Introduction to statistical methodology.
Descriptive statistics: Frequency distributions, graphs, Measures of position and variability. Bivariate and conditional frequency distributions.
Introduction to probability and random variables.
Introduction to statistical inference: Statistics and sampling distributions
Estimation: Point and interval estimation.
Hypothesis Tests.
Comparison of two groups.
Correlation and linear regression
Course Content - Last names J-Z
Introduction to statistical methodology.
Descriptive statistics: Frequency distributions, graphs, Measures of position and variability. Bivariate and conditional frequency distributions.
Introduction to probability and random variables.
Introduction to statistical inference: Statistics and sampling distributions
Estimation: Point and interval estimation.
Hypothesis Tests.
Comparison of two groups.
Correlation and linear regression.
Alan Agresti (2022) Metodi statistici di base e avanzati per le scienze sociali. 5 Edizione, Pearson.
Learning Objectives - Last names A-I
The objective of the course is to allow students to read, interpreter, analyze statistical data from complete and sample survey
Learning Objectives - Last names J-Z
The objective of the course is to allow students to read, interpreter, analyze statistical data from complete and sample survey.
Prerequisites - Last names A-I
Elements of algebra and mathematics taught in secondary schools
Prerequisites - Last names J-Z
Elements of algebra and mathematics taught in secondary schools.
Teaching Methods - Last names A-I
Lectures
Teaching Methods - Last names J-Z
Lectures.
Further information - Last names A-I
materials from e-learning Moodle
Further information - Last names J-Z
Materials from e-learning Moodle.
Type of Assessment - Last names A-I
Written exam
Type of Assessment - Last names J-Z
Written exam.
Course program - Last names A-I
INTRODUCTION TO STATISTICAL METHODOLOGY: Basic concepts
DESCRIPTIVE STATISTICS: Absolute and relative frequency distributions; Graphs: bar plot and histogram, Measures of position: mean, median, mode. Measures of variability: Range; variance and standard deviation, coefficient of variation; Bivariate frequency distributions. Relative and percentage variations.
INTRODUCTION TO PROBABILITY AND RANDOM VARIABLES: Sample space and events; probability definitions; Conditional probability; Statistical independence; Discrete and continuous random variables; Bernoulli distribution; Normal distribution.
INTRODUCTION TO STATISTICAL INFERENCE: Parameters versus statistics; Sampling distributions; Sampling distribution of the sample mean; of the sample variance and of the sample proportion.
ESTIMATION: Point and interval estimation; Confidence interval for a mean; Confidence interval for a proportion.
HYPOTHESIS TESTS: Basic concepts; Neyman-Pearson approach; P-value approach; Test for a mean; Test for a proportion
CORRELATION AND LINEAR REGRESSION: Covariance and Pearson correlation coefficient; The linear regression model; Coefficient of determination
Course program - Last names J-Z
INTRODUCTION TO STATISTICAL METHODOLOGY: Basic concepts
DESCRIPTIVE STATISTICS: Absolute and relative frequency distributions; Graphs: bar plot and histogram, Measures of position: mean, median, mode. Measures of variability: Range; variance and standard deviation, coefficient of variation; Bivariate frequency distributions. Relative and percentage variations.
INTRODUCTION TO PROBABILITY AND RANDOM VARIABLES: Sample space and events; probability definitions; Conditional probability; Statistical independence; Discrete and continuous random variables; Bernoulli distribution; Normal distribution.
INTRODUCTION TO STATISTICAL INFERENCE: Parameters versus statistics; Sampling distributions; Sampling distribution of the sample mean; of the sample variance and of the sample proportion.
ESTIMATION: Point and interval estimation; Confidence interval for a mean; Confidence interval for a proportion.
HYPOTHESIS TESTS: Basic concepts; Neyman-Pearson approach; P-value approach; Test for a mean; Test for a proportion
CORRELATION AND LINEAR REGRESSION: Covariance and Pearson correlation coefficient; The linear regression model; Coefficient of determination.