# Recent questions tagged assumption

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What do you do when the assumption of homoscedasticity is violated?
What do you do when the assumption of homoscedasticity is violated?What do you do when the assumption of homoscedasticity is violated? ...
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What is the process of developing a bayesian networks model?
What is the process of developing a bayesian networks model?What is the process of developing a bayesian networks model? ...
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Should a bayesian network be acyclic?
Should a bayesian network be acyclic?Should a bayesian network be acyclic? ...
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A function $f(x)$ is convex on $(a, b)$ if
A function $f(x)$ is convex on $(a, b)$ ifA function $f(x)$ is convex on $(a, b)$ if ...
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Prove Rolle's Theorem under the assumption that for the function $f$ on $[a, b]$ you have $f(x)>f(a)$ for some $x$ in the domain of $f$.
Prove Rolle's Theorem under the assumption that for the function $f$ on $[a, b]$ you have $f(x)>f(a)$ for some $x$ in the domain of $f$.Prove Rolle's Theorem under the assumption that for the function $f$ on $a, b$ you have $f(x)&gt;f(a)$ for some $x$ in the domain of $f$. ...
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Find the domain, the asymptotes (if any) of $f$ and classify each asymptote as vertical, horizontal or slant.
Find the domain, the asymptotes (if any) of $f$ and classify each asymptote as vertical, horizontal or slant.Let $$f(x)=\frac{x^{2}-3}{x+2}$$ You may use that  f^{\prime}(x)=\frac{x^{2}+4 x+3}{(x+2)^{2}} \quad \text { and } \quad f^{\prime \prime}(x)=\fra ...
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What is the positivist assumption?
What is the positivist assumption?What is the positivist assumption? ...
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How do I deal with alternating sequences?
How do I deal with alternating sequences?How do I deal with alternating sequences? ...
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The following data give the noise level (in decibels) generated by fourteen different chain saws powered in one of two different ways.
The following data give the noise level (in decibels) generated by fourteen different chain saws powered in one of two different ways. The following data give the noise level (in decibels) generated by fourteen different chain saws powered in one of two different ways. At the ...
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Causal AI - What is the relationship between faithfulness and the Markov assumption?
Causal AI - What is the relationship between faithfulness and the Markov assumption?Causal AI - What is the relationship between faithfulness and the Markov assumption? ...
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How is Facebook using Bayesian Optimization with BoTorch?
How is Facebook using Bayesian Optimization with BoTorch? How is Facebook using Bayesian Optimization with BoTorch? ...
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What is interventional Markov equivalence?
What is interventional Markov equivalence?What is &nbsp;interventional Markov equivalence? ...
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Is the MTS assumption, by definition a contradiction to exchangeability (ignorability)?
Is the MTS assumption, by definition a contradiction to exchangeability (ignorability)?Is &nbsp;the MTS assumption, by definition a contradiction to exchangeability (ignorability)? ...
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Is modularity assumption an advanced version of causal edges assumption?
Is modularity assumption an advanced version of causal edges assumption?Is modularity assumption an advanced version of causal edges assumption? ...
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How do causal models deal with feedback systems, which have loops in a graph?
How do causal models deal with feedback systems, which have loops in a graph?How do causal models deal with feedback systems, which have loops in a graph? ...
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Can the Local Markov Assumption (LMA) induce dependences?
Can the Local Markov Assumption (LMA) induce dependences?Can the Local Markov Assumption (LMA) induce dependences? ...
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Does the consistency assumption always hold if we treat the potential outcome for each individual $Y_i(t)$ as a random variable, instead of a constant?
Does the consistency assumption always hold if we treat the potential outcome for each individual $Y_i(t)$ as a random variable, instead of a constant?Does &nbsp;the consistency assumption always hold if we treat the potential outcome for each individual $Y_i(t)$ as a random variable, instead of a co ...
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In Linear Sensitivity Analysis, what assumption is violated when the data are generated by a noiseless process?
In Linear Sensitivity Analysis, what assumption is violated when the data are generated by a noiseless process?In &nbsp;Linear Sensitivity Analysis, what assumption is violated when the data are generated by a noiseless process? ...
