Decision to use Sampling

According to normally accepted standards of auditing, an auditor need not examine each and every item of a large sized database. He can go for sampling, which saves considerable cost and time without sacrificing quality. Under sampling, an auditor establishes proper confidence limits and selects a sample, which can be a true representative of the entire population from which it is chosen. Sampling enables the auditor to express his opinion on the financial information without examining the entire evidence. But such sampling can be adopted for low risk-items forming large size population. In case of high risk items like large dollar value transactions, an auditor would prefer to examine all items of the entire population. Similar is the case with high risk items with certain attributes like overdue accounts receivable or slow moving inventory, where the auditor chooses to examine item by item of the population. If there is an opinion that there may be some approximation in audit opinion due to sampling, it is not totally correct. Even if one goes for 100% testing without any sampling, non-sampling errors cannot be avoided. In fact, many times sampling lessens the impact of non-sampling errors.

There are certain considerations to be followed in applying sampling techniques. Proper care should be exercised in sample selection, so that it is a true representative of the population from which it is selected. Otherwise it is not possible to ascribe its characteristics to the entire population. The sample selection should also be random so that the client does not manipulate the characteristics of the sample and thereby those of the population itself. Level of assurance that is confidence that the population will be sufficiently represented by the sample and the precision will influence the sample size. If there are any errors in the sample, they should not be brushed as one-time phenomena but should be accepted as being present in the entire population.

In between statistical and non-statistical or judgemental sampling, statistical sampling methods are considered superior because they are based on mathematical principles and are more objective. All sampling approaches have the risk of making incorrect projections. But statistical sampling enables the auditor to measure and reduce such risk. It also helps in reducing errors in projections due to non-sampling mistakes.

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Nature of Data used in Qualitative Research

1. Qualitative Research & Methods employed

            Qualitative research is a scientific research which seeks to understand a given research problem or topic from the perspectives of the local population it involves.

             The three most common qualitative methods are participant observation, in-depth interviews, and focus groups.
(a)Participant observation is appropriate for collecting data on naturally occurring behaviors in their usual contexts.
(b) In-depth interviews are appropriate for collecting data on individuals’ personal histories, perspectives and experiences, particularly when sensitive topics are being explored.
(c)Focus groups are effective in eliciting data on the cultural norms of a group and in generating broad overviews of issues of concern to the cultural groups or subgroups represented.

These three methods generate data by way of field notes, audio (and sometimes video) recordings, and transcripts.
                                      
                                         2. Trustworthiness and Researcher Bias
          
                Trustworthiness is an essential component of qualitative research. Findings should reflect the reality of the experience. Providing participants with the opportunity to review the researchers interpretation of the data (Koch, 1994 ) can identify this trustworthiness or credibility. Another strategy used to maximize the trustworthiness of the findings is to undertake member checks . This involves taking analysis back to the participants to ensure it represents reasonable account of their experience (Parahoo, 1997) thus, minimizing researcher bias In this way biased results can be avoided and a reliable description of a given phenomena provided (Beck, 1994). However, research by Mayes & Pope (1995) & Clarke (1999) argue that reliability is enhanced when more than one skilled qualitative researcher is involved in the analysis process. This is seems a sound suggestion.
                                        
                                                             3. Confirmability
                Patton says that objectivity in research suffers because the intrusion of the researcher’s biases is inevitable (Patton, 1990). The concept of confirmability is the qualitative investigator’s comparable concern to objectivity.  Here steps must be taken to help ensure as far as possible that the work’s findings are the result of the experiences and ideas of the informants, rather than the reflections and ideas of the researcher. The method of triangulation can be used to reduce the bias of the investigator and promote confirmability. Miles and Huberman(1994)consider that a key criterion for confirmability is the extent to which the researcher admits his or her own.
                                       
                                                              4. Coding
           An objectivist approach treats code words as “condensed representation of the facts described in the data” (Seidel & Kelle, 1995).It should be ensured that (1.) the codes are adequate surrogates for the text they identify (2.) the text is reducible to the codes and (3.) it is appropriate to analyze relationships among codes. If these conditions are not met then an analysis of relationships among code words is risky business. (Seidel, 1991)
  
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