Parameter Estimation

In statistics, statistical inference refers to drawing conclusion based on the data. Statistical inferences are drawn in two broad ways, namely, hypothesis testing, and parameter estimation.

In hypothesis testing, we make a hypothesis and then we determine whether the sample data supports the hypothesis or does not support it. The hypothesis could be something like - Population mean is equal to 10. Then based on our sample data, we either accept or reject the hypothesis.

In contrast with hypothesis testing, under parameter estimation we try to estimate the population parameter by making use of the information available in the sample.

There are two types of parameter estimators: point estimates and confidence interval estimates.

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Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

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