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Thread: Statistical inference.

  1. #1
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    Statistical inference.

    Hi there,

    I would like to ask a couple of basic questions:

    1. What is the difference between estimation and hypothesis testing? I mean are they two options for inference? or estimation of the parameters comes first and then we apply the hypothesis testing?

    2. How can I determine what is the most suitable statistical model for my dataset?

    Please help me with these issues
    Thank you in advance.

  2. #2
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    Re: Statistical inference.


    (1): The usual (frequentist) way is: You have a hypothesis, and you express this hypothesis in terms of a model. Let's say your hypothesis is that a plant grows if you give the plant more nutrients. Your model could be plant_length ~ alpha*amount_nutrients. In a second step, you fit this model to data, i.e. you estimate your parameters. And depending on the estimated value of alpha (and it's p-value) it is either likely or unlikely that your hypothesis is true

    (2): You can compare differnt models (e.g. with different set of predictors) e.g. via the AIC-value

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