The next tab of this Excel spreadsheet contains the NFL raw data for these problems.
In the National Football League, the philosophy for winning (rushing, passing,
defense) seems to go through cycles. Consider a time series of the average
number of rushin

Question:
Does "gender" influence the relationship between hand and foot?
Does adding "gender" to our regression model improve our ability to predict foot size given hand size?
Data Collection:
(in Centimeters)
Which variable(s) are the input (x)?_
1
2
3

x-bar / R Chart Exercise : Testing the Measurement System
10 pound bag of cracked corn
Graph both charts:
n=3
Sample
Day 1
Day 2
Day 3
Day 4
Day 5
Day 6
Day 7
Day 8
Day 9
Day 10
Day 11
Day 12
Day 13
Day 14
Day 15
Day 16
Day 17
Day 18
Day 19
Day 20
R-chart

MBC 638
Data Analysis
Increase Weekly Savings
DMAIC Process Project
Michael C. Bores
Professor Kivanc Avrenli
Define: Complete by April 16th, 2016.
Measure: Complete by May 2nd, 2016.
Define
Problem statement. My wife and I are currently
saving $200.00 a

Monthly U.S. Trade Deficits, 1988 ($ billions)
Jul-88
Aug-88
Sep-88
Oct-88
X
X(bar) 10.3166667
mR(bar)
X(bar)
mR(bar)
0.8
UNPL = X(bar) + (2.66 x mR)
LNPL = X(bar) - (2.66 x mR)
URL = 3.27 x (mR)
X
Jul
10.5
Aug
11.2
Sep
9.2
Oct
10.1
Nov
10.4
Dec
10.5
Jan

1st function norm.s.dist NORMAL PROBABILTY DISTRIBUTION
Q: WHAT % OF STUDENTS ARE SHORTER THAN 60"?
GIVEN: u = 50, o =5
x = 60
50 = mean
5 = std dev
true you want the cumulative probability
Z= (60-50)/5 = 2
0.98 - area under curve that represents area sho

Figure 6.7: Monthly U.S. Trade Deficits, 1988 ($ billions)
X(bar) 10.3166667
mR(bar)
X(bar)
mR(bar)
0.8
UNPL = X(bar) + (2.66 x mR)
LNPL = X(bar) - (2.66 x mR)
URL = 3.27 x (mR)
X
Jul
10.5
Aug
11.2
Sep
9.2
Oct
10.1
Nov
10.4
Dec
10.5
Jan
Feb
Mar
Apr
May
Ju

Question:
Can the length of your hand predict the size of your foot? Is there a relationship?
Data Collection:
(in Centimeters)
Which variable is the output (y)?_The measurement of the foot is the output.
Hand
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18

15.1
7.8
8.9
17.2
10.9
15.7
confidnece interval
20.2888423
3.9 stdev
12.6 avg
4.1
8.5
16.7
We are 95% confidnet that 8.5 <orequal Mu <orequal16.7
2.2
2.4
3.8
2.2
2.5
4.3
n
CI
a
E
6.00
0.95
0.05
0.50
* step 1 S
*step 2 Za/2
0.91
-1.96
How many more obsevat