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.

  • 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)

  • 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)

    • From the R software manual: R Data Import/Export:
      • read chapter 2: Spreadsheet-like data, (sections 1 and 2)

    • From the RStudio web 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.

    • 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)



    • From the book: An Introduction to Statistical Methods and Data Analysis:
      • study (in detail) chapter 3: Data Description.
    • Study the document: R sessions: 14-15 October 2013, available in the Tutorials and code page


    • Homework 4 (lectures of October 14 and 15)



    • 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 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)




    • 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 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)




    • 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;


    • Homework 7 (lectures of November 4 and 5)




    • 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;


    • Homework 8 (lectures of November 11 and 12)



    • From the book: An Introduction to Statistical Methods and Data Analysis:
      • study (in detail) chapter 4: Probability and Probability Distributions, Sections 11 and 12;


    • Homework 9 (lectures of November 18 and 19)







    • Study the maximum likelihood notes,
    • Study the document: Bernoulli maximum likelihood, available in the Tutorials and code page

    • Homework 10 (lectures of January 7)



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




    • 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 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




    • From the book: An Introduction to Statistical Methods and Data Analysis:
      • study (in detail) chapter 5: Inferences about population central values, Section 4;

    • 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




    • 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 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




    • 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;



An excerpt of the first two R sessions:




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:


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:



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