Audit Sampling Using Statistical Methods Presented By: Abhishek Agrawal AUDIT SAMPLING • Application of an audit procedure to less than 100% of the items in a population – Account balance – Class of transactions • Examination “on a test basis” • Key: Sample is intended to be representative of the population. APIPA 2009 2 SAMPLING RISK • Possibility that the sample is NOT representative of the population • As a result‚ auditor will reach WRONG conclusion • Decision errors – Type
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Session 5 Topic: Sampling Theory/ Techniques and Discussions Project Brief ◦ Expectations and deliverables (Deadline October 1‚ 2010- EOD) Sampling basics ◦ Fundamental Issues ◦ Errors Sampling techniques ◦ Probabilistic ◦ Non-probabilistic Discussions © Krishanu Rakshit‚ IIM Calcutta 28 September‚ 2010 2 When do we use a ‘sample’ When do we use a census (population) Sampling errors ◦ Difference between a measure from sample and the measure
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historical movie taglines. This follow-up analysis considered movie taglines between 1979 and 2014 which relates to my own personal “movie watching years”. The goal was to employ additional strategies including stemming and looking at various combinations of clustering algorithms‚ pairwise distance metrics and words extracted to create the terms by document matrix to understand impact on cluster efficiency. Ultimately looking to answer the question of how movies classes may have changed over the
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11 (i) SAMPLE DESIGN AND SAMPLING PROCESS Introduction Samples are parts or potions of population. A population is the specified total of study elements. A target population‚ also known as the universe‚ includes all the members of a real or hypothetical set of people‚ event or objects to which we wish to generalize the results of our research. A study population is that aggregation of elements from which the sample is actually selected. Sampling means selecting a given number
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SAMPLING TECHINIQUE PROBABILITY SAMPLING Having chosen a suitable sampling frame and established the actual sample size required‚ you need to select the most appropriate sampling technique to obtain a representative sample. The basic principle of probability sampling is that elements are randomly selected in a population. This ensures that bias is avoided in the identification of the elements. It is an efficient method of selecting elements which may have varied characteristics‚ as the process
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Simple random sample (SRS) In statistics‚ a simple random sample from a population is a sample chosen randomly‚ so that each possible sample has the same probability of being chosen. One consequence is that each member of the population has the same probability of being chosen as any other. In small populations such sampling is typically done "without replacement"‚ i.e.‚ one deliberately avoids choosing any member of the population more than once. Although simple random sampling can be conducted
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Simple Random Sampling is done when every individual subject in the population has an equal chance of being selected for the sample‚ without any bias (Explorable). For example‚ if a researcher wants to represent the population as a whole‚ they can pick random numbers or names out a hat or use a program to randomly choose names so the information is not biased. Stratified Sampling is performed by‚ dividing the population into at least two (or more) groups or sections‚ which share certain characteristics
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1. Which of the following is a basic principle that applies to both internal and external devices? A) when connecting a faster device to a slower port‚ the port adapts to the speed of the device B) if you have multiple devices to install‚ it’s best to install them at the same time C) for most installations‚ install the device first‚ then the device driver D) some devices don’t require a software component for them to work properly 2. What happens when a problem occurs while Windows 7 is installing
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Purposive sampling Purposive sampling‚ also known as judgmental‚ selective or subjective sampling‚ is a type of non-probability sampling technique. Non-probability sampling focuses on sampling techniques where the units that are investigated are based on the judgement of the researcher. Purposive sampling explained Purposive sampling represents a group of different non-probability sampling techniques. Also known as judgmental‚ selectiveor subjective sampling‚ purposive sampling relies on
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Sampling Methodologies Population: Population is defined as including all items with the characteristic one wishes to understand. Because there is seldom enough time or money to gather information from everyone or everything in a population‚ the goal is to find a representative sample (or subset) of that population. For example‚ a researcher might study the success rate of a new ’quit smoking’ program on a sample group of 50 patients‚ in order to predict the effects of the program if it were
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