#1
x
y
22
24
26
30
35
40
12
21
33
35
40
36
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.794632
R Square 0.631439
Adjusted R Square
0.539299
Standard Error
7.269276
Observations
6
y
y
50
2000
0
0
0
Normal Probability Plot
Normal Probability Plot
22
10
7.35
7.4
7.55
7.56
7.6
7.52
7.52
7.7
7.62
7.55
Commodity Futures Index
Time Series Plot
7.8
7.6
Index
Melinda Tanner
Test 3
CH. 18 #15
a.
Week
Index
1
2
3
4
5
6
7
8
9
10
7.4
7.2
7
0
1
2
3
Commodity Futures Index continues to grow even with a slight declin
Chapter 18, #11.
For the Hawkins Company, the monthly percentages of all shipments that were received on time
over the past 12 months are 80, 82, 84, 83, 83, 84, 85, 84, 82, 83, 84, and 83.
a. Construct a time series plot. What type of pattern exists in t
Exp. 3: Separation of a Mixture and Physical Properties of Elements
Name:
Hood/Lab Partner:
OVERVIEW OF EXPERIMENT:
This experiment is about separation methods commonly used to separate components in mixture. You will separate
three components (pure subst
Exp. 5: Shapes of Molecules (Valence Shell Electron-Pair Repulsion/VSPER Theory)
Name:
Hood/Lab Partner:
OVERVIEW OF EXPERIMENT:
In this lab you will draw Lewis Structures to predict the geometric shapes of small molecules based on the repulsive
forces of
Experiment 2: DENSITY
Also: Percent Error, Specific Gravity, Accuracy & Precision
Name:
Lab Partner/Hood:
OVERVIEW OF EXPERIMENT:
The density of a substance is the relationship between the mass of the substance and how much space it takes up
(volume). Den
CashECCashgnivalents
M t N -D'scretion
m hlyCashonFltlm "Y
The number of months
of non-discretionary
expenses in the form of
cash and cash equivalents.
The number of times a
client can satisfy their
short-term liabilities.
EBT RATIOS
Housing Ratio 1
(Basi
Alphabetical Statistical Symbols:
Symbol
Text
Equivalent
a
Y- intercept of least
square regression line
Slope of least
squares regression
line
b
B (n, p)
Binomial
distribution with
parameters n and
p
c
n
C
C
Meaning
n-c-r
r
n, r
Cov (X, Y)
n-c-r
Covarianc
Exp. 8: Equilibrium and Le Chteliers Principle
Name: Anh Le
OVERVIEW OF TOPICS:
Earlier in the semester you learned how to look at a chemical equation and classify the reaction as a combination,
decomposition, single replacement, double replacement, or co
Lab 3: Measurements
https:/gpc.view.usg.edu/content/enforced/974597-C0.710.CHEMl
.
Listen
Lab 3: Measurements
Concepts to explore:
Learn how to use significant figures and understand their
importance
Make effective and useful measurements in a chemistry
Anh Le
United States History 2110
Assignment #5
1. Reconstruction: the Union victory in the Civil War in 1865 may have given
some 4 million slaves their freedom, but the process of rebuilding the South
during the Reconstruction period (1865-1877) introduc
Exp. 4: Chemical Reactions
Name:
OVERVIEW OF TOPICS:
A chemical change occurs when a substance is converted into one or more new substances chemical changes can be
represented by chemical equations. A chemical equation is a shorthand way to represent a ch
Experiment 2: DENSITY
Also: Percent Error, Specific Gravity, Accuracy & Precision
Name:
Lab Partner/Hood:
OVERVIEW OF EXPERIMENT:
The density of a substance is the relationship between the mass of the substance and how much space it takes up
(volume). Den
Exp. 7: Solution Formation and Solution Concentration Calculations (Molarity and Percent Concentrations)
Name:
Hood/Lab Partner:
OVERVIEW:
This lab has 2 distinct parts prediction and obsevation of solution formation (a homogenous mixture) based on
differ
Chapter 11
Inferences About Population Variances
Learning Objectives
1.
Understand the importance of variance in a decision-making situation.
2
Understand the role of statistical inference in developing conclusions about the variance of a single
populatio
18.2
Forescast Error
Forecast Error= Actual Value - Forecast
Percentage Error
Percentage Error= (Forecast Error/Actual Value)*100
Mean absolute Error
MAE= average of the absolute value of forecast errors=
Total of Absolute Forecast Errors/Number of Foreca
Test 1
Ch 12 Q39
39. Ho: The number of sales per day has a binomial probability distribution.
Ha: The number of sales per day does not have probability distribution.
Used the Binomial Probabilities Chart n=4 p=.30
Number of Sales
Frequency
0
1
2
3
4
Obser
Anova: Single Factor
SUMMARY
Groups
Count
Column 1
8
Column 2
8
Column 3
8
ANOVA
rce of VariationSS
Between Groups
2765.653
Within Groups
2681.14
Total
5446.793
Sum
Average
1256.4
157.05
1125.2
140.65
1048.4
131.05
df
Variance
126.2486
108.2943
148.4771
M
13.2
H0: 1=2=k
Ha: Not all population means are equal
where
j= mean of the jth population
We assume that a simple random sample of size nj has been selected from each of the k populations
or treatments. For the resulting sample data, let
xij= value of obs
Solution to question 16 Chapter 14
i
1
2
3
4
5
xi
3
12
6
20
14
yi
55
40
55
10
15
y^i = 68 - 3xi
59
32
50
8
26
yi - y^i
-4
8
5
2
-11
(yi - y^i)
16
64
25
4
121
SSE = 230 (this is the sum of the 5 numbers above
To find SST all you do is take average of row y
=25+10x+8x
SST=
SSR=
a)
16000
12000
n=
p=
SSE
n-p-1
571.42857
MSR=
SSR
p
6,000
F=
MSR
MSE
numerator deg of freedom=
denominator deg of freedom=
4,000
MSE=
b)
SSE=SST-SSR
10
2
10.5
p-value=
0.008 <.05
Since the p-value is less than .05, a significant relat
#12
SST=
ssr=
r2=
a
r2/a=
b
c
15,182.90
14,052.20
ssr/sst
0.926
1-(1-r2)[n-1/n-p-1
n=10 observations
p=2 independent variable
0.904
I guess because we can account for almost 91% of y
adjusting for the number of independent variables in the model, we see t