# Statistics for Business & Economics

## Statistics for Business & Economics

__AIMS__Aim of the course is to provide students with a broad overview of statistical methods which may be exploited to tackle economics and business issues starting from data. Students will learn statistics by doing, exploiting R, a popular open-source software for data analysis. Emphasis on the applications of the techniques and on the interpretation of results will help students to appreciate the relevance of the statistical tools in real life applications.

__REQUIRED BACKGROUND__

A basic knowledge of elementary calculus is required. The course will start assuming a previous knowledge of statistics at an undergraduate level: the minimal prerequisite is a undergraduate course in probability and basic statistics.

__TEACHING__

Lectures and lab sessions.

__EXAMINATION METHODS__

Written + oral final exam.

__DETAILED SYLLABUS__(for further details, see the diary of class, weekly updated with the topics covered in the classroom)

__CONTENTS__

Data Description: exploring data and assumptions. Probability Distributions. Inferences about Population Central Values. Inferences Comparing Two Population Central Values. Inferences about Population Variances. Inferences about More Than Two Population Central Values. Multiple Comparisons. Categorical Data. Linear Regression and Correlation. Multiple Regression and the General Linear Model. Analysis of Variance. Analysis of Covariance.

__TEXTBOOKS__- R.L. Ott & M. Longnecker (2010). An Introduction to Statistical Methods and Data Analysis, Sixth edition, Brooks/Cole Cengage Learning. Belmont, USA

- M.L. Berenson, D.M. Levine, T.C. Krehbiel (2005). Basic Business Statistics, Thelfth edition. Prentice Hall.

- From the book: An Introduction to Statistical Methods and Data Analysis:

- read chapter 1:
__Statistics and the Scientific Method__,

- readchapter 2:
__Using Surveys and Experimental Studies to Gather Data__,

- study chapter 3:
__Data Description__.

- read chapter 1:
- From the R software manual: An Introduction to R:

- read chapter 1:
__Introduction and preliminaries__,

- read chapter 2:
__Simple manipulations; numbers and vectors__(excluding section 5),

- read chapter 3:
__Objects, their modes and attributes__,

- read chapter 5:
__Arrays and matrices__, (Sections 1, 2, 3, 4, 8)

- read chapter 6:
__Lists and data frames__, (Sections 1, 2, 3.1)

- read chapter 1:
- Study the document:
**An excerpt of the first two R sessions**, available in the*Tutorials and code*page

**Homework 1 (lectures of September 23 and 24)**

- From the R software manual: An Introduction to R:

- read chapter 4:
__Ordered and unordered factors__(sections 1 and 3),

- read chapter 7:
__Reading data from files__, (Sections 1 and 3)

- read chapter 13:
__Packages__, (Sections 1 and 3)

- read chapter 4:
- From the R software manual: R Data Import/Export:

- read chapter 2:
__Spreadsheet-like data__, (sections 1 and 2)

- read chapter 2:
- From the RStudio web page:

- read the page
__R Markdown__

- read the page
__Using R Markdown with RStudio__

- read the page
- Study the document:
**An excerpt of the second two R sessions**, available in the*Tutorials and code*page

**Homework 2 (lectures of September 30 and October 1)**

- From the book: An Introduction to Statistical Methods and Data Analysis:

- read (again) chapter 1:
__Statistics and the Scientific Method__,

- read (again) chapter 2:
__Using Surveys and Experimental Studies to Gather Data__,

- study (in detail) chapter 3:
__Data Description__.

- read (again) chapter 1:
- Study the document:
**R session - Monday 07 October 2013**, available in the*Tutorials and code*page

- Study the document:
**R session - Tuesday 08 October 2013**, available in the*Tutorials and code*page

**Homework 3 (lectures of October 7 and 8)**

- Theoretical homework (pdf format)

- From the book: An Introduction to Statistical Methods and Data Analysis:

- study (in detail) chapter 3:
__Data Description__.

- study (in detail) chapter 3:
- Study the document:
**R sessions: 14-15 October 2013**, available in the*Tutorials and code*page

**Homework 4 (lectures of October 14 and 15)**

- Theoretical homework (pdf format)

- Practical homework (html format) - (Rmd format)

- Theoretical homework (pdf format)

- From the book: An Introduction to Statistical Methods and Data Analysis:

- study (in detail) chapter 3:
__Data Description__;

- study (only exploratory part) chapter 11:
__Linear Regression and Correlation__, Section 7.

- study (in detail) chapter 3:
- Study the document:
**R session - Monday 21 October 2013**, available in the*Tutorials and code*page

- Study the document:
**R session - Tuesday 22 October 2013**, available in the*Tutorials and code*page

**Homework 5 (lectures of October 21 and 22)**

- Theoretical homework (pdf format)

- From the book: An Introduction to Statistical Methods and Data Analysis:

- study (in detail) chapter 3:
__Data Description__,

- study (only exploratory parts) chapter 11:
__Linear Regression and Correlation__, Sections 1, 2, 4 and 5.

