STA260
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- Bias of an Estimator
- Central Limit Theorem
- Chebyshev's Inequality
- Chi-squared Distribution
- Chi-squared Probability Calculations Example
- Chi-squared Quantiles (Table Lookup)
- Chi-squared from Sum of Squared Standard Normals
- Consistent Estimator
- Convergence in Probability
- Degrees of Freedom in Sample Variance
- Derivation of t-statistic for Sample Mean
- Expectation and Variance of Sample Mean
- F Distribution
- Functions of a Random Sample
- Gamma Function
- Gaussian Integral
- Independence of Sample Mean and Sample Variance
- Invariance Property of MLE
- Linear Combination of Independent Normal Variables
- Linear Combinations of Random Variables
- MLE for Poisson Parameter
- MOM Estimator for Gamma Parameters
- MOM Estimator for Normal Parameters
- Marginal Distribution of Sample Variance
- Maximum Likelihood Estimation (MLE) Principle
- Median
- Method of Moments Estimation Procedure
- Method of Moments Estimation
- Moment Generating Function
- Normal Distribution
- Proof - MGF of Sample Mean from Normal Population
- Proof of Sample Variance Distribution
- Quantile
- Relationship between Standard Normal and Chi-squared
- STA260 Lecture 01 Raw
- STA260 Lecture 01
- STA260 Lecture 02 Raw
- STA260 Lecture 02
- STA260 Lecture 03 Raw
- STA260 Lecture 03
- STA260 Lecture 04 Raw
- STA260 Lecture 04
- STA260 Lecture 05
- STA260 Lecture 06 Raw
- STA260 Lecture 06
- STA260 Lecture 07 Raw
- STA260 Lecture 07
- STA260 Lecture 08 Raw
- STA260 Lecture 08
- STA260 Lecture 09
- STA260 Lecture 10
- STA260 Makeup Lecture
- STA260 Post-Lecture 02
- STA260 Post-Lecture 03
- STA260 Post-Lecture 05
- STA260 Post-Lecture 08
- STA260 Practice 02
- STA260 Practice 03
- STA260 Pre-Lecture 01 Summary
- STA260 Quiz 1
- STA260 Quiz 2
- STA260 Term Test 1 Prep
- STA260 Tutorial 01
- STA260 Tutorial 02
- STA260 Tutorial 03
- STA260 Tutorial 04
- STA260
- Sample Mean and Sample Variance
- Sample Mean
- Sample Variance
- Sampling Distribution of Sample Mean (Normal Population)
- Sampling Distribution of the Sample Mean
- Sampling Distribution
- Standardizing a Normal Sample
- Study Mistake Log
- Sum of Squares Decomposition Identity
- Sum of Squares is Chi-squared
- T Distribution
- Unbiasedness of Sample Variance
- (MOC)