**Text: ***Probability & Statistics for Engineers &
Scientists *by Walpole, Myers, Myers**, **and Ye 9th Ed.

**Prerequisite: **Grade of C or better in Math
181.

**Homework: **Homework will be assigned
for each section covered. The
homework will be worth 50 points.
No late homework will be accepted.

Assigned problems and due dates

**Exams: **There will be two exams
during the course of the semester.
Each will be worth 100 points. The exams will be on
10/3 and 11/7.

**Final Exam: ** The final exam will be
cumulative and worth 200 points. There will be no makeup final. You must take the exam
at the scheduled time. The final
exam is Tuesday December 11th from 8:00 to 10:00

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**Topics
Covered in
STAT 381**

__Chapter 1__

Histogram

Boxplot

Measures of Location

Sample
Mean

Median

Percentiles

Measures of Variation

Sample
standard
deviation

__Chapter 2__

Probability Rules

- 0 ≤ P(A) ≤ 1
- P(S) = 1
- P(A or B) = P(A) + P(B) – P(A and B)
- P(A
^{C }) = 1 – P(A)

Compute probability using combinations

Conditional probability

Multiplication Rule

Law of Total Probability

Bayes’ Theorem

__Chapter 3__

Discrete Random variables

Properties of a pdf

Properties of a cdf

Continuous Random variables

Properties of a pdf

Properties of a cdf

Two variables

Use
joint pdf

Marginal
pdf

Conditional
pdf

__Chapter 4__

Expectations, especially mean and variance

Mean and variance of linear combinations of
independent
variables.

__Chapter 5__

Binomial
and
Multinomial: pdf, mean, and variance

Hypergeometric: pdf, mean, and variance

Negative Binomial:
Know pdf

Poisson :
pdf, mean,
and variance, and effect of changing interval

__Chapter 6__

Normal Distribution

Given
X find
percentiles

Given
Percentiles,
find X

Normal approximation of the binomial

Exponential : Know pdf, mean, and variance

Weibull: pdf

Gamma: pdf, mean, variance

Time until kth event is Γ( k, 1/λ) for a
Poisson process
with parameter λ.

Mean
and variance of
linear combinations of independent variables.

Chi-Squared: mean, variance

__Chapter 8__

Sampling Distributions

Central Limit Theorem

Mean of

Standard deviation of

t-distributions

__Chapter 9__

Confidence interval for population mean,
sigma known

Finding n for fixed error

Confidence interval for difference of
population means,
sigma known

Confidence interval for population mean,
sigma unknown

Confidence interval for difference of
population means,
sigma unknown

Confidence interval for population variance

Confidence interval for proportions

Finding n for fixed error

Confidence interval for difference of
proportions

__Chapter 10__

Significance tests for population mean, sigma
known

Set
up hypotheses

One
sided vs two
sided tests.

Determine
if sample
results are significant at a given significance level.

Significance tests for proportions.

Set
up hypotheses

One
sided vs two
sided tests.

Determine
if sample
results are significant at a given significance level.