Learning objectives
To have a general view of the main concepts of descriptive and inferential statistics
Prerequisites
Calculus, linear algebra
Course unit content
Part one
Introduction
• Collecting data, review of available statistical sources
• the data matrix; Graphic representations.
Summary of a phenomenon
• Frequency distributions and double entry tables
• averages (analytical mean and other indexes of position)
• Absolute and relative variability indices, concentration
• the shape of a distributions.
Time series
• Simple mobile and fixed base index numbers
• Time series concatenation with different bases; The average annual rate of variation
• compound price index numbers and deflated values at current prices
Relationships between two variables
• covariance and linear correlation coefficient
• the covariance matrix and correlation matrix
• linear regression: the ordinary least squares method; The interpretation of the parameters; model's goodness of fit;
• linear interpolation of time series
Part II
Introduction to probability and sampling
- Outlook of probability theories
- random variables: general aspects and applications
- theorems
- Sample distribution of statistical indexes
Estimating problems
- Average punctual estimate and relative frequency
- Estimate by average interval in case of large and small samples
- Estimate by relative frequency in case of large samples
Problems of hypothesis verification
- Introduction to statistical tests; Observed significance level (P-value)
- Tests in case of large and small samples - Tests on relative frequency in case of large samples
- Tests on two universes in the case of large samples
Univariate linear regression model
-Deriving the model of linear regression
- Estimation of model parameters and hypothesis testing
- Model checking. The meaning of ANOVA table.
Full programme
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Bibliography
M.A. Milioli, M. Riani S. Zani, Introduzione alla statistica per le applicazioni economiche, Uni.Nova, Parma, gennaio 2024.
Cerioli, M.A. Milioli, A. Corbellini, G. Morelli. Un'introduzione elementare all'inferenza statistica per le discipline aziendali, Uni.nova, Parma, 2022.
A. Cerioli, M. A. Milioli, M. Riani, "Esercizi di statistica", Uni.nova, Parma, 2023.
Teaching methods
Knowledge acquisition: frontal lessons
Acquisition of the ability of applying what has been studied: written tests
Acquisition of judgment: during the course students will be encouraged to detect strengths and weaknesses of the methods and of the basic statistic indices.
Acquisition of learning skills: for each topic we will start from the illustration of the problems which have to be solved and we will analyze critically the adopted solutions.
Acquisition of technical language. While teaching, the meaning of the terms commonly used in statistics will be described
Assessment methods and criteria
The assessment is conducted through a written test lasting 60 minutes and consisting of solving 4 open-ended exercises. Each exercise is assigned a score based on its complexity. The sum of the scores is 30. The test is considered sufficient only if a score of 18 is reached.
Part of the exercises concern descriptive statistics, while others refer to inferential statistics. The questions involve inquiries on some important points of theory and practice and are aimed at verifying the ability to understand, exercise judgment independently, and communicate using appropriate technical language. The extensive articulation of questions in different domains should allow evaluating both the learning ability and the ability to apply the acquired knowledge.
The use of a calculator is allowed for the test (strongly recommended CASIO fx-570ES PLUS or similar, on which some classroom exercises will be carried out) as well as the formula sheet (available on the Elly e-learning platform).
For second-year students, the possibility of taking a final exam at the end of the lessons will be evaluated.
The results of the written test will be published on the ESSE3 portal, and students will be able to view the outcomes during the teacher's office hours.
Other information
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2030 agenda goals for sustainable development
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