==== Lectures and Tutorials ===== ==== Lectures ===== ^ L ^ Date^ Lecturer ^ Contents ^ Materials ^ | 1 | 22.9. | JK | Introduction, course map, requirements. Linear regression (continuous dependent variable, simple linear regression, p-values). | {{ :courses:b4m36san:san_intro_noskulls.pdf |SAN_intro}}, {{:courses:b4m36san:san_regression_2025.pdf|SAN_regression}}, [[https://www.youtube.com/watch?v=5Rdunc-q_1M&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=1|SAN_lecture_1_czech]], [[https://www.youtube.com/watch?v=-WFm4bHwLRg&list=PLQL6z4JeTTQmB0wG1B-nA9LjoRR0Q8ChW&index=1|SAN_lecture_1_english]] | | 2 | 29.9. | JK | Multivariate regression (overfitting, model shrinkage). | see the previous slides, [[https://www.youtube.com/watch?v=42ajwFkiLdk&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=2|SAN_lecture_2_czech]], [[https://www.youtube.com/watch?v=Mndml3EYJqo&list=PLQL6z4JeTTQmB0wG1B-nA9LjoRR0Q8ChW&index=2|SAN_lecture_2_english]] | | 3 | 6.10. | JK | Nonlinear regression (polynomial regression, splines, local regression). | {{:courses:b4m36san:san_nonlin_regression.pdf|SAN_nlin_regression}}, [[https://www.youtube.com/watch?v=341CcJQgRQg&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=1|SAN_lecture_3_czech]], [[https://www.youtube.com/watch?v=Z4mFeVQ54as&list=PLQL6z4JeTTQmB0wG1B-nA9LjoRR0Q8ChW&index=3|SAN_lecture_3_english]] | | 4 | 13.10. | JK | Nonlinear regression (polynomial regression, splines, local regression). | see the previous slides, [[https://www.youtube.com/watch?v=-ular-AJPVk&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=2|SAN_lecture_4_czech]],[[https://www.youtube.com/watch?v=gU4h5NwydxQ&list=PLQL6z4JeTTQmB0wG1B-nA9LjoRR0Q8ChW&index=4|SAN_lecture_4_english]] | | 5 | 20.10. | JK | Discriminant analysis (categorical dependent variable, LDA, logistic regression). | {{ :courses:b4m36san:san_discriminant_short.pdf |SAN_discriminant}}, [[https://www.youtube.com/watch?v=t3vLwS13l2Q&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=1|SAN_lecture_5]] | | 6 | 27.10. | JK | Generalized linear models (GLMs). | {{ :courses:b4m36san:san_glms.pdf|SAN_GLMs}}, [[https://www.youtube.com/watch?v=iOJE7GEAHXs&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=6 |SAN_lecture_7]] | | 7 | 3.11. | JK | Dimension reduction (PCA and kernel PCA). | {{:courses:b4m36san:dimred_wsom.pdf|SAN_dimred}}, [[https://www.youtube.com/watch?v=h1j8yCEMZ7A&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=1|SAN_lecture_8]] | | 8 | 10.11. | JK | Dimension reduction (other non-linear methods). | see the previous slides, [[https://www.youtube.com/watch?v=Zq39LzmaC48&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=8|SAN_lecture_9]] | | 9 | 17.11. | -- | National holiday | no class | | 10 | 24.11. | TP | Robust statistics. | {{ :courses:b4m36san:notes_robust.pdf | lecture notes, }}{{ :courses:b4m36san:robust.pdf |slides}}, [[https://www.youtube.com/watch?v=AfSAvFIAyC4&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=1|SAN_lecture_10]] | | 11 | 1.12. | TP | Anomaly detection. | {{ :courses:b4m36san:presentation_11.pdf|SAN_anomaly}}, [[https://www.youtube.com/watch?v=LbnfUscC4sQ&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=10|SAN_lecture_11]] | | 12 | 8.12. | ZM | Empirical studies, their design and evaluation. Power analysis. | {{ :courses:b4m36san:san_lecture12_studies_and_power_analysis-v08.pdf|SAN_emp_studies_power_analysis}}, [[https://www.youtube.com/watch?v=HLc4naDD9rc&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=1|SAN_lecture_12]] | | 13 | 15.12. | JK | Clustering (formalism, k-means, EM GMM, hierarchical). | {{ :courses:b4m36san:san_clustering.pdf |SAN_clustering}}, [[https://www.youtube.com/watch?v=mhEGkqzGRVs&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=1|SAN_lecture_13]] | | 14 | 5.1. | JK | Clustering (spectral clustering). | {{:courses:b4m36san:san_clustering_pokr.pdf|SAN_spect_clustering}}, [[https://www.youtube.com/watch?v=GOD8Q9k0alY&list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g&index=13|SAN_lecture_14]] | ==== Tutorials ===== ^ T ^ Date ^ Teacher ^ Contents ^ Materials ^ | 1 | 22.9. | JB, AA, JK | Statistical testing, t-test, significance, power of the test. | {{ :courses:b4m36san:san_intro.zip | san_intro.zip}}, {{ :courses:b4m36san:r_setup.zip | r_setup.zip}}, {{ :courses:b4m36san:pres-1.pdf | pres-1.pdf}} | | 2 | 29.9. | JB, AA, JK | Simple linear regression. | {{ :courses:b4m36san:san_lreg.zip | san_lreg.zip}}, {{ {{ :courses:b4m36san:r_cheat_sheet.pdf |R cheat sheet}}, {{ :courses:b4m36san:pres_2.pdf | pres_2.pdf}} | | 3 | 6.10. | JB, AA, JK | Shrinked linear regression | {{ :courses:b4m36san:san_fs.zip |}}, {{ :courses:b4m36san:assignment1.zip |}}, {{ :courses:b4m36san:pres_3.pdf | pres_3.pdf}} | | 4 | 13.10. | JB, AA, JK | Non-linear regression | {{ :courses:b4m36san:san_nonlinear.zip |}}, {{ :courses:b4m36san:pres_4.pdf | pres_4.pdf}} | | 5 | 20.10. | JB, AA, JK | Discriminant analysis | {{ :courses:b4m36san:san_lda.zip |}}, {{ :courses:b4m36san:assignment2.zip |}}, {{ :courses:b4m36san:elhabian_lda09.pdf | reading for assignment 2}}, {{ :courses:b4m36san:pres_5.pdf | pres_5.pdf}} | | 6 | 27.10. | JB, AA, JK | Generalized linear models | {{ :courses:b4m36san:san_glms.zip |}}, {{ :courses:b4m36san:assignment3.zip |}}, {{ :courses:b4m36san:pres_7.pdf | pres_7.pdf}} | | 7 | 3.11. | JB, AA, JK | Mid-term test, the final assignment | [[courses:b4m36san:new_final_assignment|Final Assignment]] | | 8 | 10.11. | JB, AA, JK | Dimension reduction | {{:courses:b4m36san:san_dimred.zip | san_dimred.zip}}, {{ :courses:b4m36san:assignment4.zip |}}, {{ :courses:b4m36san:pres_8.pdf | pres_8.pdf}}, {{ :courses:b4m36san:assig4_R_problem.pdf | assig4_R_problem.pdf}} | | 9 | 17.11. | -- | National holiday, dean's day | no class | | 10 | 24.11. | TP | Robust statistics | {{ :courses:b4m36san:instruction.pdf |}} | | 11 | 1.12. | TP | Anomaly detection – assignment | {{ :courses:b4m36san:anomaly2.pdf |}} {{ :courses:b4m36san:anomaly-problems.zip |}}{{ :courses:b4m36san:anomalylab.jl|Notebook in Pluto}}[[https://github.com/fonsp/Pluto.jl|Link to Pluto]] | | 12 | 8.12. | ZM | Empirical study design, power analysis | {{:courses:b4m36san:san_practice_hci_experiment_evaluation_and_power_analysis-v06.pdf | empirical_study,}} {{courses:b4m36san:san2023_hci_experiment_measured_values.xlsx | experiment_data_FINAL}} | | 13 | 15.12. | JB, AA, JK | Clustering | {{ :courses:b4m36san:san_clustering.zip |san_clustering.zip}}, {{ :courses:b4m36san:pres_13.pdf | pres_13.pdf}}, {{ :courses:b4m36san:pres_13.odp | pres_13.odp}} | | 14 | 5.1. | JB, AA, JK | The final assignment -- team presentations | | ==== Lecture recordings ===== [[https://www.youtube.com/playlist?list=PLQL6z4JeTTQkJVspx1BsWKeTEzGNyVE0g | Playlist from 2024 (Czech)]] [[https://www.youtube.com/playlist?list=PLQL6z4JeTTQmB0wG1B-nA9LjoRR0Q8ChW | Playlist from 2025 (English)]] ==== Extra Resources for the Curious ===== If you are interested and want to learn more, here are some extra resources beyond this course you can look at: - Wasserstein, Ronald L., and Nicole A. Lazar. "The ASA statement on p-values: context, process, and purpose." The American Statistician 70.2 (2016): 129-133. DOI: [[https://doi.org/10.1080/00031305.2016.1154108|10.1080/00031305.2016.1154108]] If you have a suggestion on what to add, please let us know. :)