I.
Estimating the Mean Diameter of Towel
Rolls
Open the file lab4.xls and the worksheet Confidence Interval. The following labels are in the range A1-A3
on your worksheet: Sample size, Conf_Level, and St.Deviation. In the range B1-B3 you will enter the
cu
Statistics 235
Gregory M. Wagner
Laboratory 4
ER3
1a)
ALLOY1
Mean
Standard Error
Median
Mode
ALLOY2
65.09
0.36098
64.6
63.8
ALLOY2+TREATMENT
Mean
65.27333
Mean
Standard Error
Median
Mode
0.167602
65
64.9
Standard Error
Median
Mode
Standard Deviation
1.977
1.
(a)
(b)
2.
(a)
(b)
First you will examine the relationship between the response variable (thrust) and each of of the
three predictor variables with scatterplots.
Obtain a scatterplot of thrust versus each of the three predictors. The format of each of
LAB 4 ASSIGNMENT
CONFIDENCE INTERVALS AND HYPOTHESIS TESTING
This lab assignment will give you the opportunity to explore the concept of a confidence interval and
hypothesis testing in the context of a real-world problem. In particular, you will study the
Name: _
Student No.: _
University of Alberta
Department of Mathematical and Statistical Sciences
Statistics 235 Final Examination Version A
Date: April 20, 2009
Instructor (circle):
P. Cartledge,
H. Kolacz
T. Varghese,
Time: 9:00-12:00
Instructions: (READ
SOLUTIONS TO LAB 4 ASSIGNMENT
Question 1
(a)
Let X be the amount of drink in a randomly selected bottle. Then given the mean of 302 ml,
standard deviation of 2 ml, and the normality of X, we have
P ( X < 300) = P ( Z =
X
<
300 302
) = P ( Z < 1) = 0.1586
LAB 1 ASSIGNMENT
DISPLAYING AND DESCRIBING DISTRIBUTIONS
In this lab assignment you will use statistical features in Excel to evaluate the accuracy of a scale weighing
trucks in motion. You will learn how to display the related data using histograms and s
ASSIGNMENT 5
SIMPLE LINEAR REGRESSION
In this assignment you will use linear regression features available in Excel to examine the relationship between
the thrust of a jet-turbine engine and three predictor variables such as fuel flow rate, exhaust temper
LAB 2 ASSIGNMENT
PROBABILITY DISTRIBUTIONS
In this lab assignment you will use numerical and graphical tools available in Excel to analyze a filling process
described by a normal distribution. You will use the process to explore the basic properties of di
LAB 3 ASSIGNMENT
SAMPLING DISTRIBUTIONS. CENTRAL LIMIT THEOREM
In this lab assignment you will explore important properties of sampling distributions in the context of a
quality control process and computer simulation. In particular, you will use the Rand
UNIVERSITY OF ALBERTA
STATISTICS 235: LAB 2
ASSIGNMENT
[Type the document subtitle]
Dylan MCATEE
LAB 2 ASSIGNMENT
1.
(a)
Assume that the mean weight is set at 300 ml. Enter the value of as 4, then 6,
and eventually 8 ml. After each entry, carefully examin
1.
a) Factor which affect distance traveled are HEAD, CARRY, MODEL and
possibly TEMP. HEAD, CARRY and MODEL ARE all controllable where as
TEMP is not. Launching the second model after each first model ensure
conditions stay the same for the second model.
CONNOR HARTLEY
STAT 235
LAB EL03
LAB # 4
STATS LAB # 4
ID : 1514509
1
a.) The margin of error for all of the intervals was 0.120123.
b.) The fraction that contain the population mean was 55/60. If the simulation were to repeated with a different seed
you
1.
a)
recession velocity at certain distances
1200
1000
800
600
recession velocity
400
200
0
-200
0
0.5
1
1.5
2
2.5
-400
distance
b)
Relatively strong, positive, quite linear, no unusual observation
2.
a) 0.789639
b) sign of the correlation is positive, m
1.
(a)
X= amount of ml in a randomly selected bottle.
mean = 302 ml, standard deviation= 2 ml
P ( X < 300) = P ( Z = X < 300 302 ) = P ( Z < 1) = 0.158655
Approximately 15.87% of bottles at the mean of 302 ml will be underfilled.
