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Statistics
Linear Models
1. Introduction to Linear Relationships
2. Simple Linear Regression
3. Inference in Simple Linear Regression
4. Multiple Linear Regression
5. Model Diagnostics and Assumption Checking
6. Model Building and Variable Selection
7. Extensions and Advanced Topics
Inference in Simple Linear Regression
Properties of OLS Estimators
Unbiasedness
Definition of Unbiasedness
Conditions for Unbiasedness
Variance of Estimators
Formula for Variance of Slope
Formula for Variance of Intercept
Factors Affecting Variance
Gauss-Markov Theorem
Statement of the Theorem
Best Linear Unbiased Estimators
Hypothesis Testing for Coefficients
Null and Alternative Hypotheses
Formulating Hypotheses for Slope
Formulating Hypotheses for Intercept
One-sided vs. Two-sided Tests
The t-statistic
Formula for t-statistic
Degrees of Freedom
t-distribution Properties
p-values and Statistical Significance
Definition of p-value
Interpreting p-values
Significance Levels
Confidence Intervals
Confidence Interval for the Slope
Formula for Confidence Interval
Interpretation
Confidence Interval for the Intercept
Formula for Confidence Interval
Interpretation
Prediction and Prediction Intervals
Point Prediction for New Observations
Confidence Interval for Mean Response
Calculation and Interpretation
Prediction Interval for Individual Response
Calculation and Interpretation
Distinguishing Between Confidence and Prediction Intervals
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2. Simple Linear Regression
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4. Multiple Linear Regression