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PPGA 503 Final Exam 2025 COMPREHENSIVE
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Terms in this set (63)
H0- There is no effect
What is a null hypothesis? HA- There IS an effect
What is an alternative
hypothesis? How do you "The evidence supports the HA, so we reject the
report it? null hypothesis"
"We reject H0 up to the 95% interval"
1. Refers to the probability that a condition or
circumstance would happen just by chance without
What is p-value
experimental intervention.
(probability values)?***
2. Standard of acceptability is 1 out of 20 or a p-
value od < or = 0.05****
You believe there's a relationship when there is
What is a type I error?
none, or a false positive.
When you don't believe there is a relationship, when
What is a type II error?
there is one, or a false negative.
To determine whether a sample is different from an
What is the two-sample t- expected value, we are assessing what's different
test used for? how do from each other.
you test this in stata?
ttesti var1 var2
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, 5/9/25, 4:28 PM PPGA 503 Final Exam 2025 COMPREHENSIVE EXAM QUESTIONS WITH DETAILED VERIFIED AND 100% CORRECT ANS…
Analysis of Variance determines whether more than
What is ANOVA? two unrelated groups are different from one
another by testing a difference in means.
What does a chi-squared Tests whether proportions in a sample are different
test do? from an expectation. Called a goodness of fit test.
It's a means of eliminating "noise" in a dataset so we
What is ordinary least can see the relationship between the variables. It
squares regression? How uses y=B0+B1 +u as the equation.
do you code it in Stata?
regress var1 var2
Seeks to describe the relationship between DV (y)
and IV (x). Uses a linear model to line the
Bivariate OLS Regression
observations to generalize the relationship between
x and y.
Using "r". We use r^2 to measure a line between 0
How do we measure and 1. The closer to 1, the more positive a
correlation? relationship (45-degree line). The closer to -1, the
more negative a relationship (45-degree line).
Conditions must hold!
Linear relationship between y and x.
Gauss-Markov
Random sample of data (to make inferences from)
Assumptions
No perfect co-linearity in explanatory variables x
Homoscadasticity: u has the same variance for all
values of x.
It means the error term is constant across all values
What is homoscadacity? of x. When we don't have this, we have
How do we test for this in heteroscadacity.
stata?
We use estat hettest
We do the exact same thing as bivariate regression,
and "regress" y on x1, x2, x3.
What is multiple
regression?
Keep in mind the effects are ON AVERAGE! these
things aren't uniform across all variables.
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