This document discusses audit sampling methods. It defines audit sampling as selecting a subset of a population for the purpose of making inferences about the whole population. Audit sampling helps auditors efficiently gather evidence and detect errors or misstatements. The document discusses factors that affect sample size, different sampling methods like simple random sampling and stratified random sampling, and the purposes of test of controls and substantive testing. It also compares statistical and non-statistical sampling methods.
I hope it will be simplified and powerful presentation for all. Rather than adding large texts, here you can find image and graphical presentation.
Happy Reading
I hope it will be simplified and powerful presentation for all. Rather than adding large texts, here you can find image and graphical presentation.
Happy Reading
Presentation by Jose Viegas Ribeiro on internal control and internal audit given at the workshop on Improving outputs of internal control units through self-assessment co-organised by SIGMA with the Ministry of Finance of Jordan, Amman 6 November 2014
Presentation by Jose Viegas Ribeiro on internal control and internal audit given at the workshop on Improving outputs of internal control units through self-assessment co-organised by SIGMA with the Ministry of Finance of Jordan, Amman 6 November 2014
The 7 Keys to an Effective Audit ProgrammeCraig Thornton
Internal auditing is a key part of any compliance system, be it health & safety, quality management, food safety or environmental management.
In this webinar, Craig Thornton, Mango’s Chief Support Officer was joined by one of the region’s leading internal auditor trainers – Michael Voss.
During the webinar, Michael presented his 7 keys to running an effective internal audit programme.
Michael is a seasoned compliance professional, a Certified Quality Manager and past Development Director of the New Zealand Organisation for Quality (NZOQ).
Would you like to watch the recording of this webinar? Copy and paste the following link into your web browser:
http://www.mangolive.com/blog-mango/internal-audit-programme-7-keys-webinar-recording-1
Audit Programme is prepared before the actual auditing procedure starts. it is essential for Auditors. There are numerous things that need to be considered while making an audit programme.
Certified Specialist Business Intelligence (.docxdurantheseldine
Certified Specialist Business
Intelligence (CSBI) Reflection
Part 5 of 6
CSBI Course 5: Business Intelligence and Analytical and Quantitative Skills
● Thinking about the Basics
● The Basic Elements of Experimental Design
● Sampling
● Common Mistakes in Analysis
● Opportunities and Problems to Solve
● The Low Severity Level ED (SL5P) Case Setup as an Example of BI Work
● Meaningful Analytic Structures
Analysis and Statistics
A key aspect of the work of the BI/Analytics consultant is analysis. Analysis can be defined as
how the data is turned into information. Information is the outcome when the data is analyzed
correctly.
Rigorous analysis is having the best chance of creating the sharpest picture of what the data
might reveal and is the product of proper application of statistics and experimental design.
Statistics encompasses a complex and detailed series of disciplines. Statistical concepts are
foundational to all descriptive, predictive and prescriptive analytic applications. However, the
application of simple descriptive statistical calculations yields a great deal of usable information
for transformational decision-making. The value of the information is amplified when using these
same simple statistics within the context of a well-designed experiment.
This module is not designed to teach one statistic. It is designed to place statistical work within
the appropriate context so that it can be leveraged most effectively in driving organizational
performance..
An important review of the basic knowledge for work with descriptive and inferential statistics.
The Basic Elements of Experimental Design
Analytic tools also can provide an enhanced ability to conduct experiments. More than just
allowing analysis of output of activities or processes, experiments can be performed on
processes and the output of processes. Experimenting on processes is a movement beyond
the traditional r.
A sample design is a definite plan for obtaining a sample from a given population. It refers to the technique or the procedure the researcher would adopt in selecting items for the sample. Sample design may as well lay down the number of items to be included in the sample i.e., the size of the sample. Sample design is determined before data are collected. There are many sample designs from which a researcher can choose. Some designs are relatively more precise and easier to apply than others. Researcher must select/prepare a sample design which should be reliable and appropriate for his research study.
