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Introduction to Statistical Modeling
Engineering & Social Sciences Program
Madrid, Spain
Dates: mid Jan 2026 - early Jun 2026
Introduction to Statistical Modeling
OVERVIEW
CEA CAPA Partner Institution: Universidad Carlos III de Madrid
Location: Madrid, Spain
Primary Subject Area: Computer Sciences
Instruction in: English
Course Code: 16485
Transcript Source: Partner Institution
Course Details: Level 100
Recommended Semester Credits: 3
Contact Hours: 42
DESCRIPTION
1. Introduction to Statistical inference.
1.1. Population and sample
1.2. Random sampling
1.3. Fundamental sampling distributions
1.4. Point estimation of parameters
1.4.1. Definitions
1.4.2. Method of moments
1.4.3. Maximum likelihood estimation
2. Confidence intervals for a single sample
2.1. Introduction
2.2. CI on the mean
2.2.1. Normal population with known variance
2.2.2. Large sample
2.2.3. Normal population unknown variance
2.3. CI on the proportion
2.3.1. Large-sample
2.4. CI on the variance
2.4.1. Normal population
3. Test of hypotheses for a single sample
3.1. Introduction
3.2. Type I and Type II Errors
3.3. Power of a statistical test
3.4. P-value
3.5. HT on the mean
3.5.1. Normal population with known variance
3.5.2. Large sample
3.5.3. Normal population with unknown variance
3.6. HT on the proportion
3.6.1. Large sample
3.7. HT on the variance
3.7.1. Normal population
4. Statistical inference for two samples
4.1. Introduction
4.2. Difference in means
4.2.1. Normal populations with known variances
4.2.2. Large samples
4.2.3. Normal populations with unknown variances
4.2.4. Normal populations with unknown equal variances
4.2.5. Normal populations, paired observations.
4.3. Difference in proportions
4.3.1. Large samples
4.4. Ratio of the variances
4.4.1. Normal populations
5. Analysis of Variance
5.1. Introduction
5.2. One-way ANOVA
5.3. ANOVA table
5.4. Multiple comparisons
5.5. Two-way ANOVA.
6. Goodness of fit tests
6.1. Introduction
6.2. Chi-square tests
6.3. Kolmogorov-Smirnov test
6.4. Graphical tools
1.1. Population and sample
1.2. Random sampling
1.3. Fundamental sampling distributions
1.4. Point estimation of parameters
1.4.1. Definitions
1.4.2. Method of moments
1.4.3. Maximum likelihood estimation
2. Confidence intervals for a single sample
2.1. Introduction
2.2. CI on the mean
2.2.1. Normal population with known variance
2.2.2. Large sample
2.2.3. Normal population unknown variance
2.3. CI on the proportion
2.3.1. Large-sample
2.4. CI on the variance
2.4.1. Normal population
3. Test of hypotheses for a single sample
3.1. Introduction
3.2. Type I and Type II Errors
3.3. Power of a statistical test
3.4. P-value
3.5. HT on the mean
3.5.1. Normal population with known variance
3.5.2. Large sample
3.5.3. Normal population with unknown variance
3.6. HT on the proportion
3.6.1. Large sample
3.7. HT on the variance
3.7.1. Normal population
4. Statistical inference for two samples
4.1. Introduction
4.2. Difference in means
4.2.1. Normal populations with known variances
4.2.2. Large samples
4.2.3. Normal populations with unknown variances
4.2.4. Normal populations with unknown equal variances
4.2.5. Normal populations, paired observations.
4.3. Difference in proportions
4.3.1. Large samples
4.4. Ratio of the variances
4.4.1. Normal populations
5. Analysis of Variance
5.1. Introduction
5.2. One-way ANOVA
5.3. ANOVA table
5.4. Multiple comparisons
5.5. Two-way ANOVA.
6. Goodness of fit tests
6.1. Introduction
6.2. Chi-square tests
6.3. Kolmogorov-Smirnov test
6.4. Graphical tools