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#causality #statistics

Question

To identify a causal effect is to reduce a causal expression to a purely statistical expression. In this chapter, that means to reduce an expression from one that uses potential outcome notation to one that uses only statistical notation such as 𝑇 , 𝑋 , 𝑌 , expectations, and [...]. This means that we can calculate the causal effect from just the observational distribution 𝑃(𝑋, 𝑇, 𝑌)

Answer

conditioning

Tags

#causality #statistics

Question

To identify a causal effect is to reduce a causal expression to a purely statistical expression. In this chapter, that means to reduce an expression from one that uses potential outcome notation to one that uses only statistical notation such as 𝑇 , 𝑋 , 𝑌 , expectations, and [...]. This means that we can calculate the causal effect from just the observational distribution 𝑃(𝑋, 𝑇, 𝑌)

Answer

?

Tags

#causality #statistics

Question

To identify a causal effect is to reduce a causal expression to a purely statistical expression. In this chapter, that means to reduce an expression from one that uses potential outcome notation to one that uses only statistical notation such as 𝑇 , 𝑋 , 𝑌 , expectations, and [...]. This means that we can calculate the causal effect from just the observational distribution 𝑃(𝑋, 𝑇, 𝑌)

Answer

conditioning

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al expression. In this chapter, that means to reduce an expression from one that uses potential outcome notation to one that uses only statistical notation such as 𝑇 , 𝑋 , 𝑌 , expectations, and <span>conditioning. This means that we can calculate the causal effect from just the observational distribution 𝑃(𝑋, 𝑇, 𝑌) <span>

#### Original toplevel document (pdf)

owner: crocodile - (no access) - Introduction_to_Causal_Inference-Nov19_2020-Neal.pdf, p18

al expression. In this chapter, that means to reduce an expression from one that uses potential outcome notation to one that uses only statistical notation such as 𝑇 , 𝑋 , 𝑌 , expectations, and <span>conditioning. This means that we can calculate the causal effect from just the observational distribution 𝑃(𝑋, 𝑇, 𝑌) <span>

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

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