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