Name
Course IProject
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C
I
Course IProject IC
PROJECT IPART IC: I Regression Iand ICorrelation IAnalysis
Using IMinitab, Iperform Ithe Iregression Iand Icorrelation Ianalysis Ifor Ithe Idata Ion ISALES I(Y) Iand ICALLS I(X)
Iby Ianswering Ithe Ifollowing Iquestions.
1. Generate Ia Iscatterplot Ifor ISALES Iversus ICALLS, Iincluding Ithe Igraph Iof Ithe Ibest Ifit
Iline.IInterpret. I(See IAppendix IA)
Sales I is I the I dependent I variable, I Calls I is I the I independent I variable. I The I trend I is I as I the
I callsIincrease Iso Idoes Ithe Isales.
2. Determine Ithe Iequation Iof Ithe Ibest Ifit Iline, Iwhich Idescribes Ithe Irelationship
IbetweenISALES Iand ICALLS.
The Iequation Iis ISales I= I9.638 I+ I0.2018 ICalls. I So Ifor Ievery Icall Ithe Isales Igo Iup I0.2018 Iin Isales.
3. Determine Ithe Icoefficient Iof Icorrelation. IInterpret.
The Icoefficient Iof Icorrelation Iis I0.871. IThis Iis Ishowing Ithat Ithere Iis Ia Istrong Irelationship Ibetween
Ithe Icalls Imade Iand Ithe Isales.
4. Determine Ithe Icoefficient Iof Idetermination. IInterpret.
The I coefficient I of I determination I is I 0.759. I The I proportion I of I the I variability I is I an
I independentIvariable.
5. Test Ithe Iutility Iof Ithis Iregression Imodel I(use Ia Itwo Itail Itest Iwith Iα I=.05).
IInterpret Iyour Iresults, Iincluding Ithe Ip-value.
T=17.5797 Ia=0.05. IP-value I= I0.00 IThere Iis Ia Irelationship Ibetween Ithe Icalls Iand Isales.
6. Based Ion Iyour Ifindings Iin I1–5, Iwhat Iis Iyour Iopinion Iabout Iusing ICALLS Ito Ipredict ISALES?
Explain. IIn Imy Iopinion Iit Iis Ia Igood Iidea Iyou Iuse Icalls Ito Ipredict Isales Ibased Ion Ithe Idata II Ihave
Iresearched. I I IThe Ifitted Iline Iplot Ishows Ius Ithat Ias Ithe Inumber Iof Icalls Iwent Iup Iso Idid Ithe Isales.
IYou Ican Ialso Itell Iby Ithe IP-value Iand Ithe Ialpha Ithat Ithere Iis Ia Istrong Irelationship Ibetween Icalls
IandIsales.
7. Compute Ithe I95% Iconfidence Iinterval Ifor Ibeta-1 I(the Ipopulation Islope).
Interpret Ithis Iinterval. I I Iam I95% Iconfident Ithat Ifor Ieach Iadditional Icall Ithat Ithe Iaverage Isales
Iwill Igo Iup Ibetween I0.17898 Iand I0.2245
.
8. Using Ian Iinterval, Iestimate Ithe Iaverage Iweekly Isales Ifor Iweekly Icalls Ithat Iare I150.
Interpret Ithis Iinterval. II Iam I95% Iconfident Ithat Ithe Imean Iweekly Isales Ifor Ithe Iweekly Icalls Iof I150
Iare Ibetween I39.41 Iand I40.40.
9. Using Ian Iinterval, Ipredict Ithe Iweekly Isales Iwhen Iweekly Icalls Iare I150.
, Interpret I this I interval. I I I am I 95% I confident I that I if I weekly I calls I are I 150 I the I weekly I sales I will
I beIbetween I35.79 Iand I44.01.
10. What Ican Iwe Isay Iabout Ithe Iweekly Isales Iwhen Iweekly Icalls Iare I300?
Explain I your I answer. I We I cannot I make I a I prediction I because I it I is I outside I the I rage I of I values I of
I ourIindependent Ivariable.
