Universitat Internacional de Catalunya

Statistics 2

Statistics 2
Second semester
Mètodes Quantitatius per a empresaris
Main language of instruction: Catalan

Other languages of instruction: English, Spanish

If the student is enrolled for the English track then classes for that subject will be taught in the same language and also in Spanish.
If the student is enrolled for the English track then classes for that subject will be taught in the same language.

Teaching staff

By appointment


In the event that the health authorities announce a new period of confinement due to the evolution of the health crisis caused by COVID-19, the teaching staff will promptly communicate how this may effect the teaching methodologies and activities as well as the assessment.

A course in statistics is offered in a wide variety of disciplines, from the social sciences to business to the natural sciences. The same statistical methods are applied across disciplines. Therefore, it should not be surprising that the tools you will learn to use in this course will benefit you in your future studies and careers regardless of whether your career interest is finance, accounting, strategy, management or marketing. In this course you will learn three important statistical procedures: (i) estimation, (ii) hypothesis testing and (iii) time series and forecasting

I believe statistics is best taught through a series of clear and carefully worked examples. A theoretical background to descriptive and inferential statistical methods will be provided, however a great deal of time will be spent teaching you how to apply the theory to the real world. Statistics is not about memorising formulas, rather it is about recognising the appropriate statistical test to conduct in a given situation. This requires practice by students. As we cover the topics, if you do not have a clear understanding of one topic it is wise to seek help immediately. The next topic will build upon the previous one. Please contact me for help if you have any questions.

Pre-course requirements

It is recommended that students have taken and understood the courses Statistics 1, Mathematics 1 and Mathematics 2”.


-   To develop a basic understanding of the different probability distributions

-   To learn the basics on how to conduct experiments and test hypotheses

-   To apply statistical terminology correctly


  • 19 - To analyse quantitative financial variables and take them into account when making decisions.
  • 28 - To be able to work in another language and use terminology and structures related to the economic-business world.
  • 31 - To develop the ability to identify and interpret numerical data.
  • 32 - To acquire problem solving skills based on quantitative and qualitative information.
  • 35 - To analyse time series.
  • 36 - To interpret quantitative and qualitative data and apply mathematical and statistical tools to business processes.
  • 40 - To be able to choose statistical methods appropriate to the object of analysis.
  • 42 - To be able to empirically analyse financial phenomena.
  • 43 - To acquire skills for using statistical software.
  • 50 - To acquire the ability to relate concepts, analyse and synthesise.
  • 51 - To develop decision making skills.
  • 52 - To develop interpersonal skills and the ability to work as part of a team.
  • 53 - To acquire the skills necessary to learn autonomously.
  • 54 - To be able to express one’s ideas and formulate arguments in a logical and coherent way, both verbally and in writing.
  • 56 - To be able to create arguments which are conducive to critical and self-critical thinking.
  • 64 - To be able to plan and organise one's work.
  • 65 - To acquire the ability to put knowledge into practice.
  • 66 - To be able to retrieve and manage information.
  • 67 - To be able to express oneself in other languages.

Learning outcomes

Understand quantitative research terminology, notation and methods, specifically those related to inference.

Ability to analyse and summarise information from lectures and materials provided by the lecturer.

Choose the appropriate statistical method to solve any economic problem.




Course introduction

Theme 10a: Continuous Probability Distribution – Uniform Distribution

-   Review of important concepts

-   Probability distribution function of Uniform Distribution

-   Mean and variance of Uniform Distribution

-   Examples and exercises

Theme 10b: Exponential Distribution

-   Probability density function of the exponential distribution

-   Mean and variance of the exponential distribution

-   Exercises

Theme 10c: Continuous Probability Distribution – Normal Distribution

-   Definition and characteristics

-   Standard normal distribution

-   Use of tables

-   Standardisation

Theme 10c: Continuous Probability Distribution – Normal Distribution

-   Group presentations and exercises (10% of the final mark)

Theme 10c: Continuous Probability Distribution – Normal Distribution

-   The coin toss exercise

-   Normal distribution and its relationship with the binomial and the Poisson

Computer room. Theme 10c: Comparison of Normal Distribution with the Poisson and the Binomial.

-   Exercise

Mid-course Examination (30% of the final mark)

Theme 11: Sampling

-   Sampling methods

-   Central limit theorem

-   Exercises

Computer room. Theme 11: Sampling

-   Practice on sampling methods

Theme 12: Estimation I

-   Confidence intervals for the mean when σ is known

-   Exercises

Theme 12: Estimation II

-   Confidence interval for the mean when σ is unknown

-   Student-t distribution

-   Use of t-distribution tables

-   Exercises

Theme 12: Practical Exercise

-   The M&M project

Theme 12: Estimation III

-   Confidence interval for a proportion

Theme 13a: One Hypothesis Sample Test

Theme 13b: Two Hypothesis Sample Test – Independent Samples

Theme 13b: Two Hypothesis Sample Test – Dependent Samples

Final Examination (60% of the final mark)


Teaching and learning activities

In person

Theoretical explanations will be given in the classroom using photocopied material and lists of problems. The lecturer's explanations will be shown on the blackboard and supplemented by the above material.

Theory will be combined with solving related problems.

Evaluation systems and criteria

In person


The marking will be divided between the mid-course and final examinations. The weighting between the different activities will be as follows:

10% in-class activity

30% mid-course examination

60% final examination

 If any student does not pass the examination at the first attempt and  is required to resit in July, the mark will be 100% based on the second-sitting examination

Bibliography and resources

Keller, G. “Statistics for Management and Economics”. South Western Cengage Learning.

Lind, D.A., Marchal, W.G. & S.A. Wathen. “Statistical Techniques in Business and Economics”. McGraw-Hill International Edition.

Prat, A., Tort-Martorell, X., Grima, P., & L. Pozueta. “Métodos Estadísticos: Control y Mejora de la Calidad”. Edicions UPC.

Wonnacott T. & Wonnacott R.J. “Introductory Statistics”. John Wiley & Sons.