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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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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 (256 words)

xx xxxx xxxxxx xxxxxxxxx have xxxx xxxxxxxxx The director of human xxxxxxxxx for x large bank has compiled xxxx xx about xx xxxxxx employees xx xxx of xxx bank’s call xxxxxxx in xxx Excel xxxx xxxx Center xxxxx In writing an article xxxxx call center x

 

xxx   

xxxx center xxxxxxxxx xxxx high xxxxxxxxx xxx xxxxxxxx xx human resources xxx a large xxxx has compiled xxxx on about xx xxxxxx employees at xxx xx xxx xxxxxxxx call centers xx the xxxxx file Call xxxxxx Data. xx xxxxxxx an article xxxxx call center xxxxxxx xxxxxxxxxxx x reporter has claimed that the xxxxxxx xxxxxx is xx xxxx than two xxxxxx Formulate and test a xxxxxxxxxx using xxxxx xxxx to xxxxxxxxx xx this claim xxx xx disputed.

xx

 

(2)   

xxxxx xxx date xx xxx xxxxx file Home xxxxxx Value, xxxxxxx a xxxxxxxx linear regression model for estimating the xxxxxx xxxxx as x function xx both the xxx xxx xxxx xx the xxxxxx xxxx a 95% xxxxxxxxxx interval for the xxxx market xxxxx for houses xxxx xxx xx years xxx and have

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file1.xls preview (232 words)

xxxx Market Value

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Home xxxxxx Value
House Age xxxxxx FeetMarket xxxxxxxxxxxx OUTPUT
xx xxxxxxxxxxxxxxx
32 xxxxx $104,400.00 Regression xxxxxxxxxxHouse Age Square Feet
xx xxxxx $93,300.00 xxxxxxxx R0.7454947764
xx1,812 xxxxxxxxxxx xxxxxx xxxxxxxxxxxxMean xxxxxxxxxxxxx Mean1695.2619047619
321,836 $101,900.00xxxxxxxx R xxxxxx 0.5329810494 xxxxxxxx Error0.3747498843xxxxxxxx xxxxx xxxxxxxxxxxx
33xxxxx$108,500.00 xxxxxxxx Error xxxxxxxxxxxxxxx Medianxxxxxxxxxxxx
xxxxxxxxxxxxxxxxx Observations xxxxxxxxMode xxxx
33 xxxxx$96,000.00 xxxxxxxx xxxxxxxxxxxxxxxxxxxxx xxxxxxxx Deviation xxxxxxxxxxxxxx
32 1,791$89,200.00 ANOVA
xxxxxxx$88,400.00 xx SS MSF xxxxxxxxxxxx F
32xxxxx $100,800.00Regressionx2537650170.6928731268825085.3464365 24.3954350189xxxxxxxxxxxx
xx xxxxx $96,700.00 Residual 39 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
32xxxxx$87,500.00 Total 41 4566069761.904759
322,372 xxxxxxxxxxx
32xxxxxxxxxxxxxxxx xxxxxxxxxxxx Standard Errort xxxx xxxxxxxxxxxx 95% Upper xxxLower xxxxxxxxxx 95.0%
xx xxxxx xxxxxxxxxxxxxxxxxxx47331.381535615713884.34664367453.4089743472 xxxxxxxxxxxx19247.6399097647xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx 75415.1231614667
xx xxxxxxxxxxxxxxxx xxxxx xxx xxxxxxxxxxxxxxx607.3128420834 xxxxxxxxxxxxx xxxxxxxxxxxx-2053.5673802352 xxxxxxxxxxxxx xxxxxxxxxxxxxxxx403.244939544
321,620xxxxxxxxxx Square xxxx xxxxxxxxxxxxx6.6965239941 6.1092991654xxxxxxxxxxxx xxxxxxxxxxxxx 54.4560666013xxxxxxxxxxxxx54.4560666013
xx xxxxx xxxxxxxxxx
xx 1,666 xxxxxxxxxxThe xxxxxxxxx xxxxxxxxxx equation xxx Value =xxxxxxxx x (-825.16(House xxxxx + xxxxxxxxxxxx xxxxx
281,520 $83,400.00
27 1,484 xxxxxxxxxx
xx1,588 $81,500.00 95% xxxxxxxxxx interval xxxx + - standard xxxxxxxxxx x xxxxxxxxxxxxxxxxx
xx xxxxx$87,100.00
281,484xxxxxxxxxx95% confidence interval xxxxx Age xx - (2.43)(1.36)/sqrt xxxx29.49
28 1,484xxxxxxxxxx
281,520xxxxxxxxxx 30 +

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file2.xls preview (299 words)

Call Center

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxx xxxxxx Data
Male x xxxxxxxx x 0xxx = xxxx x x xxx = xxxx = 0
GenderStarting xxx Prior Call Center ExperienceCollege xxxxxx Length of Service (years) t-Test: xxxxxx xxx xxxxxx for Means
x18 x x xxxx
x xxx 0 xxxx xxxxxxxx Age xxxxxx of xxxxxxx xxxxxxx
xxxx0 2.07xxxx27.84285714291.8942074364
x190 xxxxxxxxxxxxxxxxxxxxxxxxxx 1.2059960224
0 xx00 4.42 Observationsxx xx
0 xx x0 xxxxxxxxxxx Correlation -0.6078345192
0 19 1x3.05Hypothesized Mean xxxxxxxxxxx
xxx 10 0.49df 69
1 19x0 0.61x Stat24.9032490612
x xx 0x3.12 P(T<=t) xxxxxxxx 0
02000 2.95 x xxxxxxxx one-tail xxxxxxxxxxxx
x 20 102.15 xxx<xxx two-tailx
0 xx x x 4.03x xxxxxxxx xxxxxxxx 1.9949453901
x xx 0x xxxx
x 200x2.47
0xx00 2.15
1xx 003.27 Conclusion: xx can xxx xxxx xxx critical value is xxxxxxx xxxx the xxxxxxxxxxx value. xxx xxx xxxx hypothesis is xxxxx to xx xxxxxxxxx i.e. xxxxxxx xxxxxx xx xxxx xxxx 2 years and xxxxx can be xxxxxxxx using xx xxxxx of

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