Write a critical moral response to only one of the articles (!) from any of the topics covered thus far (that is, topics 1 to 3). Explain your chosen articleâs main thesis and then provide your critique. Be sure to clearly explain your key ideas.
The Royal Society of Canada Expert Panel: End-of-Life Decision Making by
Udo Schuklenk, Johannes J.M. van Delden, Joceyln Downie, Sheila McLean,
Ross Upshur, and Daniel Weinstock
(b) âPhysicianâAssisted Suicide, the Doctrine of Double Effect, and the Ground of
Valueâ by F.M. Kamm
(c) âIs There a Right to Die?â by Leon R. Kass
Sample Solution
ince the mean, median and mode values are very close to each other, it shows the data is symmetrical. The mean for the 196 students is 2.08 with a standard deviation of 1.088. The Trimmed mean value of 2.01 is similar to the mean above. Hence, shows there are no outliers in the data set. In this survey, since the sample size is 196, the Kolmogorov-Smirnov test is used. The p-value of the test is less than 0.001. Hence, the data is not distributed normal. Of the 196 students, 77 (39.3%) very enthusiastic towards start-ups, 52 (26.5%) eager to start-up, 46 (23.5%) open to any opportunity, and 16 (8.2%) to consider start-up option. Out of total, 5 (2.6%) prefer employment. Since the correlation value is within 0.5 to 0.8, start-up intention among degree students is said to correlate âadequatelyâ with at least one other variables in the construct. In this survey, the KMO value is 0.819, which is considered good. Bartlettâs test of sphericity is used to analyse whether the correlation matrix is an identity matrix. Identity matrix can be ruled out if the p-value of the test is less than 0.05 (Karuthan and Krishna, 2009). In this model, since the p-value is less than 0.001, the researcher proceeds with factor analysis. Since the researcher wanted to study the underlying construct among the six variables: Curiosity, Interest, Consideration, Preparation, Setting Up and Start-up Timing. This is a single underlying concept; therefore, it is called the âStart-up Intent Structureâ. Since the âStart-up Intent Structureâ varies from person to person, it is a variable too. However, it cannot be measured by physical means. Hence, it is called a latent variable or just factor. The model for âStart-up Intent Structureâ is given in Figure 4. In Figure 4, one can visualize six simultaneous regression functions: Curiosity, Interest, Consideration, Preparation, Setting Up and Start-up Timing as the dependents and âStart-up Intent Structureâ as the independent. In the table above, since there are 6 variables in this analysis, 6 components (or factors) are listed in the first column. The respective eigen values and percent of variance explained are provided in the next two columns. For Factor 1, the eigen value is 3.109 and the variance is 51.811% of the total variance. For factor 3, 4,5 and 6 the eigen value is less than the default value of 1. In the same table, under âExtraction Sums of Squared Loadingsâ, only two factors are listed, corresponding to the factors for which the eigen values is more than 1. Based on the cumulative % column, these factors explain 68.792% of the total variance in the 6 original variables. According to Karuthan and Krishna, (2009) established that, in social sciences, at least 50% of the total variance in >
ince the mean, median and mode values are very close to each other, it shows the data is symmetrical. The mean for the 196 students is 2.08 with a standard deviation of 1.088. The Trimmed mean value of 2.01 is similar to the mean above. Hence, shows there are no outliers in the data set. In this survey, since the sample size is 196, the Kolmogorov-Smirnov test is used. The p-value of the test is less than 0.001. Hence, the data is not distributed normal. Of the 196 students, 77 (39.3%) very enthusiastic towards start-ups, 52 (26.5%) eager to start-up, 46 (23.5%) open to any opportunity, and 16 (8.2%) to consider start-up option. Out of total, 5 (2.6%) prefer employment. Since the correlation value is within 0.5 to 0.8, start-up intention among degree students is said to correlate âadequatelyâ with at least one other variables in the construct. In this survey, the KMO value is 0.819, which is considered good. Bartlettâs test of sphericity is used to analyse whether the correlation matrix is an identity matrix. Identity matrix can be ruled out if the p-value of the test is less than 0.05 (Karuthan and Krishna, 2009). In this model, since the p-value is less than 0.001, the researcher proceeds with factor analysis. Since the researcher wanted to study the underlying construct among the six variables: Curiosity, Interest, Consideration, Preparation, Setting Up and Start-up Timing. This is a single underlying concept; therefore, it is called the âStart-up Intent Structureâ. Since the âStart-up Intent Structureâ varies from person to person, it is a variable too. However, it cannot be measured by physical means. Hence, it is called a latent variable or just factor. The model for âStart-up Intent Structureâ is given in Figure 4. In Figure 4, one can visualize six simultaneous regression functions: Curiosity, Interest, Consideration, Preparation, Setting Up and Start-up Timing as the dependents and âStart-up Intent Structureâ as the independent. In the table above, since there are 6 variables in this analysis, 6 components (or factors) are listed in the first column. The respective eigen values and percent of variance explained are provided in the next two columns. For Factor 1, the eigen value is 3.109 and the variance is 51.811% of the total variance. For factor 3, 4,5 and 6 the eigen value is less than the default value of 1. In the same table, under âExtraction Sums of Squared Loadingsâ, only two factors are listed, corresponding to the factors for which the eigen values is more than 1. Based on the cumulative % column, these factors explain 68.792% of the total variance in the 6 original variables. According to Karuthan and Krishna, (2009) established that, in social sciences, at least 50% of the total variance in >
