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Question
Submitted by rbcjy on Fri, 2012-05-04 08:19
due on Fri, 2012-05-04 11:00
answered 5 time(s)
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CORRELATION AND REGRESSION

Please give step-by-step answers with explanations, thanks!

Answer
Submitted by Coloratus on Fri, 2012-05-04 12:59
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Complete answer to first problem

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Formula xxxx xxxxxxxxxx r xxx

As a result, xx have:


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Answer
Submitted by rajendrabnk on Fri, 2012-05-04 15:43
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please find it attached

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x have tried as much as possible to explain to xxx xxx xxxxxxxx Let xx know xx xxx xxxx xxxx xxxxx Also, Please DO NOT forget xx rate me xx you liked xx xxxxxxxx A testimonial xxxx be a xxxxx xxx xx acknowledge! xx

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17.2

The xxxxxxx xxx the xxxxxxxxxxx coefficient xx given xx

Now, all the xxxxxx xxx xxxxx in the xxxxxxxxx Substituting, xx get:

r = xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxx xxxx

2 )]

r = xxxxxxxxxxxxxxxxxxx

x = 0.7835

17.3

xxx xxxxxxxxxxx xxxxxxxxxxxx represents xxx xxxxxx of xxxxxxxxxxx xx xxxxxxxxxx xxxxxxxxx xx xxx variable

explained xx the xxxxx xxxxxxxxx xxxxx 78.35% xx variation xx Y is explaned by X.

Section B

1. The xxxxxxx numbers xxxx xxxx filled.

xx Y is perfectly correlated with X. In xxxx xxxxx for xxxxx additional x, x xxxxxxx by xx xxx

values xxx xxxxxxxxxx xxxxxxxxxxxx

x Y

x 7

2 xx

x xx

10 52

13 67

b) x xx xxxxxxxxx negatively correlated xxxx X. xxxx means xxxx for xxxxx xxxxxxxxxx xx x xxxxx xx

xxxxxxxx xxxxxxxxx xx x xxxxxxxxxx xxxxx amount (Here, x xxxx xxxxx xx

x x

1 5

x x

x 3

x 2

x x

c) The mean xxxxxx be xxxx xxx standard xxxxxxxxx should xx

- - - more text follows - - -

file2.xls preview (74 words)

data

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Yearxy
Motorboats xxxxxxxxxxxxxxxxx xxxxxx xyx squarex xxxxxx
1977xxx 13xxxx xxxxxx 169
xxxx xxxxxxxxx xxxxxx 441
1979 xxx 24 11544xxxxxxxxx
xxxx498 xx7968 xxxxxx256
xxxx 513 xxxxxxx263169 576
1982 512 20xxxxx xxxxxx xxx
xxxxxxx 157890xxxxxx225
1984 559 34 xxxxxxxxxxx1156
xxxx 585 33xxxxxxxxxxx xxxx
xxxx xxx33 xxxxx 376996 xxxx
1987 xxx3925155 xxxxxx 1521
1988 xxx43 xxxxxxxxxxx xxxx
xxxx 711 xx35550505521xxxx
1990719 47xxxxx xxxxxx 2209
xxx xxxx
xxx412
xxxx xxxxxx
Ʃ(x^2)4618597
Ʃ(y^2) 14056
rxxxxxxxxxxxx

Regression line

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxx OUTPUT
Regression xxxxxxxxxx
Multiple R0.9414772888
R Squarexxxxxxxxxxxx
Adjusted x xxxxxx0.8769111091
Standard Error xxxxxxxxxxxx
xxxxxxxxxxxx14
ANOVA
dfSS xx x xxxxxxxxxxxx F
Regressionx 1711.9786630483xxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxxx12xxxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxx xxxxxxxxxxxxxxx
xxxxxxxxxxxxxxxxxxxx xxxxx t xxxx xxxxxxx xxxxx 95%xxxxx 95%Lower xxxxxUpper xxxxx
Intercept-41.43043894857.4122172282 -5.5894798645 xxxxxxxxxxxx xxxxxxxxxxxxxx -25.2806049554xxxxxxxxxxxxxx-25.2806049554
x xxxxxxxx 1xxxxxxxxxxxx 0.01290497369.6754705394 0.0000005109xxxxxxxxxxxx 0.1529792144 0.09674417020.1529792144
For xxx boats, x xxxxxxxxxxxxxx
Confidence interval xx xxx confidence xxxxx xxxxxxxxxxxxx to69.4627304557

xxxxxx

x

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xxx

The xxxxxxxxxx xxxxxxxxxxxx xx calculated by the following equation (In xxxxxx x put xx this formula

and xx calculates xx xxxxxxx xx xx just like x calculator).

xxxx xxx xxxxxxxxxxx coefficient xxxxx xxxxx of 0.941 xxxxx xxx xxx predict xxx xxxx score from

the xxxxxx xxx xxxx xxx error xx prediction xx xxxxxxxxxx small. We xxxxx conclude that this xxxx

is reliable.

xxx xxxxxxxxxx xxxxxxxx is xxxxxxxxx below xxx xx is xxxxxxxx xx x similar xxxxxxx to xxx

correlation coefficient. xxx xxxxxxxxxx equation is xxxx xx xxxxxxx xxxxxx xx xxx xxxxxxxxx

xxxxx (Y) from xxxxxx of xxx Independent Value (X). The xxxxxxx x and I xxxxx xxx the xxxxx and

xxxxxxxxx respectively.

xxx slope and intercept xxx xxxxxxxx using the xxx xxxxxxxxx below.

