1 Sampling Methods When surveying, for any purpose, it is important to recognise that the results are only as representative as the survey subjects (the sample), and as such much academic research has been performed in to techniques for selection, broadly placing them in one of two categories – probability sampling and non-probability sampling. In short, with probability sampling the participants are selected by chance. There are dozens of methods of selecting members, using a variety of mathematical techniques, but the key is that each subject has a random, calculable chance of being selected. There is no human intervention involved in the selection. Method Characteristics Simple (random) Sampling The sample is selected entirely at random Stratified The population is first divided in to exclusive subgroups based on some predetermined criteria (e. g.

location), then samples are selected at random Proportionate Stratified As above, but a smaller group that would otherwise not provide statistically valid results may be over sampled then the results weighted to correct for this. For example, if a particular group is too small to provide a statistically significant sample, more members of that group would be sampled Clustering The starting point for the sample is randomized, then assumes that the sample at that point is representative of the region. For example, selecting a street corner, interviewing the first 10 people, and assuming that they are representative of the area Table 2 – Probability Sampling Methods Non-probability samples, however, contain an element of human bias in the sample selection. Again, there are various methods for the selection, the most common of which are: Method Characteristics Quota Respondents are preselected to ensure that the sample is representative Purposive Subjects are selected as they have some specific characteristic, for example, hold a certain position or job type Convenience The sample is selected by availability Snowballing Contacts provide information about other potential respondents Self-selection Respondents volunteer themselves for selection Judgement An “expert” uses his or her judgement to nominate people for sample Table 3 – Non-probability Sampling Methods Most samples use a combination of sample selection methods. For example, quota sampling is often used to ensure that a random sample is actually representative of the population. 2 Survey types There are three basic surveying techniques that are suitable for consideration in the project: o Interviews Telephone Self Administered Survey 2.

### The Research paper on Random Sampling Method

Samples and Sampling The term “sampling,” as used in research, refers to the process of selecting the individuals who will participate (e.g., be observed or questioned) in a research study. A sample is any part of a population of individuals on whom information is obtained. It may, for a variety of reasons, be different from the sample originally selected. Samples and Populations The ...

1 Interview (face to face) This category includes in-depth interviews, focus groups and projective methods (such as word association tests) which are not suitable for use in this project. There are several distinct advantages to this type of survey, such as: o Response rates tend to be higher than other methods o Ability to reassure the subject about their response so Questions can be clarified o The interviewer can supplement the data with observation (for example, other feedback) o Longer and more complex interviews can be performed (although this is not recommended here) o Visual aids, such as queue cards, can be use do Response bias can be largely removed from the results if respondents see follow up interviews as an essential part of the implementation process However, there are disadvantages: o It is often costly to meet each subject, even in a group session. Travel costs and time must be taken in to account. o There is much more significant chance of interviewer bias being introduced to the sample, for example, by tone of voice or interpretation of response o Although response rates are higher, as people are reluctant to appear “rude” the response may include some level of bias here 2.

### The Essay on The Effects On Population Size And Growth In Australia

The Effects on Population Size and Growth in Australia Abstract The present prospective observational study is aimed to assess the effects of the major factors like births, deaths, and overseas and interstate migration on population size and growth in Australia. The study is based on the data on population change in Australia for the years 1996-1997 and 2005-2006 from the Australian Bureau of ...

2 Telephone Telephone interviewing, especially within a single organisation such as a company, represents a highly convenient, accurate sampling technique o Telephone interviews tend to have less interviewer bias than face to face interview so People are more inclined to say what they think as it is more anonymous o Cheaper than interviewing, but more expensive than self administered tests. The cost per response required must be evaluated. o Shorter – max 15 minute so Simpler questions – no cue card so Some response bias, although can be mitigate do Generally higher response rate than self administered tests 2. 3 Self administered survey that the respondent completes themselves, either as a paper form, or through the internet, is a self administered survey. o Anonymity is a major selling point of a self administered survey – respondents do not feel the pressure to be polite o The respondent can complete the survey at their convenience o They are cheap – especially in clients where there is an established too lo Uptake is low – people do not tend to respond as there is no human contact requesting ito People get bored of taking self assessment surveys. Over surveying further lowers the response rate for subsequent contact so The least likely to produce any accurate results, because: o there is a high degree of response bias – typically respondents are those with a problem or complaint o The respondent may only read part of the question before answering 3 Sample Sizes Sample size determination is important as too large a sample wastes time and money, too small a sample and the results will not be statistically valid – the degree to which a sample satisfies this constraint is indicated by: o The Margin of Error – this tells us what percentage of variance can be expected in the sample – it reveals the errors inherent in the sample data.