11. Using IMinitab, Irun Ithe Imultiple Iregression Ianalysis Iusing Ithe Ivariables ICALLS, ITIME,
IandIYEARS Ito Ipredict ISALES. IState Ithe Iequation Ifor Ithis Imultiple Iregression Imodel.
SALES I= I8.60864 I+ I0.20551 ICALLS I+ I0.0520391 ITIME I- I0.181791 IYEARS
For Ieach Icall Ithe Isales Iis Igoing Ito Igo Iup I0.20551 Iholding Iconstant Ithe Itime Iand Iyears.
12. Perform Ithe Iglobal Itest Ifor Iutility I(F-Test). IExplain Iyour Iconclusion.
I Iam I100% Iconfident Ithat Ithe Ientire Iregression Icoefficients Iare Iinsignificant Iat Ileast Ione Iis Isignificant.
13. Perform Ithe It-test Ion Ieach Iindependent Ivariable. IExplain Iyour Iconclusions, Iand Iclearly Istate
Ihow Iyou Ishould Iproceed. IIn Iparticular, Istate Iwhich Iindependent Ivariables Ishould Iwe Ikeep,
IandIw hich Ishould Ibe Idiscarded. I(See IAppendix IB)
The Iindependent Ivariables Ithat Ishould Ibe Idiscarded Iare Itime. I We Ishould Ikeep Ithe Icalls Iand Iyears.
14. Is Ithis Imultiple Iregression Imodel Ibetter Ithan Ithe Ilinear Imodel Ithat Iwe Igenerated Iin Iparts I1–10?
Explain. I(See IAppendix IC) IThe Isummary Imodel Ifor Ithe Imultiple Iregressions Iis Ivery Isimilar ItoIthe
Ilinear Imodel. I I Iwould Isay Ithat Ineither Ione Iof Ithem Iis Ibetter Ithan Ithe Iother,
Course IProject
I
C
I
Course IProject IC
PROJECT IPART IC: I Regression Iand ICorrelation IAnalysis
Using IMinitab, Iperform Ithe Iregression Iand Icorrelation Ianalysis Ifor Ithe Idata Ion ISALES I(Y) Iand ICALLS I(X)
Iby Ianswering Ithe Ifollowing Iquestions.
1. Generate Ia Iscatterplot Ifor ISALES Iversus ICALLS, Iincluding Ithe Igraph Iof Ithe Ibest Ifit
Iline.IInterpret. I(See IAppendix IA)
Sales I is I the I dependent I variable, I Calls I is I the I independent I variable. I The I trend I is I as I the
I callsIincrease Iso Idoes Ithe Isales.
2. Determine Ithe Iequation Iof Ithe Ibest Ifit Iline, Iwhich Idescribes Ithe Irelationship
IbetweenISALES Iand ICALLS.
The Iequation Iis ISales I= I9.638 I+ I0.2018 ICalls. I So Ifor Ievery Icall Ithe Isales Igo Iup I0.2018 Iin Isales.
3. Determine Ithe Icoefficient Iof Icorrelation. IInterpret.
The Icoefficient Iof Icorrelation Iis I0.871. IThis Iis Ishowing Ithat Ithere Iis Ia Istrong Irelationship Ibetween
Ithe Icalls Imade Iand Ithe Isales.
4. Determine Ithe Icoefficient Iof Idetermination. IInterpret.
The I coefficient I of I determination I is I 0.759. I The I proportion I of I the I variability I is I an
I independentIvariable.
5. Test Ithe Iutility Iof Ithis Iregression Imodel I(use Ia Itwo Itail Itest Iwith Iα I=.05).
IInterpret Iyour Iresults, Iincluding Ithe Ip-value.
T=17.5797 Ia=0.05. IP-value I= I0.00 IThere Iis Ia Irelationship Ibetween Ithe Icalls Iand Isales.
