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Using R for Introductory Statistics 2nd Edition By John Verzani 9781466590731 ALL Chapters
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Solutions Manual For Using R for Introductory Statistics 2ndEdition By John Verzani 9781466590731 ALL Chapters .
What is inferential statistics? - ANSWER: sample > measure values > make inference about whole
population
What is causal inference? - ANSWER: prediction of intervention, missing data imputation
In causality, what are all paths that start with an arrow pointing to the independent variable and end
with an arrow pointing to the dependent variable (to be controlled) called? - ANSWER: back-door
paths
How can I block back-door paths? - ANSWER: include 3rd variables in regression models, matching
based on confounding variables
Example: We want to investigate how personality (agreeableness) of a manager is related to his/her
employee well-being. -> we are expecting a positive relationship. What would be H0? - ANSWER: The
agreeableness of a manager does not affect his/her employees wellbeing (experiment)
H1 represents... - ANSWER: what you want to observe
You either __ / __ your hypothesis, but you do not proof it __ - ANSWER: confirm / disconfirm; true /
false
The manipulated variable is the___ - ANSWER: independent one
What is probability? - ANSWER: o 1. view: long term frequencies, probability of the same event
happening many times
o 2. view: personal belief = Bayesian statistics, subjective Probability/personal belief
Axioms of Probability - ANSWER: a set of rules that probabilities defined on a sample space must
follow
Die cumulative discribution function does what compared to the probability mass function? -
ANSWER: Go up
We cannot compute the probability of each number up to x either because there are just too many
numbers in between. Solution - ANSWER: using integral to create a probability density function.
4: We showed the results to our supervisor and the supervisor advised that we add gender as another
predictor. We did so but results showed that our explained variance in dependent variable (R2) did
not change. Based on this, which of the following is correct? - ANSWER: Adding gender does not
improve our model fit.
Law of large numbers - ANSWER: increased sample size > mean gets closer to expected mean
Central Limit Theorem (CLT) - ANSWER: with the addition of new random variables a normal
distribution is created
What is the aim of the Exploratory Factor Analysis (EFA) - ANSWER: reproduce the observed
relationships among a group of indicators with a smaller set of latent variables.
The higher the common variance, the ___ the possibility that your factors belong together as they
highly correlate with each other - ANSWER: higher
What do I do it the commonality of an item is low? - ANSWER: reconsider / change
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