A 5% margin of error is generally acceptable. o The Level of Confidence indicates the confidence we have in the data. A 95% level of confidence is usually acceptable. Together, this tells us that, if we were to conduct the same survey 100 times, the data would be within 5% of the percentage reported in 95 out of the 100 surveys. The sample size required to obtain this level of confidence increases as the population decreases: Population Size Sample size Proportion of Population Margin of Error 50 45 90 % 5%100 80 80 % 5%1000 278 28 % 5%5000 357 7 % 5%7500 366 5 % 5%Table 4 – Required sample sizes for statistical significance As is evident, as the population increases, the proportionate sample size decreases, subject to the law of diminishing returns – there is little variation between the size of sample required when the population is 20, 000 and that from a population of 100, 000 (6 fewer responses are needed).

### The Essay on Marketing Research Sample Size Calculator

Sample Size Calculator Terms: Confidence Interval & Confidence Level The confidence interval (also called margin of error) is the plus-or-minus figure usually reported in newspaper ... three factors that determine the size of the confidence interval for a given confidence level: * Sample size * Percentage * Population size Sample Size The larger your sample size, the more sure you ...

Usually, a sample size of at least thirty is required, although there are test that can be performed on data sets that are smaller.

Below are tables of sample sizes needed to meet a specified margin of error at a 95% confidence level for various population sizes. Margin of Error Sample Size Proportion of Population 10% 81 16. 20%9% 96 19. 20%8% 116 23. 20%7% 141 28.

### 20%6% 174 34. 80%5% 217 43. 40%4% 273 54. 60%3% 341 68.

20%Table 5 Sample sizes required to meet a 95% confidence level between a 3% and 10% margin of error with a population of 500 Margin of Error Sample Size Proportion of Population 10% 85 11. 33%9% 102 13. 60%8% 125 16. 67%7% 156 20. 80%6% 197 26.

27%5% 254 33. 87%4% 334 44. 53%3% 441 58. 80%Table 6 Sample sizes required to meet a 95% confidence level between a 3% and 10% margin of error with a population of 750 Margin of Error Sample Size Proportion of Population 10% 88 8.

### 80%9% 106 10. 60%8% 131 13. 10%7% 164 16. 40%6% 211 21.

10%5% 278 27. 80%4% 375 37. 50%3% 516 51. 60%Table 7 Sample sizes required to meet a 95% confidence level between a 3% and 10% margin of error with a population of 1000 Margin of Error Sample Size Proportion of Population 10% 90 6. 00%9% 110 7. 33%8% 136 9.

07%7% 173 11. 53%6% 227 15. 13%5% 306 20. 40%4% 429 28. 60%3% 624 41. 60%Table 8 Sample sizes required to meet a 95% confidence level between a 3% and 10% margin of error with a population of 1500 Margin of Error Sample Size Proportion of Population 10% 92 4.

### The Research paper on Multicultural Population Study

The objective of this research is to analyze the community based in the U. S. , most of them are Asians in this research we are talking about the Filipinos who are working in U. S. most of them are working there in cheap wages. The population of Filipinos are increasing in US are increasing rapidly. Number of Filipinos are working abroad especially professional ones would rather work abroad than ...

### 60%9% 112 5. 60%8% 140 7. 00%7% 179 8. 95%6% 235 11.

75%5% 322 16. 10%4% 462 23. 10%3% 696 34. 80%Table 9 Sample sizes required to meet a 95% confidence level between a 3% and 10% margin of error with a population of 2000.