403/650/890留学生代做、代做PYTHON/Java语言、代写Trumps Analysis

日期：2019-01-16 10:13

Stat 403/650/890: Reading Assignment 1 – Causality or Significance Testing

For this reading assignment, read ONE of the articles and answer ONE set of questions.

(You can do both, but only one will be marked)

Reading Assignment – Causality

To answer the following questions, read the sections 1, 2, and 3 of the article "For

Objective Causal Inference, Design Trumps Analysis", by Donald Rubin.

A1) Randomized experiments make causal inference valid because we know the

'scores' "are known from the design of the experiment". What are these 'scores'?

(Name only)

A2) Rubin is stating that randomized experiments are 'the gold standard' for causal

inference. Does that mean causality can be inferred from all randomized experiments,

or are some "poorly suited"? If so, give an example.

A3) What are the two design steps that are "absolutely essential" for objective

inferences?

A4) In Section 2.1, how is a treatment defined?

A5) What are covariates, "in contrast to" outcome/response variables?

A6) What is "self optimizing" behaviour happens when treatments are not assigned

randomly by the experimenter?

A7) In designing observational studies to approximate experiments (Section 3), what

step is often skipped? Is this okay?

Reading Assignment - Significance Testing

To answer the following questions, read the article "The insignificance of

Significance Testing", a commentary by Neville Nicholls.

B1) Give an example of a data set that could have physical significance, but not

statistical significance.

B2) Cohen mentions some probability when talking about an n=50 sample from a

population with population correlation of ρ = 0.30. What is the name for this

probability?

(The name isn’t in the paper, it IS in our notes on hypothesis testing)

B3) The 1979-95 data used to calculate climate trends has no uncertainty from

sampling, How is this possible?

B4) What deviations from a well-behaved distribution could affect the correlation

between SOI and snowfall?

B5) What are three alternatives to null hypothesis testing?

B6) What is another term for the “repeated investigations” issue? That is, when a

so-called insignificant result is left unpublished until someone repeats it and finds

significance simply by chance? (Again, the term is in our notes, think Tukey)

B7) A permutation test produces a value that works very similarly to a p-value.

However, a permutation test has one major advantage over a classic hypothesis test

(and confidence intervals). What is it? (Hint: Spearman correlation and the median have

this same advantage).