Applied Statistics

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Estimator Properties

Simulations to demonstrate the properties of sample estimators

Go to Estimator Properties

Central Limit Theorem

Simulations with different distributions of X to demonstrate the CLT

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Confidence Intervals for the Mean

Create confidence intervals for the population mean

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Hypothesis Test for the Mean

Perform hypothesis tests to evaluate the population mean

Go to Hypothesis Test for the Mean

Hypothesis Test for Variance

Perform hypothesis tests to evaluate the population variance

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Analysis of Variance

Perform ANOVA tests to evaluate significant differences between groups

Go to ANOVA

Test Power

Calculate statistical power for different types of tests and scenarios

Go to Test Power

Stratified Sampling

Analyze stratified sampling and compare with simple random sampling

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Cluster Sampling

Analyze cluster sampling and compare with simple random sampling

Go to Cluster Sampling

Linear Regression Model

Explore relationships between variables and fit linear regression models

Go to Linear Regression

Ordinary Least Squares

Ordinary Least Squares method for estimating coefficients

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Maximum Likelihood

Maximum Likelihood Estimation of parameters for the Normal Distribution

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Logistic Regression Model

Explore relationships between variables and fit logistic regression models

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Autoregressive Moving Average

Autoregressive Moving Average Models

Go to ARMA

AR(1) vs Random Walk Process

Analyze the coefficient distributions for each process

Go to AR(1) vs Random Walk

Spurious Regression

Analyze spurious relationships between non-stationary series

Go to Spurious Regression

Fixed Effects vs Random Effects Estimators

Comparison between Fixed Effects and Random Effects Estimators

Go to Fixed vs Random Effects