statistical concepts from reports and papers.
3. Master the statistical methods to summarize and analyze data: descriptive statistics, confidence interval for population mean and proportion, hypothesis testing, Chi-square test for independence, linear regression model.
4. Interpret results from various computer packages (R, SPSS, SAS) and be able to perform appropriate statistical techniques.

 

Schedule and daily learning goals 

The schedule is tentative and subject to change. The learning goals below should be viewed as the key concepts you should grasp after each week, and also as a study guide before each homework and final exam.

Venue: All the lectures will be held at Department of Economics and Management “Marco Fanno”, University of Padua, Via Ugo Bassi 1, 35131, Padua, Italy - room 44.


Lecture 01, 01/10, from 08.30 to 10.30 at room 44

Overview, Collecting Data and Descriptive Statistics

• Introduction the role of statistics
• How to collect data
• Determine the quantitative and qualitative data
• Summarizing a data set by using statistical measure of central tendency and variability, and
using graphical presentation.
• Homework

 

Lecture 02, 03/10, from 08.30 to 10.30 at room 44

Introduction to Probability


• Definition of probability
• Random variable
• Some common probability distribution (normal, t-student, Chi-square)
• Homework


Lecture 03, 04/10, from 08.30 to 10.30 at room 44

Correct Exercises I and II 2/3 Course Syllabus


Lecture 04, 08/10, from 08.30 to 10.30 at room 44

Introduction to Statistical Inference: Confidence Interval
• Sampling distribution
• Statistical estimation
• Two-sided confidence interval for population mean
• Two-sided confidence interval for population proportion
• Homework

Lecture 04-05, 10/10 and 11/10, from 08.30 to 10.30 at room 44

Hypothesis Testing
• t-test for mean of one sample
• t-test for mean of paired data
• t-test for comparing two population means of independence data (equal variances and
unequal variances)
• Homework


Lecture 07, 15/10, from 08.30 to 10.30 at room 44

Correct Exercises III and IV


Lecture 08, 17/10, from 08.30 to 10.30 at room 44

Testing for Categorical Data and Normality
• Testing for normality of data
• Goodness-of-fit test
• Chi-square test for independence
• Homework


Lecture 09-10, 18/10 and 22/10, from 08.30 to 10.30 at room 44

Linear regression model
• Set-up a regression model
• Fitting model
• Model checking (the significant of coefficients, model assumptions)
• Model predicting
• Homework

 

Professor: Duc-Khanh To, Ph.D
E-mail: toduc@stat.unipd.it
Office: room 145, Department of Statistical Sciences, University of Padua, Via C. Battisti, 241;
I-35121 Padua, Italy

 

REGISTRATION ON:  https://www.economia.unipd.it/tutoring-statistics-0

For further information:
Segreteria didattica Dipartimento di Scienze Economiche e Aziendali "M. Fanno"
Via Ugo Bassi, 1 Padova
tel. 049 827 1230
didattica.economia@unipd.it