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Working with R-output (1)

The p-value given by the lm output is a two-sided p-value by default. In the twin study, it might seem more reasonable to follow along the one-sided scientific hypothesis that the IQ scores of the twins are positively associated. Because the p-value is the probability of the observed data or more extreme, the two-sided test p-value is twice as big as the one-sided result. That is, to get a one-sided p-value from the two-sided output in R, divide the p-value by two.

The linear regression model of Foster vs. Biological, model, is provided in the script.

This exercise is part of the course

Inference for Linear Regression in R

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Exercise instructions

  • Get the Biological coefficient from the model.
    • Tidy the model.
    • Filter for the term "Biological".
  • Add a column, one_sided_p_value, of the one-sided p-value.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

model <- lm(Foster ~ Biological, data = twins)

# Get the Biological model coefficient
biological_term <- model %>% 
  # Tidy the model
  ___ %>%
  # Filter for term equal to "Biological"
  ___ 

biological_term %>%
  # Add a column of one-sided p-values
  ___(one_sided_p_value = ___)
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