STT315
INTRO TO PROB & STAT FOR
BUSINESS
Instructor: Yuehua Cui
cui@stt.msu.edu
2-3
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.
On the 13t

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 specifications 32, 33, 39,
43, 44, 49, 49, 50, 51, 51, 54, 5

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
Sampling from a Population with Numerical Characteristic

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. E ( X )
p( y)
y x
called the mean of X or simply th

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 population with quantifiable precision.
A simple rando

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 confidence
interval encloses the population parameter that is,

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
Publishing will explain how you get registered into
the

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. 185-187)
2. Probability Distributions for Discrete
Random Var

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 Democrats, 29% for Republicans
and 45% does not vote at all.

Introduction to Experiments and
Observational Studies
1
Experiments and Observational
Studies
Lots of vocabulary: Observational study;
prospective study; retrospective study;
Experiment; random assignment; factors;
response variable; levels; treatment
gr

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 people who inquire about investment opportunities at a brok

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.: tcdf(-e99,t, n-1)
Two side: 2 *tcdf(abs(t), e99,n-1)
P-val

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 used to mathematically model situations where outcomes ar

I . I I 'I- {I} i If.) _ {
ST'l'SIS—Leel Final Exam (B) Ma)“ 4 $015
"I he exam is closed hook. and notes. lLittlculuttvrs and four formula Shut“ m
- c
answers to seatttron carefully. t40>< 1:14 |00 Points) pen-“med Heal“: bubble 3’0"?
1. Management at '
i

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) '
percent (46%) of students eat breakfa
class eats breakfast o

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 Probability mass function. Properties are
p(x) where p(

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, , ) and get 90th percentile of the Normal distribution N(, )

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, j) where i denotes the outcome for the Green die and j

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. Hypergeometric probability distributions have three par

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. Suppose that the number X of units of a product
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 from the population. What is the probability that the p

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(X) = 1/
2 = V(X) = 1/2,
= SD(X) = 1/.
There are some

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.
Wed like the sample to be representative of
the popula

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 in the results
The specific context of the survey
The

The answer is C,
do not reject H0
The answer is C,
do not reject H0
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question 47: