1. Using excel, determine the mean squared error for this model? What does it mean?
Transcribed Image Text:A
SUMMARY
1 OUTPUT
WN
2
3
4 Multiple R
5 R Square
Regression Statistics
7
Adjusted R
6 Square
Standard Error
Observations
8
9
10 ANOVA
11
12 Regression
13 Residual
14 Total
15
16
17 Intercept
18 fixed acidity;
volatile acidity
19
20 citric acid
residual sugar
21
22 chlorides
free sulfur
23 dioxide
total sulfur
B
24 dioxide
25 density
26 pH
27 sulphates
28 alcohol
00
0.600459577
0.360551703
0.356119484
0.648011208
df
1599
с
Coefficients
SS
D
11 375.7544028 34.15949116
1587 666.4107004 0.419918526
1598 1042.165103
Standard
Error
21.96520845 21.194575
0.024990553 0.025948502
-1.083590259 0.12110128
MS
t Stat
E
F
P-value
F
81.3479022 1.7914E-145
Significance F
-1.874225158 0.419283205 -4.470069717 8.37395E-06
0.004361333 0.002171292 2.008635263 0.044744951
Lower 95%
G
Upper 95%
H
Lower 95.0%
|
Upper 95.0%
1.036359939 0.300192136 -19.60710094 63.53751785 -19.60710094 63.53751785
0.963082682 0.335652752 -0.025906394 0.075887499 -0.025906394 0.075887499
-8.947801896 9.87236E-19 -1.321125565 -0.846054953 -1.321125565 -0.846054953
-0.182563948 0.147176188 -1.240444878 0.214994246 -0.471244142 0.106116245 -0.471244142 0.106116245
0.01633127 0.015002096 1.088599183 0.276495961 -0.013094741 0.04575728 -0.013094741 0.04575728
-2.69663236 -1.051817956 -2.69663236 -1.051817956
0.000102431 0.008620235 0.000102431 0.008620235
-0.00326458 0.000728729 -4.47982984 8.00461E-06 -0.004693951 -0.001835208 -0.004693951 -0.001835208
-17.88116384 21.63309988 -0.826565029 0.408607897 -60.31362221 24.55129454 -60.31362221 24.55129454
-0.413653144 0.191597361 -2.158970991 0.031001886 -0.789463688 -0.0378426 -0.789463688
0.916334413 0.114337465 8.014297061 2.12723E-15 0.692066057 1.140602768 0.692066057
0.276197699 0.026483586 10.42901431 1.12303E-24 0.224251206 0.328144192 0.224251206
-0.0378426
1.140602768
0.328144192
Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...
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