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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 V authentication credentials than financial data V identity than financial data A financial than personal data O health than financial data V intellectual property than identity data O identity than health data

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 V authentication credentials than financial data V identity than financial data A financial than personal data O health than financial data V intellectual property than identity data O identity than health data

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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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
Transcribed Image 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: 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
Transcribed Image 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
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