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NURLIANA BINTI MOHD RAMLI
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FAEQAH BINTI MOHD NORMAN
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2. Nature of Audit Sampling
The process of using auditing procedures to test less
than 100 percent of various items in a company's
account balance such that each unit may have an
equal opportunity of being selected.
3. Define Audit Sampling
Refer to Definition on ISA 530 for Audit Sampling
Process of selecting a subset of a population of items
for the purpose of making inferences to whole
population.
The process of using auditing procedures to less than
100 per cent of various items in a company's account
balance such that each unit may have an equal
opportunity of being selected.
It is used to conduct test of control and substantive
test.
4. Purpose
Audit sampling help auditors on doing their audit
work at a given period of time. It is possible for
auditor to make details examination on all the items
being examined.
To gather or get the evidences from the audit
procedures being performed. Sampling is only the
method (efficient) or sources of the evidence.
To detect error and any materially misstatements.
To show or a s a prove that the auditor have done
their work.
5. select the audit samples
1) Simple random sampling – cases are selected in a
completely random way which ensures that each case
has an equal chance of being selected e.g. by using a
computerised random number list or drawing random
numbers out of a hat.
2) Stratified random sampling – The population is
divided into groups depending on characteristics they
share in common e.g. diagnosis, age etc. A random
sample is then selected from each group.
6. Know to select the audit samples
3) Interval random sampling – The population is arranged
in order and the first case is then selected at random. The
rest of the cases are then selected at pre-defined intervals,
e.g. every 3rd or every 5th patient.
4) Rapid-cycle sampling – This method can be used where
you know there may be a problem and you want to obtain
results as quickly as possible. Here you carry out the audit
with a relatively small sample, implement changes and
then re-audit using another small sample to determine
whether improvements have been made. This method
uses lots of small data sets to monitor care and can make
the change cycle quicker to complete.
7. factors affecting the sample size.
There are several factors which must be considered when deciding
upon the sample size.
Population Size
This is only relevant in very small populations.
Level of confidence
Even a 100% sample will not give complete assurance .Auditors work
to level of confidence which can be expressed precisely .For
example ,a 5% confidence level means that there is 19 chances out of
20 that the sample is representative of the population as a whole.
Precision
Clearly the level of confidence and the precision interval are related
,in that for a given sample size higher confidence can be expressed in
a wider precision interval and vice versa.
8. Risk
Risk is a highly important concept in modern auditing and in high risk
areas a large sample will be desirable because high confidence levels and
narrow precision intervals are required.
Materiality
This is really a subset of risk. Materiality is fundamental to modern
auditing and with all populations being sample, materiality should be
considered in fixing the sample size.
Subjective factors
This is most important and yet difficult area of consideration .The
auditor expects to gain audit evidence about a population from a
sample.
Expected error/deviation rate
The theory requires that the samples size required is a function of the
error .This is only known after the results have been evaluated .However
an estimate based on previous experience and knowledge of other
factors may give a good indication
9. Audit samples selection method
a)All items selection
b)Specific selection
CHARACTERISTICS OF SAMPLE:
Random
A random sample is one where each item of the population has an
equal or specified chance of being selected. Statistical inferences may
not be valid unless the sample is random.
Representatives
The sample should be representative of the differing items in the
whole population .For example ,it should contains a similar
proportion of high and low value item to the population.
10. Protective
Protective that is of the auditor. More intensive auditing should occur on
high value items known to be high risk.
Unpredictable
Client should not be able to know or guess which items will be examined.
Several METHODS available to an auditor for selecting items: (Should
have 7 techniques for audit sampling and 3 under non-statistical while 4
under statistical method of selection)
Haphazard
Simply choosing items subjectively but avoiding bias. Bias might come in
by tendency to favor items in a particular location or in an accessible file for
conversely in picking items because they appear unusual.
Simple random
All items in population have a number .Numbers are selected by a means
which gives every number an equal chance of being selected.
