Secuestro Como Medio De Guerra

The Statistical Package for Social Scientists (SPSS) software, version 21, was used first to explore all scale-form data for normality as a prerequisite of t-testing (Allen & Bennett, 2012). Depending on the nature of the data distributions obtained, most of the hypotheses were addressed using parametric t-tests. If the data violated the normality and symmetry assumptions, non-parametric Mann-Whitney U tests or Wilcoxon Signed Ranks tests were utilised to determine whether the null hypotheses could be rejected.

In the following sections, methods of testing the Bias, Skill, Trait, and overall Scepticism hypotheses are specified in turn.

Trait Range Hypotheses

These hypotheses were tested using participants’ Wrightsman Trust Scale (1991) scores only. When evaluating the Bias sub-scale test results, although the scale centres around a central point of zero, the hypotheses have been framed in such a way as to avoid use of zero as the test value to maintain usefulness of the confidence interval.

Hypothesis 1: Auditors are less trusting than other groups

The null hypothesis, which this research seeks to reject, is that auditors exhibit the same level of trust/distrust bias as QFIs and layperson participants. That is, there is no difference between the belief-cynicism Bias sub-scale scores of auditors and other respondents. The mean level may be neutral (score of 0), or indicative of bias in either continuum direction.

H10 µ Auditor Bias = µ all other participants’ Bias

If the null hypothesis is rejected, differences in mean bias scores would be explored between groups. If Trust is in itself a predictor of Neutrality, as is suggested by use of this same Trust scale in prior research, it would be expected that Auditors are less biased than Laypersons and QFI specialists. The alternative hypotheses are, therefore:

H11 µ Auditor Bias < µ Layperson Bias

H12 µ Auditor Bias < µ QFI Bias

For both alternate hypotheses to be supported, the mean auditor participant score will be lowest, of the three groups, on the belief-cynicism continuum. Although QFIs are expected to be most sceptical of all the groups, their work is predicated on the basis that fraud exists in the information they gather and analyse. Therefore QFIs are expected to take a Presumptive Doubt approach to scepticism, which would equate to a cynicism bias tendency in the Trust/Distrust items within the scepticism scale. This contrasts with the Neutral approach expected of Auditors. Therefore Auditors are expected to be less biased according to the Bias sub-scale.

Hypothesis 2 – Auditors have a more consistent Range of Biases than other groups

The groups’ standard deviations were used to explore for greater consistency of characteristics within the Auditor group than in Non-sophisticated Laypersons. The null hypothesis, which this research seeks to reject, is that the Auditor group members’ Trait characteristics are no more consistent than the Trait characteristics of laypersons:

H20 σAuditor Bias = σ other participants’ Bias

If the null hypothesis is supported, the notion of auditors exhibiting a less diverse range of default trait biases than non-auditors is not supported. The alternative hypothesis, testing for greater consistency of the Neutrality characteristic in the Auditor group, is:

H21 σAuditor Bias < σ Non-sophisticated Layperson Bias

H22 σAuditor Bias < σ QFI Bias

For the null hypothesis to be rejected, the range of auditor participants’ bias scores would be narrower on the belief-cynicism continuum than other participants’ scores, further elucidating the results of mean testing, above.

Skill Hypothesis

The testing in this section is conducted using scores derived from the Skill sub-scale items.

Hypothesis 3: Auditors are more Skilled than Laypersons, but less skilled than QFIs The null hypothesis, which this research seeks to reject, is that auditors exhibit the same level of skill as all other participants. That is, there is no difference between the skill scores of auditors and other respondents.

H30 µ Auditor Skill = µ other participants’ Skill

Given the professional requirements pertaining to Auditors, the alternate hypothesis is therefore:

H31 µ Auditor Skill > µ Non-Sophisticated Layperson Skill

However, the obligations of QFIs with regard to evidence are arguably greater than the requirements for Auditors. Therefore, the second alternative hypothesis is that Auditors’ skill scores would be lower than QFI participants’ skill scores :

H32 µ Auditor Skill < µ QFI Skill

The highest scores indicate greater skill, and the lowest scores indicate lesser skill. Therefore, for the alternate hypothesis 31 to be supported, the mean auditor

participant score would be higher on the skill sub-scale, and for the alternate form of hypothesis 32 to be supported, the mean auditor participant score would be lower

than the mean QFI score.

Scepticism Level Hypotheses

The Scepticism hypotheses are framed in accordance with the composite scoring system, described in section 4.7.2 Formal Scores, which combines the Trait and Skill factors. This score is expressed as a percentage, with the higher scores representing greater scepticism.

Hypothesis 4: Auditors have a more consistent range of Scepticism than other groups

The null hypothesis, which this research seeks to reject, is that there are no identifiable differences in the ranges of overall Scepticism scores, when compared between groups, to support the discussion of between-group Scepticism characteristics. Specifically, there is not enough homogeneity between the composite scores of auditors support meaningful discussion of those scores as distinct from any other respondents.

