STAT 3090
Test 1 - Version A
Fall 2014
Students Printed Name: _
XID:_
Instructor: _
Section # :_
Read each question very carefully. You are permitted to use a calculator on all portions of this
exam. You are NOT allowed to use any textbook, notes, cellpho
(tnal
l.
Exorrri Sr vi er",
KuJ
Consider the following data:
x
p(x)
Step 1. Find the expected value E( X
/,t, F( )- Z x rcfw_f *
).
3
4 5 6 7
0.1 0.1 0.2 0.3 0.3
Round your answer to one decimal place.
2;cfw_0,t)-h
4i*.1t*c'il,2*bi 4.",g" :r'*"vi
Step 2.
haelli3090SonnnerH-2014
Exam 2
Name: at Y F _,._
MULTIPLE CI IDICE. Choose the one alternative that best completes the statement or answers the
question. Solve the problem. Place answer in provided space for given problem. Each MC problem is 3
pt
5.
D_1
STAT 3090
Test 1 - Version A
Fall 2014
Students Printed Name: _ANSWER KEY_
XID:_
Instructor: _
Section # :_
Read each question very carefully. You are permitted to use a calculator on all portions of this
exam. You are NOT allowed to use any textbook, not
Simple Linear Regression
The following data represent the total compensation for 10 randomly selected chief executive
officers (CEOs) and the companys stock performance in 2011. For the following analysis use
compensation as the explanatory (predictor) va
Appendix A
D
Table D
Critical Values of t
Numerical entries represent the value of t such that the area to the right of the t is equal to .
Area to the Right of the Critical Value
Degrees
of
Freedom
t0.200
t0.100
t0.050
t0.025
t0.010
t0.005
1
1.376
3.078
STAT 3090 Formula Sheet 3 HAWKES
Confidence Intervals:
( )
s
For () - x t
2 n
For (p) - p z
Sample Size:
n=
( )
z
2
2
2
(E)
2
Hypothesis Test about mean
x x x
=
s
sx
n
Degrees of freedom = n 1
Test Statistic: t
=
Hypothesis Test about proportion
STAT 3090
Test 3 - Version A
Fall 2014
Students Printed Name: _
XID:_
Instructor: _
Section # :_
Read each question very carefully. You are permitted to use a calculator on all portions of this exam. You are NOT
allowed to use any textbook, notes, cellpho
STAT 3090
Test 2 - Version A
Fall 2014
Students Printed Name: _
XID:_
Instructor: _
Section # :_
Read each question very carefully. You are permitted to use a calculator on all portions of this exam. You are NOT
allowed to use any textbook, notes, cellpho
MATH 3090 Summer 11 2014
Exam 2
Name:
MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the
question. Solve the problem. Place answer in provided space for given problem. Each MC problem is 3
pts.
1) A package deli
STAT 3090 Formula Sheet 2 Hawkes
Discrete Probability Distributions:
= E ( x) = x p( x)
2 = E [( x ) 2 ] = ( x ) 2 p( x) = [ x 2 p( x)] 2
Poisson Distribution:
Binomial Distribution:
n
= p x (1 p ) n x
P( x)
x
n
n!
=
x x!(n x)!
=
= np
p( x) =
x e
(STAT 3090) - Chapters 6 & 7 Fellers notes F 2014 (Oct 20, 2014)
CHAPTER 6
Pg 282: A random variable is the outcome of a random process.
Random variables can only assume one value at a time, and a chance
process always impacts the outcome. In business, ev
WORKSHEET 9: Chapter 13 Simple Linear Regression
NAME: _
SECTION:_
Grader: each part counts 12 point
The following data represent the total compensation for 10 randomly selected chief executive officers
(CEOs) and the companys stock performance in 2011. F
WORKSHEET 9: Chapter 13 Simple Linear Regression
NAME: Jessica Sieron
SECTION:_STAT 3090-13_
Grader: each part counts 12 point
The following data represent the total compensation for 10 randomly selected chief executive officers
(CEOs) and the companys st
WORKSHEET 7: Chapter 9 Confidence Intervals and Sample Size Estimation
NAME: _
SECTION:_Remember: Your page x = my page x
1
A Statistics class decided to study the proportion of purple candies in a random sample of 2500
Skittles. After much time counting
Calculator Tutorial TI 82/83/84
Provided by Dr. Gary Fellers Oct 7, 2013 Version
1. Entering Data
(You might need to turn the diagnostics ON to do certain calculations. Press the blue (or yellow)
2ND button, press the white 0, scroll down to DiagnosticOn,
Chapter 13
Getting An Equation for a Straight Line
Regression Analysis: Y = fn(X) = a + bX
Y^
=
^
0
+
^
1
X
(Dr. Fellers-Nov 19,
2014)
Question to be answered: Is there a statistically significant, linear relationship between X and Y;
^
^
and if so, what
Chapter 5 Fellers Class Notes
(Pg 224, Sep 12, 2014)
Probability
Probability examples at this level are either obvious (like the probability of a flipped coin
turning-up heads) or not so obvious (when you need to not panic while finding the correct
formul
STAT 3090
Test 3 - Version A
Fall 2014
Students Printed Name: _
XID:_
Instructor: _
Section # :_
Read each question very carefully. You are permitted to use a calculator on all portions of this exam. You are NOT
allowed to use any textbook, notes, cellpho
STAT 3090
Test 2 - Version A
Fall 2014
Students Printed Name: _
XID:_
Instructor: _
Section # :_
Read each question very carefully. You are permitted to use a calculator on all portions of this exam. You are NOT
allowed to use any textbook, notes, cellpho
Appendix A Table A
A Standard Normal Distribution
Numerical entries represent the probability that a standard normal random variable
is between - and z where z =
x
.
Area
z
z
0
z
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0.00
0.0002
0.0003
0.0003
0.0003
0.