11. Stratified
Dividing the population into sub population and is useful when parts
of the population have higher than normal risk. Frequently high value
items form a small part or the population and 100% checked and the
remainder are sampled.
Cluster sampling
This is useful when data is maintained in clusters as wage records are
kept in weeks or sales invoice in months. The idea is to select a cluster
randomly and then to examine all the items in the cluster chosen.
Random systematics
Involves making a random start and then taking every nth item
thereafter. This is commonly use method which saves the work of
computing random numbers.
Multi stage sampling
This method is appropriate when data is stored in two or more levels.
For example stock in a retail chain of shops. The first stage is to
randomly select a sample of shops and the second stage is to randomly
select stock items from the chosen shops.
12.
13. Test of control
Purpose of test of controls is determine the system’s
internal controls comply with the stated policies, plans,
laws and regulations.
Auditors evaluate the design of controls and determine if
the controls are in operation. They must also obtain
evidence whether the controls are operating effectively.
Test of controls to establish to detect material error and
whether the internal controls were operating effectively
through out the period being audited.
Normally test of control provide information as to the rate
of error in terms of control failure rather than to enable
direct extrapolation in term of monetary errors in the
financial statements.
14. Substantive test
Purpose of substantive test is provide audit evidence to
the completeness, accuracy and validity of the
information contained in the financial statements.
Determine their accuracy and to draw conclusions about
the materiality of the error amounts in the accounts.
The objective is to obtain reliable confidence limits, such
as confidence limits with actual confidence levels never
less than their nominal levels which are not conservative.
Example the total error amount should not be very much
greater than the true error amount with sample sizes that
are not too large for practical audit applications.
15.
16. Statistical vs. Non-statistical
Statistical Non-statistical
Through the application of Auditor does not quantify
mathematical rules. sampling risk.
It allows the quantification Instead, those sample items that
(measurement) of sampling auditor believes will provide the
most useful information in the
risk in planning the sample
circumstances are selected.
and evaluate the results.
Conclusions are reached about
Example: Statistical result at populations on judgmental
a 95% confidence level basis. Thus selection of
provides a 5% sampling risk) nonprobability samples is often
termed judgmental sampling
17. Advantages Disadvantages
Very accurate. Inadequacy of the samples.
Economical in nature. Chances for bias.
Very reliable. Problems of accuracy.
High suitability ratio towards Difficulty of getting the
the different surveys. representative sample.
Takes less time. Untrained manpower.
In cases, when the universe Absence of the informants.
is very large, then the Chances of committing the
sampling method is the only errors in sampling.
practical method for
collecting the data.
18. Probability Sampling Non-Probability Sampling
Advantages
Advantages More flexible
Less prone to bias
Less costly
Allows estimation of magnitude Less time-consuming
of sampling error, from which Judgmentally representative
you can determine the
statistical significance of samples may be preferred when
changes/differences in small numbers of elements are to
indicators be chosen
Disadvantages
Disadvantages Greater risk of bias
Requires that you have a list of
May not be possible to generalize
all sample elements
to program target population
More time-consuming Subjectivity can make it difficult
More costly to
No advantage when small measure changes in indicators
numbers over time
of elements are to be chosen No way to assess precision or
reliability of data
19.
20. Type I and Type II errors
Type I and Type II errors are the two types of decision
errors an auditor can make when deciding that
sample evidence supports or does not support a test
of controls or a substantive procedures based on a
sampling application.
In reference to a test of controls Type I and Type II
errors are:
Risk of incorrect rejection (Type I): the risk that the
assessed level of control risk based on the sample is
greater than the true operating effectiveness of the
control. Also commonly referred to as the risk of
assessing control risk too high or the risk of under-
reliance.
21. Risk of incorrect acceptance (Type II): the risk that
the assessed level of control risk based on the sample
is less than the true operating effectiveness of the
control. Also commonly referred as the risk of
assessing control risk too low or the risk of over-
reliance.
In reference to substantive tests Type I and Type II
errors as follows:
Risk of incorrect rejection (Type I): the risk that the
sample supports the conclusion that the recorded
account balance is materially misstated when it is not
materially misstated.