H40 σ Auditor Scepticism = σNon-Sophisticated Layperson Scepticism

This research posits that if the null hypothesis is rejected, it may be possible to identify discrete differences between groups. To that end, alternative hypotheses explore whether the professional and Sophisticated Layperson groups reflect more consistent scepticism characteristics than Non-sophisticated Laypersons, as follows:

H41 σ QFI Scepticism < σNon-sophisticated Layperson Scepticism

H42 σ Auditor Scepticism < σNon-sophisticated Layperson Scepticism

H43 σ QFI Scepticism < σAuditor Scepticism

H44 σ Sophisticated Layperson Scepticism < σ Non-sophisticated Layperson

Scepticism

Hypothesis 5: Auditors’ Scepticism level is higher than Laypersons’, but lower than QFIs’

The null hypothesis, which this research seeks to reject, is that there are no identifiable differences in overall Scepticism scores between groups. Specifically, there is no difference between the composite scores of auditors and other respondents to suggest different levels of scepticism.

H50 µ Auditor Scepticism= µ Non-Sophisticated Layperson Scepticism

This research posits that if the null hypothesis is rejected, it may be possible to identify discrete differences between groups, and subsequently arrive at levels of scepticism. To that end, alternative hypotheses explore for expected differences, as follows:

H51 µ Sophisticated Layperson Scepticism > µ Non-sophisticated Layperson

Scepticism

H52 µ Auditor > µ Sophisticated Layperson Scepticism

H53 QFIs have higher Scepticism than Auditors

Professional Scepticism Hypothesis

This hypothesis directly addresses RQ 2 by comparing Auditors’ Scepticism scores with a benchmark that denotes the lower limit of a professional scepticism range.

The lower limit of the professional scepticism range is derived from standard deviation statistic calculated using the unadjusted Raw Total scores of QFI participants. As reflected in Hypothesis 4, the QFI scores were expected to cluster quite closely, reflecting professional homogeneity. For the most part, this expectation was observed in the data collected from the sample, however the overall range of results extended across much of the scale, as is demonstrated in Figure 4.1, following.

Figure 4.1 QFI Scepticism Score Distribution Boxplot

The data were then explored to observe for the existence of any outliers which might unduly influence the results. A small, yet distinct, group of results at the trust end of the continuum was subsequently identified. This grouping is highlighted by the blue circle in Figure 4.2.

Figure 4.2 Detrended Normal Q-Q Plot: QFI Scepticism Scores

To utilise the QFI results, without undue effects of the outliers, the data was reduced by approximately 5 percent, so the results then reflected 95.4% of the QFI population, and eliminating outlier bias. This research thereby adopts the procedure used by Staheli et al (1987), who defined “the range of normal” in the same way. The procedure is appropriate for comparison of the QFI sample (n = 41) with the Auditor sample (n = 45) because “[w]ith the two standard deviation cutoff, bias has reached asymptote by a sample size of about 15 and it would seem safe to compare conditions with different numbers of observations as long as each had at least 20” (Miller, 1991, p.912).

The lower limit, or Professional Scepticism Benchmark, was therefore calculated using the following syntax:

Lower PS Limit = (1 – (σ / Raw Scepticism Score range) * 100) * 2

where the standard deviation is 7.426, and the possible Raw Scepticism Score range (of -26 to 42) is 68.

By applying this method, the lower limit of professional scepticism is 100 – 21.8 = 78.2%. Whilst it is noted that future studies, with much greater numbers of participants, may lead to revised standard deviations and thus revised attitude score ranges, for the purposes of this study, the above standard deviations set the boundaries of score ranges as follows:

Table 4.6 Scepticism Score Range Boundaries

Scepticism Attitude Score Range % Established by Participant

Group(s)

Subjectivity 0 – 50 50th percentile representing the nexus of subjectivity and scepticism

Scepticism 51 - 77 Mid-range

Professional Scepticism 78* - 100 2 x QFI standard deviations of the maximum Scepticism score (100%) * rounded

This means that, at the time of testing, subjects with scores of 78% or higher would be considered to have a default attitude of Professional Scepticism; subjects with scores in the range of 51 – 77% would be considered to have an attitude that encompasses scepticism; and subjects with scores of 50% or below would be considered to have a predominantly subjective attitude.

Hypothesis 6: Auditors’ Professional Scepticism is equal to, or higher than, the minimum benchmark for Professional Scepticism.

Hypothesis 6, which predicts that Auditors are professionally sceptical, is expressed as follows:

H6 Auditor Scepticism > 78.15%

The proportion of Auditor group scores which meet or exceed the lower boundary represents, for the purpose of this research, the proportion of Auditors who exhibit indicators of professional scepticism.