6. Based Ion Iyour Ifindings Iin I1–5, Iwhat Iis Iyour Iopinion Iabout Iusing ICALLS Ito Ipredict ISALES?
Explain. IIn Imy Iopinion Iit Iis Ia Igood Iidea Iyou Iuse Icalls Ito Ipredict Isales Ibased Ion Ithe Idata II Ihave
Iresearched. I I IThe Ifitted Iline Iplot Ishows Ius Ithat Ias Ithe Inumber Iof Icalls Iwent Iup Iso Idid Ithe Isales.
IYou Ican Ialso Itell Iby Ithe IP-value Iand Ithe Ialpha Ithat Ithere Iis Ia Istrong Irelationship Ibetween Icalls
IandIsales.
7. Compute Ithe I95% Iconfidence Iinterval Ifor Ibeta-1 I(the Ipopulation Islope).
Interpret Ithis Iinterval. I I Iam I95% Iconfident Ithat Ifor Ieach Iadditional Icall Ithat Ithe Iaverage Isales
Iwill Igo Iup Ibetween I0.17898 Iand I0.2245
.
8. Using Ian Iinterval, Iestimate Ithe Iaverage Iweekly Isales Ifor Iweekly Icalls Ithat Iare I150.
Interpret Ithis Iinterval. II Iam I95% Iconfident Ithat Ithe Imean Iweekly Isales Ifor Ithe Iweekly Icalls Iof I150
Iare Ibetween I39.41 Iand I40.40.
9. Using Ian Iinterval, Ipredict Ithe Iweekly Isales Iwhen Iweekly Icalls Iare I150.
, Interpret I this I interval. I I I am I 95% I confident I that I if I weekly I calls I are I 150 I the I weekly I sales I will
I beIbetween I35.79 Iand I44.01.
10. What Ican Iwe Isay Iabout Ithe Iweekly Isales Iwhen Iweekly Icalls Iare I300?
Explain I your I answer. I We I cannot I make I a I prediction I because I it I is I outside I the I rage I of I values I of
I ourIindependent Ivariable.
11. Using IMinitab, Irun Ithe Imultiple Iregression Ianalysis Iusing Ithe Ivariables ICALLS, ITIME,
IandIYEARS Ito Ipredict ISALES. IState Ithe Iequation Ifor Ithis Imultiple Iregression Imodel.
SALES I= I8.60864 I+ I0.20551 ICALLS I+ I0.0520391 ITIME I- I0.181791 IYEARS
For Ieach Icall Ithe Isales Iis Igoing Ito Igo Iup I0.20551 Iholding Iconstant Ithe Itime Iand Iyears.
12. Perform Ithe Iglobal Itest Ifor Iutility I(F-Test). IExplain Iyour Iconclusion.
I Iam I100% Iconfident Ithat Ithe Ientire Iregression Icoefficients Iare Iinsignificant Iat Ileast Ione Iis Isignificant.
13. Perform Ithe It-test Ion Ieach Iindependent Ivariable. IExplain Iyour Iconclusions, Iand Iclearly Istate
Ihow Iyou Ishould Iproceed. IIn Iparticular, Istate Iwhich Iindependent Ivariables Ishould Iwe Ikeep,
IandIw hich Ishould Ibe Idiscarded. I(See IAppendix IB)
The Iindependent Ivariables Ithat Ishould Ibe Idiscarded Iare Itime. I We Ishould Ikeep Ithe Icalls Iand Iyears.
14. Is Ithis Imultiple Iregression Imodel Ibetter Ithan Ithe Ilinear Imodel Ithat Iwe Igenerated Iin Iparts I1–10?
Explain. I(See IAppendix IC) IThe Isummary Imodel Ifor Ithe Imultiple Iregressions Iis Ivery Isimilar ItoIthe
Ilinear Imodel. I I Iwould Isay Ithat Ineither Ione Iof Ithem Iis Ibetter Ithan Ithe Iother,