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What are the two fundamental ideas in sensitivity analysis for causal inference?
What are the two fundamental ideas in sensitivity analysis for causal inference?What are the two fundamental ideas in sensitivity analysis for causal inference? ...
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Why should sensitivity analysis be performed when doing causal inference?
Why should sensitivity analysis be performed when doing causal inference?Why should sensitivity analysis be performed when doing causal inference? ...
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What are some of the strategies for reducing causal model sensitivity?
What are some of the strategies for reducing causal model sensitivity?What are some of the strategies for reducing causal model sensitivity? ...
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What is the goal of causal inference?
What is the goal of causal inference?What is the goal of causal inference? ...
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What are the rules of d-separation in a causal DAG?
What are the rules of d-separation in a causal DAG?What are the rules of d-separation in a causal DAG? ...
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Why Is Causal Inference Necessary?
Why Is Causal Inference Necessary?Why Is Causal Inference Necessary? ...
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How does one use difference in difference method for causal inference?
How does one use difference in difference method for causal inference?How does one use difference in difference method for causal inference? ...
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When are graphs markov equivalent?
When are graphs markov equivalent?When are graphs markov equivalent? ...
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What is the faithfulness assumption in causal modelling?
What is the faithfulness assumption in causal modelling?What is the faithfulness assumption in causal modelling? ...
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Are causal models falsifiable?
Are causal models falsifiable?Are causal models falsifiable? ...
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Under what circumstances are two causal models probabilistically/interventionally equivalent?
Under what circumstances are two causal models probabilistically/interventionally equivalent?Under what circumstances are two causal models probabilistically/interventionally equivalent? ...
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What does it mean to say, "causal models offer a stability guarantee"?
What does it mean to say, "causal models offer a stability guarantee"?What does it mean to say, &quot;causal models offer a stability guarantee&quot;? ...
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What are the two types of data for causal inference?
What are the two types of data for causal inference?What are the two types of data for causal inference? ...
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What are the two types of causal questions?
What are the two types of causal questions?What are the two types of causal questions? ...
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How do causal models deal with feedback systems, which have loops in a graph? In that case, the DAG assumption will no longer be valid?”
How do causal models deal with feedback systems, which have loops in a graph? In that case, the DAG assumption will no longer be valid?”How do causal models deal with feedback systems, which have loops in a graph? In that case, the DAG assumption will no longer be valid?” ...
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Why is removing edges in a Bayesian Network equivalent to adding independencies?
Why is removing edges in a Bayesian Network equivalent to adding independencies?Why is removing edges in a Bayesian Network equivalent to adding independencies? ...
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What would it mean if the modularity assumption is violated in a causal model?
What would it mean if the modularity assumption is violated in a causal model?What would it mean if the modularity assumption is violated in a causal model? ...
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What is the modularity assumption in causal inference using DAGs?
What is the modularity assumption in causal inference using DAGs?What is the modularity assumption in causal inference using DAGs? ...
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How is the local Markov assumption equivalent to the global Markov assumption in causal inference?
How is the local Markov assumption equivalent to the global Markov assumption in causal inference?How is the local Markov assumption equivalent to the global Markov assumption in causal inference? ...
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What is the Causal Edges assumption?
What is the Causal Edges assumption?What is the Causal Edges assumption? ...
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What are the two parts of the minimality assumption in Bayesian networks?
What are the two parts of the minimality assumption in Bayesian networks?What are the two parts of the minimality assumption in Bayesian networks? ...
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How is the local Markov assumption related to Bayesian network factorization?
How is the local Markov assumption related to Bayesian network factorization?How is the local Markov assumption related to Bayesian network factorization? ...
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What is the local Markov assumption in a Bayesian Network?
What is the local Markov assumption in a Bayesian Network?What is the local Markov assumption in a Bayesian Network? ...
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What is the minimality assumption when dealing with DAGs in Bayesian Networks?
What is the minimality assumption when dealing with DAGs in Bayesian Networks?What is the minimality assumption when dealing with DAGs in Bayesian Networks? ...
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What does the assumption of unconfoundedness in treatment effect state?