You can either calculate xxx above xxxxxxxx by xxxxxxxxxx or by xxxxx (I had xxxx xxxxxxxxxx xx

xxxxxxx All the values that are xxxxxx xxx calculation xx Slope and x are in excel. You xxx just xxx

in xxx xxxxxx xxx

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Answer
Submitted by shahimermaid on Fri, 2012-05-04 14:10
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the answer is in attached file

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xxxx

xxxxxxxxxxxxxx x xxxxx - xxxxxxxxxx x Sqrt([NΣX2 x xxxxxxx xxxx [NΣY2 x (ΣY)2])

= 10 (5980)-(525)(100)/ sqrt ({10(32,085)-(525)^2} Sqrt xxx xxxxxxxxxxxxxxxx

x 59800 -52500/ sqrt ({320850-275625} xxxx xxxxxxxxxxxxxx

xxxxxxxxxx (45225) Sqrt xxxxxx

=7300/212.66 x 43.82

xxxxx

xxxx

r^2 xxx be interpreted xx the xxxxxxxxxx of variance xx y xxxx is accounted xxx by x. r^2 = xxxx xx xxx xxxx 61 xxxxxxxxxx of the xxxxxxxx in y xx xxxxxxxxx xxx xx xxxxxxxxxxx xx xx

section x

Q1 a) missing y= xx

b) y x xxxxxxxxx

c) xx 2,3,4,5,6

y: xxxxxxxxx

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

x

y

x^2

xxx

xy

xxx

xx

xxxxxx

169

5811

xxx

21

211600

441

xxxx

xxx

xx

231361

576

xxxxx

498

xx

248004

xxx

7968

xxx

24

263169

xxx

12312

xxx

20

xxxxxx

400

10240

xxx

xx

xxxxxx

225

7890

559

xx

xxxxxx

xxxx

xxxxx

xxx

xx

342225

xxxx

19305

614

33

xxxxxx

xxxx

20262

645

39

xxxxxx

1521

xxxxx

675

xx

xxxxxx

1849

xxxxx

711

50

505521

xxxx

35550

xxx

xx

xxxxxx

xxxx

xxxxx

 

 

 

 

 

xxxx

412

xxxxxxx

xxxxx

xxxxxx

Q2 Correlation(r) = NΣXY - xxxxxxxxxx / xxxxxxxxxxx - (ΣX)2] Sqrt xxxxxx x xxxxxxxx

14 (247521)-(7945)(412)/ xxxx xxxxxxxxxxxxxxxxxxxxxx sqrt x 14(14056)-(412)^2

3465294-3273340/ sqrt (14(4618597)-(7945)^2) xxxx ( xxxxxxxxxxxxxxxxx

xxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

xxxxxxxxxxxxxx x 164.44

xxxxx

xx is xxxxxxxxxx correlated

xx

Simple xxxxxx xxxxxxxxxx xxxxxxxx Dependent Variable: y Independent xxxxxxxxx x

Regression xxxxxxxxxxx = x + xx Slope(b) = (NΣXY x (ΣX)(ΣY)) / xxxxxx x xxxxxxxxxxxxxxxxxxxx = (ΣY x xxxxxxx x N

Y=-41.43 +0.12 xxxxxxx xx xx 140

c) R-sq x 0.8863795 . xxx accuracy is xxxx


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Answer
Submitted by shahimermaid on Fri, 2012-05-04 09:13
teacher rated 387 times
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solution to section A

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17.2

Correlation(r) = NΣXY - (ΣX)(ΣY) / xxxxxxxxxxx x (ΣX)2] xxxx xxxxxx - (ΣY)2])

x 10 xxxxxxxxxxxxxxxxxx xxxx ({10(32,085)-(525)^2} xxxx xxx (1192)-(100)^2})

x xxxxx -52500/ xxxx ({320850-275625} xxxx {11920-10000})

=7300/sqrt xxxxxxx Sqrt xxxxxx

xxxxxxxxxxxx x xxxxx

xxxxx

17.3

xxx xxx be xxxxxxxxxxx xx xxx percentage of xxxxxxxx xx y that is accounted for by xx xxx x xxxx xx say that 61 percentage xx the xxxxxxxx xx x xx accounted xxx by differences in xx


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