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Statistics for Social Sciences I: Introduction to Statistic
Engineering & Social Sciences Program
Madrid, Spain
Dates: mid Jan 2026 - early Jun 2026
Statistics for Social Sciences I: Introduction to Statistic
OVERVIEW
CEA CAPA Partner Institution: Universidad Carlos III de Madrid
Location: Madrid, Spain
Primary Subject Area: Sociology
Other Subject Area: Mathematics
Instruction in: English
Course Code: 16618
Transcript Source: Partner Institution
Course Details: Level 100
Recommended Semester Credits: 3
Contact Hours: 42
DESCRIPTION
1. Introduction.
1.1. Concept and uses of statistics.
1.2. Statistical terminology.
1.3. Typos of variables.
2. Analysis of univariate data.
2.1. Representations and plots of qualitative data.
2.2. Representations and plots of quantitative data.
2.3. Numerical summary of a sample of data.
3. Analysis of bivariate data.
3.1. Representations and plots of qualitative and discrete data.
3.2. Representations and numerical summaries of quantitative data: correlation and regression.
3.3 Introduction to time series analysis.
4. Probability and probabilistic models.
4.1. Random experiments, sample space, elementary and composite events.
4.2. Properties of probability.
4.3. Conditional probability and its properties.
4.4. Random variables and their characteristics.
4.5. Bernoulli trials and related distributions.
4.6. The normal distribution.
4.7 Other distributions
5. Introduction to statistical inference.
5.1. Outline and objectives.
5.2. Point estimators.
5.3. Interval estimators.
5.4. Fundamentals of hypothesis testing.
5.5. Tests for normal means.
5.6. Tests for proportions.
5.7. Testing for Independence
1.1. Concept and uses of statistics.
1.2. Statistical terminology.
1.3. Typos of variables.
2. Analysis of univariate data.
2.1. Representations and plots of qualitative data.
2.2. Representations and plots of quantitative data.
2.3. Numerical summary of a sample of data.
3. Analysis of bivariate data.
3.1. Representations and plots of qualitative and discrete data.
3.2. Representations and numerical summaries of quantitative data: correlation and regression.
3.3 Introduction to time series analysis.
4. Probability and probabilistic models.
4.1. Random experiments, sample space, elementary and composite events.
4.2. Properties of probability.
4.3. Conditional probability and its properties.
4.4. Random variables and their characteristics.
4.5. Bernoulli trials and related distributions.
4.6. The normal distribution.
4.7 Other distributions
5. Introduction to statistical inference.
5.1. Outline and objectives.
5.2. Point estimators.
5.3. Interval estimators.
5.4. Fundamentals of hypothesis testing.
5.5. Tests for normal means.
5.6. Tests for proportions.
5.7. Testing for Independence