You can use your regression analysis results to make which of the following conclusions? (Select all that apply) The financial loss incurred to organizations is significantly higher for M...


You can use your regression analysis results to make which of the following conclusions? (Select all that apply)<br>The financial loss incurred to organizations is significantly higher for<br>M authentication credentials than financial data<br>V identity than fınancial data<br>V financial than personal data<br>V health than fınancial data<br>V intellectual property than identity data<br>O identity than health data<br>

Extracted text: You can use your regression analysis results to make which of the following conclusions? (Select all that apply) The financial loss incurred to organizations is significantly higher for M authentication credentials than financial data V identity than fınancial data V financial than personal data V health than fınancial data V intellectual property than identity data O identity than health data
Coefficients:<br>Estimate std. Error t value Pr (>|t|)<br>0. 6403 83.006<br>0. 9213<br>0. 8673<br>(Intercept)<br>data_typeAuthentication_Credentials_Vs_Identity -8. 0170<br>data_typeFinancial_vs_Identity<br>data_typeHealth_vs_Identity<br>data_typeIntellectual_Property_vs_Identity<br>data_typePersonal_vs_Identity<br>< 2e-16 e se se<br>< 2e-16 e se se<br>< 2e-16 * se se<br>< 2e-16<br>5.726 1.79e-08 ** *<br>< 2e-16 *e se *<br>53.1464<br>-8.702<br>-9. 665<br>9. 941<br>-8. 3822<br>12.4783<br>1.2553<br>0. 8936<br>0. 9158 -11.294<br>5. 1165<br>-10. 3434<br>signif. codes:<br>O * ***' 0.001 ***' 0.01 *' 0.05 .' 0.1 '1<br>Residual standard error: 6.108 on 494 degrees of freedom<br>Multiple R-squar ed: 0. 5735,<br>F-statistic: 132. 8 on 5 and 494 DF, p-value: < 2.2e-16<br>Adjusted R-squared: 0. 5691<br>> round(tapply(lab8. datasfin_loss, lab8. datasdata_type, mean, na.rm = TRUE), 3)<br>Нealth<br>65. 625<br>Authentication Credentials<br>Financial<br>Intellectual Property<br>58.263<br>Identity<br>44.764<br>45.129<br>Personal<br>53.146<br>42.803<br>

Extracted text: Coefficients: Estimate std. Error t value Pr (>|t|) 0. 6403 83.006 0. 9213 0. 8673 (Intercept) data_typeAuthentication_Credentials_Vs_Identity -8. 0170 data_typeFinancial_vs_Identity data_typeHealth_vs_Identity data_typeIntellectual_Property_vs_Identity data_typePersonal_vs_Identity < 2e-16="" e="" se="" se="">< 2e-16="" e="" se="" se="">< 2e-16="" *="" se="" se="">< 2e-16="" 5.726="" 1.79e-08="" **="" *="">< 2e-16="" *e="" se="" *="" 53.1464="" -8.702="" -9.="" 665="" 9.="" 941="" -8.="" 3822="" 12.4783="" 1.2553="" 0.="" 8936="" 0.="" 9158="" -11.294="" 5.="" 1165="" -10.="" 3434="" signif.="" codes:="" o="" *="" ***'="" 0.001="" ***'="" 0.01="" *'="" 0.05="" .'="" 0.1="" '1="" residual="" standard="" error:="" 6.108="" on="" 494="" degrees="" of="" freedom="" multiple="" r-squar="" ed:="" 0.="" 5735,="" f-statistic:="" 132.="" 8="" on="" 5="" and="" 494="" df,="" p-value:="">< 2.2e-16="" adjusted="" r-squared:="" 0.="" 5691=""> round(tapply(lab8. datasfin_loss, lab8. datasdata_type, mean, na.rm = TRUE), 3) Нealth 65. 625 Authentication Credentials Financial Intellectual Property 58.263 Identity 44.764 45.129 Personal 53.146 42.803

Jun 08, 2022
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