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Submitted by Allen on Sat, 2013-11-09 12:25
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Call center typically have high turnover. The director of human resources for a large bank has compiled data on about 70 former employees at one of the bank’s call centers in the Excel file Call Center Data. In writing an article about call center w

Call center typically have high turnover. The director of human resources for a large bank has compiled data on about 70 former employees at one of the bank’s call centers in the Excel file Call Center Data. In writing an article about call center w

 

(1)   

Call center typically have high turnover. The director of human resources for a large bank has compiled data on about 70 former employees at one of the bank’s call centers in the Excel file Call Center Data. In writing an article about call center working conditions, a reporter has claimed that the average tenure is no more than two years. Formulate and test a hypothesis using these data to determine if this claim can be disputed.

 

 

(2)   

Using the date in the excel file Home Market Value, develop a multiple linear regression model for estimating the market value as a function of both the age and size of the house. Find a 95% confidence interval for the mean market value for houses that are 30 years old and have 1,800 square feet and a 95% prediction interval for a house that is 30 years old with 1,800 square feet.

 

PLEASE ATTACHED IS THE CALL CENTER DATA  and  HOME MARKET VALUES FOR THE ASSIGNMENT.

Please be sure your work is organized, legible, and your responses are substantive. You need to submit all details of your work including excel sheets used to arrive to the solution. It is not enough to attach your excel sheet. You MUST provide interpretation of results and describe conclusions.

Answer
Submitted by Allen on Sat, 2013-11-09 12:28
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price: $30.00

Call center typically have high turnover. The director of human resources for a large bank has compiled data on about 70 former employees at one of the bank’s call centers in the Excel file Call Center Data. In writing an article about call center

body preview (250 words)

xx xxxx xxxxxx xxxxxxxxx xxxx high xxxxxxxxx xxx director of xxxxx resources for a large xxxx has compiled data xx xxxxx xx former employees at one xx xxx xxxxxxxx call xxxxxxx xx xxx Excel file xxxx Center Data. In writing xx article xxxxx xxxx center x

xx

xxx   

xxxx center xxxxxxxxx xxxx xxxx xxxxxxxxx xxx xxxxxxxx xx human xxxxxxxxx xxx a large xxxx has xxxxxxxx data xx about xx former xxxxxxxxx xx xxx of the xxxxxxxx xxxx centers xx the Excel xxxx Call xxxxxx xxxxx xx xxxxxxx an article about xxxx center xxxxxxx conditions, x xxxxxxxx has claimed xxxx the average tenure xx no xxxx than xxx years. xxxxxxxxx and xxxx x xxxxxxxxxx xxxxx xxxxx data xx xxxxxxxxx xx this xxxxx can xx disputed.

xx

 

(2)   

xxxxx xxx date in xxx excel file xxxx Market Value, develop a multiple xxxxxx regression model xxx xxxxxxxxxx xxx xxxxxx xxxxx as x function xx both xxx age xxx xxxx of xxx house. Find x 95% confidence interval xxx xxx mean xxxxxx xxxxx xxx xxxxxx xxxx are xx xxxxx xxx xxx have

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file1.xls preview (134 words)

