ID:
87097
Dettaglio:
SSD: Statistics
Duration: 72
CFU: 9
Located in:
BERGAMO
Url:
BUSINESS ADMINISTRATION - 87-270/PERCORSO COMUNE Year: 2
Year:
2025
The course has two goals. Firstly, it provides students with the theory of descriptive statistics, of probability and inferential statistics. Secondly, it teaches students how to use statistics for analyzing real data by using Excel. Special attention will be given business, economics applications with reference to social, ecological and technological transactions.
Good knowledge of the topics taught in the first year course “Calculus” and “Computer Sciences” (with respect to the use of Excel).
Class lessons (72 hours).
During the teaching through the use of the Kahoot software, the level of understanding of the topics will be tested periodically.
Excel Lab during the teaching period and in preparation for exam sessions.
The exam in the computer class consisting of exercises to be solved using Excel (25 points) and 10 multiple choice theory questions (7 points).
The test is passed if the number of correct answers in the theory part is at least equal to 5 and if the total mark (Theory + Excel) is at least equal to 18.
Elements of univariate descriptive statistics
Frequency tables, graphical summaries (plots), summary statistics (mean, mode, median and quantiles), variability indexes (variance, standard deviation, coefficient of variation), skewness. - Time series and index numbers
Elements of bivariate descriptive statistics
Contingency table, statistical independence and chi-square index for association. Covariance and correlation coefficient, regression line and goodness of fit.
Elements of probability
Definition of probability, probability theorems, independent events, conditional probability, law of total probability, Bayes' theorem.
Random variables
Definition, probability distribution, density function, cumulative distribution, expected value and variance. Examples of random variable: Bernoulli, Binomial, Poisson, Uniform, Normal, T-Student. Linear combination of random variables and central limit theorem.
Elements of point estimate statistics
Sample mean, sample variance, sample proportion and their properties.
Confidence intervals
General theory confidence intervals for the mean and the proportion.
Hypothesis testing
General theory and hypothesis test for the mean and the proportion.
Regression
Parameters estimate, goodness of fit, significance test and ANOVA.
All these topics will be taught first from a theoretical point of view and then through application with real data using Excel