NOVA Information Management School

Statistics for Enterprise Data Analysis



Academic unit

NOVA Information Management School



Teacher in charge

Ana Cristina Marinho da Costa

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English


This curricular unit aims at supplying to the students the theoretical and practical knowledge about methodologies on summarizing data, and parametric and nonparametric statistical inference. Students will explore the core principles of statistics, from both the conceptual and applied perspectives. The students will acquire competences related to descriptive statistics, random variables, sampling and confidence intervals, and hypothesis testing. The students will clearly understand the conditions of applicability of each procedure. The concepts and principles will be applied and discussed using the environment, functions, and visualizations of Microsoft Excel using real-world concepts applicable to many industries, including medical, business, sports, insurance, etc.


Basic knowledge of Microsoft Excel functions and graphics.

Subject matter

The curricular unit is organized in seven Learning Units (LU):

LU1. Descriptive statistics

  • Introduction to statistics
  • Organizing information
  • Frequency distributions
  • Descriptive statistics
  • Outliers detection

LU2. Random variables

  • Introduction and concepts
  • Probabilistic models
  • Discrete random variables
  • Continuous random variables

LU3. Probability distributions

  • Binomial distribution
  • Poisson distribution
  • Normal distribution
  • Approximation of the Binomial distribution to Normal

LU4. Sampling and sampling distributions

  • Introduction and concepts
  • Non-probabilistic sampling designs
  • Probabilistic sampling designs
  • Sampling statistics and sampling distributions
  • Distribution of the sampling mean
  • Distribution of the sampling proportion

LU5. Interval estimation

  • Confidence intervals for the mean
  • Confidence intervals for the difference between means
  • Confidence intervals for the proportion
  • Confidence intervals for the difference between proportions
  • Sample size determination

LU6. Hypothesis testing

  • Concepts and methodology
  • Hypothesis testing for the mean
  • Hypothesis testing for the difference between means
  • Hypothesis testing for the ration between variances
  • Hypothesis testing for the proportion
  • Hypothesis testing for the difference between proportions
  • Correlation coefficient

LU7. Nonparametric testing

  • Introduction to nonparametric testing
  • Distribution fitting tests
  • Comparing independent samples
  • Comparing paired-samples
  • Spearman’s rank correlation test


  • Carvalho, A. (2015). Exercícios de Excel para Estatística. FCA – Editora de Informática.
  • Conover, W. J. (1999). Practical Nonparametric Statistics. 3rd ed., Wiley.
  • Hogg, R. V., Tanis, E. A. (2010). Probability and Statistical Inference. 8th Edition, New Jersey: Pearson/Prentice-Hall.
  • Newbold, P., Carlson, W. L., Thorne, B. (2012). Statistics for Business and Economics. 8th Edition, Boston: Pearson.
  • Pedrosa, A. C. e Gama, S. M. A. (2004). Introdução Computacional à Probabilidade e Estatística. Porto Editora.

Teaching method

The curricular unit is based on theoretical and practical lessons. A variety of instructional strategies will be applied, including lectures, slide show demonstrations, step-by-step applications using Microsoft Excel, questions and answers. The sessions include presentation of concepts and methodologies, solving examples, discussion and interpretation of results. The practical component is geared towards solving problems and exercises, including discussion and interpretation of results. A set of exercises to be completed independently in extra-classroom context is also proposed.

Evaluation method

1st call: Project (25%) + Midterm exam (35%) + End-of-semester exam (40%).

2nd call: Project (25%; not allowed to improve the grade from 1st call) + Exam (75%).