STT315—Lecl Final Exam (A) May 4, 2015
he exam is closed book and notes. Calculators and four formula sheets are permitted. Please bubble wur
answers to scantron carefully. (4OX2.5=100 points) '
perce
STT 315 Final practice problems
Part I:
1. In East Lansing 35% of the population votes for Democrats, 20% for Republicans and 45%
does not vote at all. In Lansing 26% of the population votes for Democ
Chapter 1
The following dataset is a sample of delivery times (in 25 days) for a particular make-to-order firm last year. A make-to-order firm is design to produce products according to customer speci
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ST'l'SIS—Leel Final Exam (B) Ma)“ 4 $015
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Lecture 7 Notes Part 1
Chapter 5. Completion of Coverage of Chapter 5 Material.
I will start by going over the textbooks example that runs from page 190 to page 193
concerning sample average
SUMMARY
S
Lecture 7 Part 2
Chapter 3. Random Variables and Probability Distributions on the Line.
Discrete Probability mass function. p(x)
Cumulative distribution function. F ( x ) P ( X x)
xp( x)
Expectation
Week 6 Notes Part 2
Sec 5-1. Discuss and motivate the use of data gathered in simple random samples for
inferences about the population from which the sample is drawn. The sample can tell us
about the
Graphical Summaries of
Quantitative Variables
1
Two types of summaries
Think about the percentage scores on an exam
In a class of 50 students, these will be 50 numbers
between 0 and 100.
To summari
Week 5 Notes Part 2
Exponential Distribution with Parameter > 0 (Sec 3-12). Here is the density function:
e x ,
x0
f (x)
0,
x<0
Graph the density function.
Important Results for Exponential( ):
= E
STT 315 Chapter 6 Notes
Chapter 6: Inferences Based on a Single Sample: Estimation with Confidence Intervals
Definition: The confidence coefficient is the probability that a randomly selected confiden
MyStatLab
We will use this program to assign and grade
homework, for computations (StatCrunch), and
for its various multimedia tools such as its Java
Applets.
Today, Mr. Chris Delaney from Pearson
P
Statistics for Business and
Economics
Chapter 4. Random Variables and
Probability Distributions
Today we cover topics from Secs 1, 2, 3
Topics
1. Two Types of Random Variables (minimal read
pp. 185-18
Example MC Problems
STT 315
These are just examples. The list is long yet it does not cover all the ideas that we cover in this course.
UNIT 1
CHAPTER 2
1 - 3. Suppose it is known that 40% of the peop
How to calculate P-value
Z-value
Right tail: normalcdf(lower, e99,0,1)
Left tail: normal cdf(-e99,upper, 0,1)
Two side: 2*normal cdf(abs(z),e99,0,1)
T-value
Right tail: tcdf(t,e99,n-1)
Left tail.: tcd
STT315
INTRO TO PROB & STAT FOR
BUSINESS
Instructor: Yuehua Cui
[email protected]
2-3
MyStatLab
We will use this program to assign and grade homework, for
computations (StatCrunch), and for its various
Week 4 Notes
Discuss discrete and continuous random variables and their distributions as probability
models. Outcomes are on the real number line, often the events of interest are intervals.
Discrete
Week 6 Notes Part 1
Finding percentiles of Normal Distributions (Chap 4, Sec 4-5).
TI-83. Use invNorm(.90, , ) and get 90th percentile of the Normal distribution N(, ).
Excel. Use = norminv(.90, , ) a
Week 2 Notes
Example 1. Rolling Two Balanced Dice. For purposes of enumerating outcomes, think
of one die as green in color and the other as red in color. We take S to consist of all
ordered pairs (i,
Week 5 Notes Part 1
Hypergeometric Distributions (Sec 3-8). The Hypergeometric probability distributions
arise when counting Successes when sampling n at random from a dichotomous, finite
population.
Week 4 Notes Part 2
Some Properties of Expectation and of Variance (Sec 3-3).
For constants a and b,
E (aX b) aE ( X ) b a b
(3-6)
V (aX b) a 2V ( X ) a 2 2
(3-10)
Example 1. Profit from Products Sold
Week 3 Notes
Section 2-7. BAYES CALCULATIONS. We start with an informal approach.
Example 1. (a) The prevalence of a disease is 5% in a population of 1,000 individuals. A
person is selected at random
WEEK 1
Go over Syllabus.
Go over Tentative Schedule.
Expected Coverage for Today. Ideas in Chapter 2, Sections 2-1 through 2-4.
Types of probability: objective and subjective
Probability models are us
Introduction to Experiments and
Observational Studies
1
Experiments and Observational
Studies
Lots of vocabulary: Observational study;
prospective study; retrospective study;
Experiment; random assig
Introduction to Sample Surveys
1
Sample Surveys
Want to learn something about a (often large)
group called the population.
We only can collect data on a subset of the
population, called the sample.
Sample Size and Simple Random
Samples
1
Sample Size
The sample size is the number of
individuals in a sample
The sample size depends on
Resources available for the survey
Desired level of confidence