22. Risk of incorrect acceptance (Type II): the risk that
the sample supports the conclusion that the recorded
account balance is not materially misstated when it is
materially misstated.
The risk of incorrect rejection relates to the efficiency
of the audit because such errors can result in the
auditor's conducting more audit work than
necessary in order to reach the correct conclusion.
The risk of incorrect acceptance relates to the
effectiveness of the audit because such errors can
result in the auditor failing to detect a material
misstatement in the financial statements. This
can lead to litigation against the auditor by the
parties who relied on the financial statements.
23. EXPECTED ERROR IN THE
POPULATION
a) Tolerable error
Tolerable error is the maximum error in the population that auditors
would be willing to accept and still conclude that the result from the
sample has achieved the audit objective. Tolerable error is considered
during the planning stage and, for substantive procedures, is related
to the auditors' judgement about materiality. The smaller the
tolerable error, the greater the sample size needs to be.
In tests of control, the tolerable error is the maximum rate of
deviation from a prescribed control procedure that auditors would be
willing to accept and still conclude that the preliminary assessment of
control risk is valid. In substantive procedures, the tolerable error is
the maximum monetary error in an account balance or a class of
transactions that auditors would be willing to accept so that when the
results of all audit procedures are considered, auditors are able to
conclude, with reasonable assurance, that the financial statements are
not materially misstated.
24. b) Expected error
If auditors expect errors to be present in the population, a larger
sample than when no error is expected ordinarily needs to be
examined to conclude that the actual error in the population is not
greater than the planned tolerable error. Smaller sample sizes are
justified when the population is expected to be error free.
In determining the expected error in a population, auditors would
consider such matters as error levels identified in previous audits,
changes in the entity's procedures and evidence available from other
procedures, including tests of control.
25. NATURE OF ERROR
Auditors may observe that many have a common feature,
for example type of transaction, location, product line or
period of time.
In such circumstances, auditors may decide to identify all
items in the population which possess the common
feature, thereby producing a subpopulation, and extend
audit procedures in this area.
Auditors would then perform a separate analysis based on
the items examined for each sub-population.
26. What if the auditor finds there is
an error?
If material error exists in the accounting records or
financial statements, it must be the result of one or more
of the following :
a) A large number of small error – should be detected by
representative sampling.
b)Few large error – should be detected by selecting
sampling.
c) A combination of (a) and (b) – both sample types will be
needed
27. i. Representative sample
Drawn at random from a population. A sample should be large
enough to allow auditors to draw valid inferences about the whole
population. Auditors test of control will always make use of
representative sampling may also be used for substantive testing.
b) Selecting samples
focus on particular items in the population. These are usually the
large and unusual items, transactions or balances that are large
enough to give a materials error if incorrect, or which are worthy of
investigation.
28. ACTION TAKEN WHEN ERROR IS
FOUND
Auditors project the error results of the sample to the population from
which the sample was selected in order to form a conclusion about
the possible level of error in the population as a whole.
The projection of the error results of the sample to the population as a
whole involves estimating the probable error in the population by
extrapolating the errors found in the sample.
When projecting error results, auditors would ensure that the method
of projection is consistent with the method used to select the
sampling unit.
This is in addition to considering the qualitative aspects of the errors
found. When the population has been divided into sub-populations,
the projection of errors is done separately for each sub-population and
the results are combined.
29. Auditors would consider whether errors in the population might
exceed the tolerable error. To accomplish this, auditors compare the
projected population error to the tolerable error taking into account
the results of other audit procedures relevant to the specific control or
financial statement assertion.
The projected population error used for this comparison in the case of
substantive procedures is net of adjustments made by the entity.
When the projected error exceeds tolerable error, auditors re-assess
the sampling risk and if that risk is unacceptable, consider extending
the audit procedure or performing alternative audit procedures, either
of which may result in them proposing an adjustment to the financial
statements.