Python: Correlation and P-value Concepts

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  • เผยแพร่เมื่อ 5 ก.ย. 2024

ความคิดเห็น • 6

  • @neerajk3455
    @neerajk3455 2 ปีที่แล้ว +2

    @Mark Keith where is countinuation of univariate stats, automating?

  • @sheerwolff9484
    @sheerwolff9484 2 ปีที่แล้ว +3

    Tons of respect for creating this content, it's very helpful for a python newbie like myself.
    But, with all due respect, your explanation of p-value and how it should be interpreted is simply not true. A low p-value does not mean the results are reproductible and it does not reflect how the data we collected is represented in the population (around 15:30). p-value is the probability (under the null hypothesis ) to get a result as extreme as we obtained. this is why a high p-value cannot support a null hypothesis, it can only provide support to the expriment's hypothesis, h1.

    • @MarkKeith
      @MarkKeith  ปีที่แล้ว +1

      Thanks, my intention was that the the p-value represents (inversely) the likelihood that the results will be reproduced. Wouldn't that be interpreted the same as getting results "as extreme as we obtained"?

    • @practicemail3227
      @practicemail3227 ปีที่แล้ว +2

      @@MarkKeith both explanation are correct, to add up more, P-value can be interpreted as the measure of evidence against null hypothesis , provided by the data. Feel free to correct me, if any mistake.

  • @balajiwalebhkat
    @balajiwalebhkat 3 ปีที่แล้ว +2

    i m from india i need your notes for study how i get this?

    • @MarkKeith
      @MarkKeith  3 ปีที่แล้ว +1

      Sorry for how late I am. It's in my book and I've added the link the description