Multiple regression: how to select variables for your model

Поделиться
HTML-код
  • Опубликовано: 15 фев 2024
  • When doing linear regression, it is important to include right right variables in your model. Multiple regression differs from simple linear regression in that more than one explanatory variable is used in the model. Master variable selection in multiple regression with our concise guide! Dive into the art and science of choosing the right predictors for your statistical models. This video is perfect for data science enthusiasts, statisticians, and researchers looking to enhance their model's accuracy and efficiency. Learn about key concepts such as multicollinearity, Adjusted R-squared, stepwise regression, forward selection, and backward elimination. In this video you'll learn about using R programming for your regression analysis. R is a powerful tool when it comes to statistical analysis. Whether you're working on predictive analytics, machine learning projects, or academic research, our expert insights will help you make informed decisions on which variables to include in your multiple regression model. Boost your data analysis skills today and ensure your models are both powerful and precise!
  • РазвлеченияРазвлечения

Комментарии • 8

  • @otek7472
    @otek7472 5 месяцев назад +1

    Never stop uploading please! Love your videos. You explain everything really well!

  • @alessandroe.d.pozzobon6620
    @alessandroe.d.pozzobon6620 5 месяцев назад +1

    A video on nonlinear regression would be interesting.

    • @metameles5846
      @metameles5846 5 месяцев назад

      As would one on multinomial and ordinal regression :)

  • @clbgrmn
    @clbgrmn 4 месяца назад

    Hi thanks for the video! Would you expect that going forward vs backwards would always produce the same model? I assume the answer is no (otherwise they wouldn't both need to exist), and it seems like you started to explain it a bit at the end, but I'm not sure I understand the difference.
    Further, it seems like if a linear model is the right model, and the fwd/bwd options exist, you would always want to create your lm's in this way since it will produce the most explanatory model. Is that a reasonable conclusion? Thanks in advance!

  • @maimonaalkhrfan3654
    @maimonaalkhrfan3654 Месяц назад

    it is not working for me please someone help because of this %>%

    • @johnbennett8461
      @johnbennett8461 Месяц назад

      you need to install the tidyverse package.

  • @umagenetics3975
    @umagenetics3975 2 месяца назад

    Please don Forward steowise regression

  • @hypercrack7440
    @hypercrack7440 Месяц назад +1

    Hey Greg, love your video but PLEASE STOP THE SCRATCHING NOISES everytime you try to underline or point out something it nags me, idk if anyone's noticed but as a headphones users it feels like scratching with your nails on a chalkboard. Thank you.