Data Science

Data Science is a branch of formal science that encompasses the entirety of techniques for collecting, processing, storing, analyzing, and presenting data. This category covers basic statistics and visualization at an introductory level for first and second-year undergraduates.

Introduction to Statistics

• Definition of Statistics
• Parameters and Statistics
  • 🔒(24/07/05) What are Hyperparameters?
• Degrees of Freedom in Statistics

Data

• Definition and Etymology of Data
  • Scales of Measurement for Data
  • What is Dimensionality Reduction?
• Qualitative and Quantitative Variables
  • Frequency of Qualitative Data
  • Class Intervals of Quantitative Data
• Independent and Dependent Variables
  • Design Matrix $X$

Measures of Central Tendency and Variability

• Mean $\overline{x}$
• Median $m$
• Mode
• Variance $s^{2}$
• Z-Score and Standardization
• 🔒(24/07/21) Normalization
• Percentiles and Outliers

Evaluation

• 🔒(24/03/19) Definition of Classification and Regression Problems
• Cross-Validation
• Fitted Values, Predicted Values, Residuals, and Errors

Classification Problems

• Confusion Matrix, Sensitivity, and Specificity
  • 🔒(24/03/25) Situations Where Accuracy is Overestimated
• ROC Curve
  • Finding the Optimal Cutoff Using ROC Curve
  • Comparing Models Using AUC of ROC Curve
• 🔒(24/04/06) $F_{1}$ Score
  • 🔒(24/04/06) Precision
  • 🔒(24/04/06) Recall

Visualization

• Bar Graphs for Qualitative Data
• Histograms for Quantitative Data
• Line Graphs for Time-Series Data
• Scatter Plots for Multivariate Data
• What is a Heatmap?
• What is a Dendrogram?
• What is a Box Plot?

Excel

• How to Draw a Histogram
• How to Create a Map-Like Visualization

References

• Mendenhall. (2012). Introduction to Probability and Statistics (13th Edition)
• 경북대학교 통계학과. (2008). 엑셀을 이용한 통계학