How to develop self-confidence in students pdf
How to be confident in school presentation
Activities to build confidence in students!
4.1 Statistical Inference and Confidence Intervals
Learning Outcomes
By the end of this section, you should be able to:
- 4.1.1Estimate parameters, create confidence intervals, and calculate sample size requirements.
- 4.1.2Apply bootstrapping methods for parameter estimation.
- 4.1.3Use Python to calculate confidence intervals and conduct hypothesis tests.
Data scientists interested in inferring the value of a population truth or parameter such as a population mean or a population proportion turn to inferential statistics.
A data scientist is often interested in making generalizations about a population based on the characteristics derived from a sample; inferential statistics allows a data scientist to draw conclusions about a population based on sample data.
In addition, inferential statistics is used by data scientists to assess model performance and compare different algorithms in machine learning application. Inferential statistics provides methods for generating predictive forecasting models, and this allows data scientists to generate predictions and trends to assi