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FAQ:
Q: What is the difference between statistical inference and statistical model?
A: Recall, a statistical inference aims at learning characteristics of the population from a sample; the population characteristics are parameters and sample characteristics are statistics. A statistical model is a representation of a complex phenomena that generated the data.
Q: What is estimation in statistics?
A: An approximately true picture can be formed if the sample estimations satisfy some important property such as unbiasedness consistency, sufficiency, efficiency & so on. So, a more general concept of estimation would be to find out an interval based on sample values which is expected to include the unknown parameter with a specified probability.
Q: What is estestimation in statistics?
A: Estimation represents ways or a process of learning and determining the population parameter based on the model fitted to the data. Point estimation and interval estimation, and hypothesis testing are three main ways of learning about the population parameter from the sample statistic.
Q: What is the difference between point estimation and interval estimation?
A: Point estimation = a single value that estimates the parameter. Point estimates are single values calculated from the sample Confidence Intervals = gives a range of values for the parameter Interval estimates are intervals within which the parameter is expected to fall, with a certain degree of confidence.