Description
The Data Science section on OpenCSE is currently marked "Coming Soon." This leaves students without access to the syllabus, notes, or practice resources. Adding the official syllabus along with supporting materials will make the section complete and immediately useful for students studying Statistics and Data Science fundamentals.
Suggested Changes
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Add topic-wise notes with clear explanations for each unit.
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Include necessary diagrams (data distribution curves, regression plots, confusion matrices, sampling illustrations).
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Provide quizzes for each unit (MCQs, short answers, problem-solving) to reinforce learning.
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Organize content by units:
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Unit I: Exploratory Data Analysis
Elements of Structured Data, Rectangular Data, Estimates of Location, Estimates of Variability, Exploring the Data Distribution, Exploring Binary and Categorical Data, Correlation, Exploring Two or More Variables
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Unit II: Data and Sampling Distributions
Random Sampling and Sample Bias, Selection Bias, Sampling Distribution of a Statistic, The Bootstrap, Confidence Intervals, Normal Distribution, Long-Tailed Distribution, Student's t-Distribution, Binomial Distribution, Chi-Square Distribution, F-Distribution
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Unit III: Statistical Experiments and Significance Testing
A/B Testing, Hypothesis Tests, Resampling, Statistical Significance and p-Values, Multiple Testing, Degrees of Freedom, ANOVA, Chi-Square Test, Multi-Arm Bandit Algorithm, Power and Sample Size
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Unit IV: Regression and Prediction
Simple Linear Regression, Multiple Linear Regression, Prediction Using Regression, Factor Variables in Regression, Interpreting the Regression Equation, Regression Diagnostics, Polynomial and Spline Regression
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Unit V: Classification
Naive Bayes, Discriminant Analysis, Logistic Regression, Evaluating Classification Models, Strategies for Imbalanced Data
Description
The Data Science section on OpenCSE is currently marked "Coming Soon." This leaves students without access to the syllabus, notes, or practice resources. Adding the official syllabus along with supporting materials will make the section complete and immediately useful for students studying Statistics and Data Science fundamentals.
Suggested Changes
Add topic-wise notes with clear explanations for each unit.
Include necessary diagrams (data distribution curves, regression plots, confusion matrices, sampling illustrations).
Provide quizzes for each unit (MCQs, short answers, problem-solving) to reinforce learning.
Organize content by units:
Unit I: Exploratory Data Analysis
Elements of Structured Data, Rectangular Data, Estimates of Location, Estimates of Variability, Exploring the Data Distribution, Exploring Binary and Categorical Data, Correlation, Exploring Two or More Variables
Unit II: Data and Sampling Distributions
Random Sampling and Sample Bias, Selection Bias, Sampling Distribution of a Statistic, The Bootstrap, Confidence Intervals, Normal Distribution, Long-Tailed Distribution, Student's t-Distribution, Binomial Distribution, Chi-Square Distribution, F-Distribution
Unit III: Statistical Experiments and Significance Testing
A/B Testing, Hypothesis Tests, Resampling, Statistical Significance and p-Values, Multiple Testing, Degrees of Freedom, ANOVA, Chi-Square Test, Multi-Arm Bandit Algorithm, Power and Sample Size
Unit IV: Regression and Prediction
Simple Linear Regression, Multiple Linear Regression, Prediction Using Regression, Factor Variables in Regression, Interpreting the Regression Equation, Regression Diagnostics, Polynomial and Spline Regression
Unit V: Classification
Naive Bayes, Discriminant Analysis, Logistic Regression, Evaluating Classification Models, Strategies for Imbalanced Data