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Flashcards

Simple linear regression

Marie Skalshøi Statistical and Geospatial Modelling European species English 13 cards

Simple linear regression

Cards in this deck (13)

  1. 1What can a “simple linear regression” be used for?- Examining how strong the relationship is between one response variable and one predictor variable
    - Estimating the value of the response variable at a certain value of the predictor variable (e.g., the amount of soil erosion at a certain level of rainfall) within the range of our dataset!.
  2. 2When do we use a “simple linear regression”?When these assumptions are met:
    - Homogeneity of variance (homoscedasticity)
    - Independence of observations:
    - Normality:
    - The relationship between the independent and dependent variable is linear
    - Continues data / numeric data
  3. 3What is ” Homoscedasticity”?Homoscedasticity: The variance of the response variable does not change with the value of the predictor variable.
  4. 4What is “Independence of observations”?Independence of observations: Each observation is independent of the others - the value of observation x is not affecting/being affected by the value of observation y.
  5. 5What is ”Normal distribution”?Normality: “The response variable or the residuals of the model are normally distributed”
  6. 6What is “linear relationship”?Linear relationship: “That there is a linear relationship between the predictor and response variable i.e. follow a straight line”
  7. 7How can we check for the assumptions of a simple linear model in R?Plot(lm)
  8. 8How can we create a simple linear model in R?lm(response variable ~ predictor variable, data = Dataset)
  9. 9Show me an example of the output from plot(lm)? Explain what you are looking for?USE WEBPAGE FROM MICHAEL
  10. 10What is a “simple linear model”?What is a “simple linear model”?
  11. 11How do we interpretate the results from a simple linear model in R?Summary(lm_model)
  12. 12Show me an example of the output from summary(lm_model) and explain the interpretation:- P-value < 0.05
    - Coefficient —> (intercept) = estimate for response variable
    - USE Equitable equations or so from Youtube
    Show me an example of the output from summary(lm_model) and explain the interpretation:
  13. 13What is “residual”?Residual: “The difference between the actual value and the value predicted by the model for any given point”

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European species Statistical and Geospatial Modelling (Regression Analysis) Flashcards on Simple linear regression, created by Marie Skalshøi on 13/03/2025.
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Marie Skalshøi
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