Multicollinearity issue, does it make my results insignificant?
I have conducted a regression where 6 out of 9 explanatory variables are marked on the same scale of 0 to 5. Excerpt from data seen below.
[TABLE="width: 384"]
[TD="class: xl64, width: 64, align: right"]1[/TD]
[TD="class: xl65, width: 64, align: right"]2[/TD]
[TD="class: xl65, width: 64, align: right"]3[/TD]
[TD="class: xl65, width: 64, align: right"]4[/TD]
[TD="class: xl65, width: 64, align: right"]5[/TD]
[TD="class: xl64, width: 64, align: right"]6[/TD]
[TD="class: xl66, align: right"]2.7945709[/TD]
[TD="class: xl63, align: right"]2.523261[/TD]
[TD="class: xl63, align: right"]2.768621[/TD]
[TD="class: xl63, align: right"]3.12227[/TD]
[TD="class: xl63, align: right"]2.537218[/TD]
[TD="align: right"]2.287279[/TD]
[TD="class: xl66, align: right"]2.6657027[/TD]
[TD="class: xl63, align: right"]2.318319[/TD]
[TD="class: xl63, align: right"]2.883092[/TD]
[TD="class: xl63, align: right"]3.089985[/TD]
[TD="class: xl63, align: right"]2.463932[/TD]
[TD="align: right"]2.315841[/TD]
[TD="class: xl66, align: right"]2.8066551[/TD]
[TD="class: xl63, align: right"]2.54824[/TD]
[TD="class: xl63, align: right"]2.556541[/TD]
[TD="class: xl63, align: right"]2.785207[/TD]
[TD="class: xl63, align: right"]2.300211[/TD]
[TD="align: right"]2.161496[/TD]
[TD="class: xl66, align: right"]2.6643963[/TD]
[TD="class: xl63, align: right"]1.641753[/TD]
[TD="class: xl63, align: right"]2.239954[/TD]
[TD="class: xl63, align: right"]1.562361[/TD]
[TD="class: xl63, align: right"]1.682554[/TD]
[TD="align: right"]1.985844[/TD]
[TD="class: xl66, align: right"]2.8280855[/TD]
[TD="class: xl63, align: right"]2.119587[/TD]
[TD="class: xl63, align: right"]2.490479[/TD]
[TD="class: xl63, align: right"]1.780684[/TD]
[TD="class: xl63, align: right"]1.679536[/TD]
[TD="align: right"]1.977059[/TD]
[TD="class: xl66, align: right"]2.8393802[/TD]
[TD="class: xl63, align: right"]1.929261[/TD]
[TD="class: xl63, align: right"]2.479487[/TD]
[TD="class: xl63, align: right"]1.804895[/TD]
[TD="class: xl63, align: right"]1.673621[/TD]
[TD="align: right"]2.045525[/TD]
[TD="class: xl66, align: right"]2.7411508[/TD]
[TD="class: xl63, align: right"]2.486125[/TD]
[TD="class: xl63, align: right"]2.411711[/TD]
[TD="class: xl63, align: right"]1.931177[/TD]
[TD="class: xl63, align: right"]1.918335[/TD]
[TD="align: right"]2.069157[/TD]
[TD="class: xl66, align: right"]2.8605461[/TD]
[TD="class: xl63, align: right"]2.517329[/TD]
[TD="class: xl63, align: right"]2.46032[/TD]
[TD="class: xl63, align: right"]1.837561[/TD]
[TD="class: xl63, align: right"]1.897486[/TD]
[TD="align: right"]2.102621[/TD]
[TD="class: xl66, align: right"]2.9125756[/TD]
[TD="class: xl63, align: right"]2.622658[/TD]
[TD="class: xl63, align: right"]2.469014[/TD]
[TD="class: xl63, align: right"]1.804663[/TD]
[TD="class: xl63, align: right"]1.866855[/TD]
[TD="align: right"]2.10192[/TD]
[TD="class: xl66, align: right"]2.8072717[/TD]
[TD="class: xl63, align: right"]2.426955[/TD]
[TD="class: xl63, align: right"]2.371158[/TD]
[TD="class: xl63, align: right"]1.765089[/TD]
[TD="class: xl63, align: right"]1.799954[/TD]
[TD="align: right"]2.026291[/TD]
[TD="class: xl66, align: right"]2.7447101[/TD]
[TD="class: xl63, align: right"]2.264876[/TD]
[TD="class: xl63, align: right"]2.173995[/TD]
[TD="class: xl63, align: right"]1.656273[/TD]
[TD="class: xl63, align: right"]1.79111[/TD]
