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Statistics Exam 2 Study Guide – Probability, Hypothesis Testing & Regression

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Prepare for success in Statistics Exam 2 with this comprehensive study guide covering probability, hypothesis testing, and regression analysis. Designed for students who want clear explanations, practical examples, and targeted review, this resource helps you master key concepts and build confidence before test day. Whether you’re revising class notes or tackling practice problems, you’ll find step‑by‑step guidance to make complex topics easier to understand. Perfect for exam prep, self‑study, or last‑minute review, this guide ensures you focus on the essential skills needed to excel in your statistics course.

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Statistics Exam 2 Study Guide – Probability,
Hypothesis Testing & Regression




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10

, Statistics Exam 2 Study Guide – Probability,
Hypothesis Testing & Regression
1. The Standard Normal Curve is defined by: u=0, o=1

2. Mathematically, every t-distribution is centered at zero, bell-shaped
with a degrees of freedom (df) curve, has fatter tails than a
value less than infinity Standard Normal Curve,
can be used to correct for potential
inaccuracy in a standard error statistic.

3. A college professor is interested in If the population mean for IQ on the old
the test
possibility that, on average, teenagers, to- among teenagers today is 100,
there was an
day, have a higher IQ (intelligence 11% probability of observing a mean IQ
quo- tient) than their parents had in the sample that falls 7 points or
at the same farther away from
age. To investigate this possibility, the
pro- 100. fessor plans to administer an
IQ test from 1988 to teenagers, one that
was likely
used when their parents were in their
ear- ly teens. When that old IQ test
was first ad- ministered 30 years ago,
it was designed so that the
population mean was "100".
Say that, after conducting this study
on a sample of N = 50 teenagers, the
professor observed a sample mean
for IQ of and, after applying a One-
Sample t-Test to the data, he obtains
a p-value of p = 0.11 = 11%. This p-
value can be interpreted to mean:

4. Total cholesterol is an example of a vari- it utilizes numerical values that
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