Using the COUNTIF functio
1.
a) when sigma is increased, the maximum point decreases and the left and right
edges increase making the graph increasingly flat. An increase in the standard
deviation means the strength of each alloy is less consistent and it results in more
unfavorab
1.
a)
P=0.779
b)
x=1 mean=0.25
1 P(X=<x)=1-0.9735=0.0265
c)
P=0.765
d)
Increasing , starts to skew the graph in the other direction.
The increase implies that there are is a much greater probability of
having a tile with a flaw, due to having a much highe
Connor Hartley
Stats 235 Lab #1
LAB EL03
Stats Lab #1
1.)
a.) The shape of the histogram from the data set is slightly left skewed, but overall fairly
symmetric and single peaked. It appears there is one outlier at a pull strength of 75.
b.) The approxima
CONNOR HARTLEY
STAT 235
LAB EL03
LAB # 5
STATS LAB # 5
ID: 1514509
Units Produced Over 25 Months
Quantity
(per Minute)
500
480
460
440
420
400
380
360
340
320
300
0
5
10
15
20
25
Month
1
b.) The trend from the plot is that the average number of units incr
Statistics 235
Gregory M. Wagner
Laboratory 5
ER3
1a)
b)
c) The Atlantic regions relationship is reasonably strong. It is scattered, and not linear. If we
were to draw a straight line on this graph, there would be many outliers. The points are not
followi
STAT235 LAB#1
LAB Section:EA6
Pengyu Chen
ID: 1432818
Sept. 17 2015
1. The study is an example of an observational study. Because there is neither
comparison nor control in the whole study. Plus, there is no statement in the
introduction that it is an exp
Stat 235 Assignment #4 Solutions Fall 2015
SOLUTIONS TO HOMEWORK ASSIGNMENT 4
12.1.2 (15 marks total: (a) 1 (b) 1 (c) 2 (d) 5 (e) 6)
X - amount of a catalyst
Y - purity of a chemical solution
( purity | amount ) E ( purity | amount ) 123.0 2.08(amount ),
Statistics 235 Homework #2 Solutions Fall 2015
SOLUTIONS TO HOMEWORK ASSIGNMENT 2
4.1.2
Let X = voltage of a new battery. We are given that X ~ Uniform(1.43,1.60).
1
1
, 1.43 x 1.60
f X ( x) 1.60 1.43 0.17
0
, else
(a) X E[ X ]
1.43 1.60
1.515.
2
(b) X
Statistics 235 Homework #1 Solutions Fall 2015
SOLUTIONS TO HOMEWORK ASSIGNMENT 1
6.2.4
The histogram for the data obtained with Excel is displayed below:
The histogram shows two observations separated from the main body of data. A glance at the data
set
Homework Assignments:
There will be four homework assignments in the course. The homework assignment questions are
taken from the textbook. Homework assignments must be submitted to the assignment box outside
of CAB 331/335 by 22:00 PM on the due date. Ma
Statistics 235 Midterm Examination Version A
Date: February 26, 2013
Instructor: H. Kolacz, M. Maciak, G. Wagner
Time: 11:00-12:20
Name: _
I.D. #: _
Instructions:
1. This is a closed book exam. You are permitted to use a non-programmable calculator
approv
LAB 2 ASSIGNMENT
PROBABILITY DISTRIBUTIONS
In this lab assignment you will use numerical and graphical tools available in Excel to examine the process of
manufacturing of ultra-strong alloys used in fasteners, springs and instrument parts. You will use th
LAB 1 ASSIGNMENT
DISPLAYING AND DESCRIBING DISTRIBUTIONS
In this lab assignment you will learn how to apply graphical and numerical tools in Excel to analyze data
produced in a simple experiment. In particular, you will display the distance traveled by a
LAB 5 ASSIGNMENT
LINEAR REGRESSION AND CORRELATION
In this lab assignment you will use simple linear regression to examine the relationship between distance
from the earth and the recession velocity of galaxies. In particular, you will use scatter plots t