[TD="align: right"]1.9964[/TD]
[TD="class: xl66, align: right"]2.8302365[/TD]
[TD="class: xl63, align: right"]2.412752[/TD]
[TD="class: xl63, align: right"]2.309863[/TD]
[TD="class: xl63, align: right"]1.741599[/TD]
[TD="class: xl63, align: right"]1.87927[/TD]
[TD="align: right"]2.086493[/TD]
[TD="class: xl66, align: right"]2.8156909[/TD]
[TD="class: xl63, align: right"]2.639425[/TD]
[TD="class: xl63, align: right"]2.363351[/TD]
[TD="class: xl63, align: right"]1.778991[/TD]
[TD="class: xl63, align: right"]1.9125[/TD]
[TD="align: right"]2.098853[/TD]
[TD="class: xl66, align: right"]2.7576525[/TD]
[TD="class: xl63, align: right"]2.583813[/TD]
[TD="class: xl63, align: right"]2.245098[/TD]
[TD="class: xl63, align: right"]1.53905[/TD]
[TD="class: xl63, align: right"]1.785954[/TD]
[TD="align: right"]2.012423[/TD]
[TD="class: xl66, align: right"]2.7367484[/TD]
[TD="class: xl63, align: right"]2.545393[/TD]
[TD="class: xl63, align: right"]2.210216[/TD]
[TD="class: xl63, align: right"]1.51596[/TD]
[TD="class: xl63, align: right"]1.768283[/TD]
[TD="align: right"]2.039025[/TD]
[TD="class: xl66, align: right"]2.7936911[/TD]
[TD="class: xl63, align: right"]2.575252[/TD]
[TD="class: xl63, align: right"]2.317997[/TD]
[TD="class: xl63, align: right"]1.421082[/TD]
[TD="class: xl63, align: right"]1.594394[/TD]
[TD="align: right"]1.919797[/TD]
[/TABLE]
Due to them also being correlated (See below) is this a serious multicollinearty issue that means my regressio results are insignificant? (see below)
Variable 1 & 2 =0.817846
Variable 2 & 3 = 0.62312
Variable 3 & 4 = 0.842107
Variable 4 & 5 = 0.844526
Variable 5 & 6 = 0.929187
Regression results
[TABLE="width: 499"]
Coefficients
[/td][td]Standard Error
[/td][td]t Stat
[/td][td]P-value
[/td][/tr][tr][td]Intercept
[/td]
[TD="align: right"]7.657114437[/TD]
[TD="align: right"]0.320950828[/TD]
[TD="align: right"]23.85759368[/TD]
[TD="align: right"]1.56203E-67[/TD]
1
[/td]
[TD="align: right"]0.401967263[/TD]
[TD="align: right"]0.201176626[/TD]
[TD="align: right"]1.998081344[/TD]
[TD="align: right"]0.04674538[/TD]
2
[/td]
[TD="align: right"]-0.149847228[/TD]
[TD="align: right"]0.104101885[/TD]
[TD="align: right"]-1.439428579[/TD]
[TD="align: right"]0.15122738[/TD]
3
[/td]
[TD="align: right"]0.848281878[/TD]
[TD="align: right"]0.176776938[/TD]
[TD="align: right"]4.798600358[/TD]
[TD="align: right"]2.69132E-06[/TD]
4
[/td]
[TD="align: right"]-0.396603539[/TD]
[TD="align: right"]0.133370769[/TD]
[TD="align: right"]-2.973691619[/TD]
[TD="align: right"]0.003217662[/TD]
5
[/td]
[TD="align: right"]-0.36444739[/TD]
[TD="align: right"]0.220129689[/TD]
[TD="align: right"]-1.655603071[/TD]
[TD="align: right"]0.099004046[/TD]
6
[/td]
[TD="align: right"]0.078668917[/TD]
[TD="align: right"]0.164035587[/TD]
[TD="align: right"]0.479584453[/TD]
[TD="align: right"]0.631924521[/TD]
7
[/td]
[TD="align: right"]-0.145393714[/TD]
[TD="align: right"]0.086736012[/TD]
[TD="align: right"]-1.676278527[/TD]
[TD="align: right"]0.094881019[/TD]
8
[/td]
[TD="align: right"]1.47872E-11[/TD]
[TD="align: right"]3.26495E-12[/TD]
[TD="align: right"]4.52907424[/TD]
[TD="align: right"]9.01855E-06[/TD]
9
[/td]
[TD="align: right"]-0.005853495[/TD]
[TD="align: right"]0.001110117[/TD]
[TD="align: right"]-5.272863884[/TD]
[TD="align: right"]2.81956E-07[/TD]
[/TABLE]
[TABLE="width: 384"]
[tr]
[TD="width: 64, align: right"][/TD]
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