xxxx Market Value

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxx Market xxxxx
xxxxx Age xxxxxx Feetxxxxxx xxxxxSUMMARY xxxxxx
331,812xxxxxxxxxx
32 xxxxx $104,400.00 xxxxxxxxxx xxxxxxxxxx House AgeSquare xxxx
321,842 xxxxxxxxxx xxxxxxxx x 0.7454947764
xxxxxxx xxxxxxxxxx x xxxxxx0.5557624616Mean xxxxxxxxxxxxxMean xxxxxxxxxxxxxxx
xx 1,836 $101,900.00Adjusted R xxxxxx 0.5329810494Standard xxxxx xxxxxxxxxxxxxxxxxxxx Error 33.986351355
33xxxxx$108,500.00 Standard xxxxxxxxxxxxxxxxxxxxxxxxxx 28Median 1666
xxxxxxx $87,600.00 Observations xxMode xxMode1520
331,850 xxxxxxxxxx Standard Deviation2.4286568271 xxxxxxxx Deviationxxxxxxxxxxxxxx
32 1,791$89,200.00ANOVA
33 1,666$88,400.00 df SS MSxSignificance F
321,852 xxxxxxxxxxx xxxxxxxxxx2 2537650170.692873 xxxxxxxxxxxxxxxxxx 24.3954350189 xxxxxxxxxxxx
321,620xxxxxxxxxxxxxxxxxx39xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
32xxxxx xxxxxxxxxx Totalxx xxxxxxxxxxxxxxxxx
xx 2,372 $114,000.00
xx2,372xxxxxxxxxxx xxxxxxxxxxxx xxxxxxxx xxxxxt xxxx P-valueLower xxxUpper xxx Lower xxxxxxxxxx 95.0%
xxxxxxx$87,500.00 xxxxxxxxx 47331.3815356157 13884.3466436745 xxxxxxxxxxxx0.0015278315xxxxxxxxxxxxxxxx 75415.123161466719247.6399097647 75415.1231614667
xxxxxxx $116,100.00xxxxx Agexxxxxxxxxxxxxxx 607.3128420834xxxxxxxxxxxxx xxxxxxxxxxxx -2053.5673802352 403.244939544-2053.5673802352xxxxxxxxxxxxx
32xxxxxxxxxxxxxxxSquare Feetxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxx xxxxxxxxxxxx 27.3660702956xxxxxxxxxxxxx xxxxxxxxxxxxx xxxxxxxxxxxxx
32xxxxx $86,400.00
xx1,666 $87,100.00 xxx xxxxxxxxx regression equation is: xxxxx x 47331.38 x (-825.16(House Age)) + 40.91(Square xxxxx
281,520$83,400.00
xx xxxxx$79,800.00
xx1,588$81,500.00 95% xxxxxxxxxx intervalxxxx + x standard deviation* x Stat/sqrt(sample)
xxxxxxx$87,100.00
28 1,484xxxxxxxxxx xxx xxxxxxxxxx interval House xxx xx x xxxxxxxxxxxxxxxxx xxxxxxxxx
281,484 xxxxxxxxxx
xx1,520xxxxxxxxxx xx + xxxxxxxxxxxxxxxxx xxxx 30.51
27 xxxxxxxxxxxxxxx
xx1,484 $82,000.00
xx1,468xxxxxxxxxx
xx1,520 xxxxxxxxxx95% xxxxxxxxxx interval xxxxxx Feet 30 - xxxxxxxxxxxxxxxxxx (42) -177.31
27xxxxx xxxxxxxxxx
271,484xxxxxxxxxx xx + 220.25*(6.10)/sqrt xxxx237.31
xxxxxxxxxxxxxxxxx
27 1,668xxxxxxxxxx
xx xxxxx xxxxxxxxxx 95% xxxxxxxxxx interval mean + x xxxxxxxx xxxxxxxxxx x Stat*sqrt(1 x xxxxxxxxx
281,784 $91,300.00
xx 1,484 $81,300.0095% xxxxxxxxxxx xxxxxxxx House Age xxx (2.43)*(1.36)*sqrt(1 + 1/42)26.66
27 1,520 xxxxxxxxxxx
xxxxxxxxxxxxxxxxx xxx (2.43)*(1.36)*sqrt(1 + 1/42)xxxxx
271,684$96,700.00
xx1,581 xxxxxxxxxxx
xxx xxxxxxxxxxx xxxxxxxx xxxxxx xxxx xxx (220.25)*(6.1)*sqrt(1 x 1/42) -1329.43
42
30+ (220.25)*(6.1)*sqrt(1 + xxxxx 1389.43

file2.xls preview (104 words)

Call Center

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxx xxxxxx Data
xxxx = 1 Female = xxxx = 1 No = xxxx = 1 No x x
xxxxxxxxxxxxxx xxx xxxxx Call Center xxxxxxxxxxxxxxxxx Degree Length of Service xxxxxxx t-Test: Paired xxx xxxxxx xxx xxxxx
0xx0x xxxx
1xx x0xxxx xxxxxxxx Age Length of Service xxxxxxx
0 xx 0 0 2.07 xxxx xxxxxxxxxxxxx 1.8942074364
01900 xxxx xxxxxxxx xxxxxxxxxxxxx xxxxxxxxxxxx
xxxx 0 4.42xxxxxxxxxxxxxxxx
xxx x 03.29xxxxxxx xxxxxxxxxxx xxxxxxxxxxxxx
x 19 1 x3.05 Hypothesized Mean Difference x
x191 0xxxx xx xx
x xx xx xxxxx xxxx xxxxxxxxxxxxx
1 19 x03.12 xxx<=t) one-tail x
0 20 0 x xxxxx xxxxxxxx one-tail1.6672385492
x xx 10 2.15 xxx<=t) two-tail0
xxxx 04.03 x Critical xxxxxxxxxxxxxxxxxxxx
1 20 x0 xxxx
x 200 x 2.47
0 21 x 0 2.15
1 21003.27 Conclusion: xx can xxx xxxx xxx xxxxxxxx value xx SMALLER xxxx the statistical value. xxx xxx xxxx hypothesis is xxxxx to xx xxxxxxxxx i.e. average tenure is xxxx xxxx 2 xxxxx and claim can be disputed using %5 xxxxx xx significance.
1 xx0x1.10
1 21x 0 1.78
x22x x 1.94
x2210 2.91
0xx1 xxxxx
x xx102.53
x23x1 1.84
x231 02.88
123 xx2.20
xxxxxxxxx
1 240x xxxx
1xxx 11.41
1xx 0 xxxxx
0 25x 1xxxx
x xx xx 0.63
1250 x 1.30
x25x 1xxxx
0xx1x2.30
0 xx1x xxxx
0xx1 x 2.13
1 26 1xxxxx
xxx x12.16
x xxx 0xxxx
028x 01.70
x xxx xxxxx
1290 1 xxxx
xxx0 12.15
x xx x x xxxx
1 30 x 1 xxxx
xxx 0 x1.95
0310x 1.02
x xxx1 xxxx
1xxx 0xxxx
x xxx 11.64
x32xx xxxx
x32x xxxxx
1 33x 0 1.29
0 34 x x 1.48
x xxx1 1.31
x 34 0 01.46
xxx x0xxxx
x36 0 x1.16
0xxxx xxxx
xxxx 1 1.05
xxx x 0xxxx
x 40xx 1.24
0 xxx 0 xxxx
1 xx1xxxxx
0xx 1 00.99
x43 1xxxxx
x xxx xxxxx
0xx1x 0.35
0 xx 1 0 xxxx


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