- study (in detail) chapter 3:
- Study the document:
**R session - Monday 28 October 2013**, available in the*Tutorials and code*page

- Study the document:
**R session - Tuesday 29 October 2013**, available in the*Tutorials and code*page

**Homework 6 (lectures of October 28 and 29)**

- Practical homework (html format) - (Rmd format)

- From the book: An Introduction to Statistical Methods and Data Analysis:

- study (in detail) chapter 4:
__Probability and Probability Distributions__, Sections 1, 2, 3, 4 and 5;

- study (in detail) chapter 4:
**Homework 7 (lectures of November 4 and 5)**

- Theoretical homework (pdf format)

- From the book: An Introduction to Statistical Methods and Data Analysis:

- study (in detail) chapter 4:
__Probability and Probability Distributions__, Sections 7, 8, 9, 10 and 13;

- study (in detail) chapter 4:
**Homework 8 (lectures of November 11 and 12)**

- Practical homework (html format) - (Rmd format)

- From the book: An Introduction to Statistical Methods and Data Analysis:

- study (in detail) chapter 4:
__Probability and Probability Distributions__, Sections 11 and 12;

- study (in detail) chapter 4:
**Homework 9 (lectures of November 18 and 19)**

- Practical homework (html format) - (Rmd format)

**Simulation of the midterm exam (November 26)**

- Practical homework (html format) - (Rmd format)

- Study the maximum likelihood notes,

- Study the document:
**Bernoulli maximum likelihood**, available in the*Tutorials and code*page

**Homework 10 (lectures of January 7)**

- Theoretical and practical homework: pdf format

- From the book: An Introduction to Statistical Methods and Data Analysis:

- study (in detail) chapter 5:
__Inferences about population central values__, Sections 1, 2 and 3;

- study (in detail) chapter 5:

- Study the document:
**R sessions: 13-14 January 2014**, available in the*Tutorials and code*page

**Homework 11 (lectures of January 13-14)**

- Practical homework (html format) - (Rmd format)

- From the book: An Introduction to Statistical Methods and Data Analysis:

- study again (in detail) chapter 5:
__Inferences about population central values__, Sections 1, 2 and 3;

- study again (in detail) chapter 5:

- Study the paper: An introduction to the bootstrap with applications in R (available here)

- Study the document:
**R sessions: 20-21 January 2014**, available in the*Tutorials and code*page

**Homework 12 (lectures of January 20-21)**

- Practical homework (html format) - (Rmd format)

- From the book: An Introduction to Statistical Methods and Data Analysis:

- study (in detail) chapter 5:
__Inferences about population central values__, Section 4;

- study (in detail) chapter 5:

- Study the document:
**R session - Monday 27 January 2014**, available in the*Tutorials and code*page

- Study the document:
**R session - Tuesday 28 January 2014**, available in the*Tutorials and code*page

**Homework 13 (lectures of January 27-28)**

- Practical homework (html format) - (Rmd format)

- From the book: An Introduction to Statistical Methods and Data Analysis:

- study (in detail) chapter 5:
__Inferences about population central values__, Sections 5, 6, 7, 8 and 10;

- study (in detail) chapter 7:
__Inferences about population variances__, Sections 1 and 2;

- study (in detail) chapter 5:

- Study the document:
**R session - Monday 03 February 2014**, available in the*Tutorials and code*page

- Study the document:
**R session - Tuesday 04 February 2014**, available in the*Tutorials and code*page

**Homework 13 (lectures of February 03-04)**

- Practical homework (html format)

- (Rmd format)

- Practical homework (html format)

- From the book: An Introduction to Statistical Methods and Data Analysis:

- study (in detail) chapter 6:
__Inferences comparing two population central values__, Sections 1, 2, 4 and 6;

- study (in detail) chapter 7:
__Inferences about population variances__, Section 3;

- study (in detail) chapter 6:

**Homework 15 (lectures of February 10-11)**

- Practical homework (html format) - (Rmd format)

- From the R software manual: An Introduction to R:

An excerpt of the first two R sessions:

- Dataset Pizza (txt, tab-delimited format)

- Dataset Pizza (csv, comma separated values format)

- Dataset Pizza (xls, MS-Excel format)

An excerpt of the second two R sessions:

R session - Monday 07 October 2013:

R session - Tuesday 08 October 2013:

R sessions: 14-15 October 2013:

R session - Monday 21 October 2013:

R session - Tuesday 22 October 2013:

R session - Monday 28 October 2013:

R session - Tuesday 29 October 2013:

R sessions: 12-13 November 2013:

R sessions: 12-13 November 2013:

R session - Monday 19 November 2013:

R session - Tuesday 20 November 2013

**(new versions, adding also the replicate function)**:

Additional R script:

- A graphical exploration of the central limit theorem (HTML file) - (RMarkdown file)

R session: 7 January 2014:

R session: 13-14 January 2014:

R session - Monday 20 January 2014:

R session - Tuesday 21 January 2014:

R session - Monday 27 January 2014:

R session - Tuesday 28 January 2014:

R session - Monday 03 February 2014:

R session - Tuesday 04 February 2014:

**To download the softwares**:

**Software manuals**:

**Other useful resources on R**:

- Pizza dataset: [txt format] - [csv format] - [xls format]

- Mutual fund dataset: [csv format]

- ch3researchstudy dataset: [RData format] - [xls format]

- GradSurvey dataset: [txt format] - [csv format]

- GOLFCRD dataset: [CSV format] -[XLS format]

- GOLFBRD dataset: [CSV format] - [XLS format]

- GOLFFAC1 dataset: [CSV format] - [XLS format]