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Sampling method

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• A good research strategy requires careful planning and a pilot study will often be a part of this strategy.
• In order to make statistically valid inferences for the population, they must incorporate the sample design in the data analysis.
• -Reduce cost while doing only a small selected random group-Time consume in order to emphasize the correctness of data-Less burden since less data to be handle-Control the quality of data and minimize the error
• It is a regularly occurring and official count of a particular population. The term is used mostly in connection with national population and housing censuses. Other common censuses include agriculture, business, and traffic censuses.
• to business, all levels of governance, media, students and teachers, charities and researchers, and any citizen who is interested. to show the difference between certain areas, or to understand the association between different personal characteristics.
• It is important for a researcher to be aware of these errors, in particular non-sampling error, so that they can be either minimized or eliminated from the survey. Discrepancy-PercanggahanThe greater the error, the less representative the data are of the population.Data can be affected by two types of error: - 1)Sampling Error 2)Non-Sampling Error
• It is important for a researcher to be aware of these errors, in particular non-sampling error, so that they can be either minimized or eliminated from the survey. Discrepancy-PercanggahanThe greater the error, the less representative the data are of the population.Data can be affected by two types of error: - 1)Sampling Error 2)Non-Sampling Error
• Sampling error can be measured and controlled in random samples where each unit has a chance of selection, and that chance can be calculated. In general, increasing the sample size will reduce the sample error.Sampling errors do not occur in a census, as the census values are based on the entire population. it can be measured mathematically
• Sampling error can be measured and controlled in random samples where each unit has a chance of selection, and that chance can be calculated. In general, increasing the sample size will reduce the sample error.A typical survey process includes initiating pre-survey contact requesting cooperation, actual surveying, post survey follow-up if a response is not received, a second survey request, and finally interviews using alternate modes such as telephone or person to person.
• Sampling error can be measured and controlled in random samples where each unit has a chance of selection, and that chance can be calculated. In general, increasing the sample size will reduce the sample error.A typical survey process includes initiating pre-survey contact requesting cooperation, actual surveying, post survey follow-up if a response is not received, a second survey request, and finally interviews using alternate modes such as telephone or person to person.
• Non-sampling error can occur at any stage of a census or sample study, and are not easily identified or quantified.
• Coverage error: e.g. a field interviewer fails to interview a selected household or some people in a household.Non-response error: i.e. no data has been obtained at all from a selected unit or partial.Response error: giving a response which they feel is more acceptable rather than being an accurate response.
• Coverage error: e.g. a field interviewer fails to interview a selected household or some people in a household.Non-response error: i.e. no data has been obtained at all from a selected unit or partial.Response error: giving a response which they feel is more acceptable rather than being an accurate response.
• Standard Error (SE) -As the standard error of an estimated value generally increases with the size of the estimate, a large standard error may not necessarily result in an unreliable estimate. Therefore it is often better to compare the error in relation to the size of the estimate.Relative Standard Error (RSE) - It is usually displayed as a percentage. A high RSE indicates less confidence that an estimated value is close to the true population value.Where published statistics contain an indication of the RSEs they can be used to compare statistics from different studies of the same population
• -callbacks – if there are non-response value, the interviewer should make a callback to the respondent in order to get the accurate data. If and only if the respondent’s phone number is given.-reward and incentives – a way to appreciate respondents for giving some time and opportunity for the interviewer interview them.-trained interviewers – interviewers must be trained well in order to confront any problem occur during conduct the survey.-data checks – ensure all important data that needed are being checks.-questionnaire construct – certify that the questions in the questionnaires are appropriate for the topic and easy to understand by the respondents.
• As for sampling error happen because:i) sample frame error – (i.e. other than UiTM students)ii) selection error – (i.e. then we might loss the suitable respondent that should be represent in data)
• As for non-sampling error happen because:i) coverage error – (i.e. suitability of each of the unit in the sample)ii) non-response error – (i.e. maybe they sensitive with questions about age, hp. No., marital status etc) iii) response error - respondents no understood about the survey or question that being asked.
• Sampling method

1. 1. Group Members: AMIRA BINTI MISDAR HATIKA BINTI MEGAT JAMIL NUR ARINA BINTI NURUL ‘AKLA NUR FATHANAH BINTI MOHAMAD ZAKI Sept 2013 – Jan 2014 D2 CS 241 4A 2012738515 2012959065 2012918743 2012753899
2. 2. QUESTION 1 DISTINGUISH CAREFULLY BETWEEN A PILOT SURVEY, A SAMPLE SURVEY AND A CENSUS.
3. 3. Pilot Survey A small experiment designed to test logistics and gather information prior to a larger study, in order to improve the latter’s quality and efficiency. It also can reveal deficiencies in the design of a proposed experiment or procedure and these can be addressed before time and resources are expended on large scale studies.
4. 4. Pilot Survey cont… Reasons : To test out the questions and see if they are giving you the type of answers that you want. People may not understand what you are asking, so the reseacher may need to modify questions to get what you want. If you do not carry a pilot test and not work out on those problems, the results from the final questionnaire may be useless.
5. 5. Use to obtain information about a large aggregate or population by selecting and measuring a sample from that population. Due to the variability of characteristics among items in the population, researchers apply scientific sample designs in the sample selection process to reduce the risk of a distorted view of the population, And then, they make inferences about the population based on the information from the sample survey data.
6. 6. COST • A sample survey costs less than a census because data are collected from only part of a group. TIME • Results are obtained far more quickly for a sample survey, than for a census. Fewer units are contacted and less data needs to be processed. CONTROL • The smaller scale of this operation allows for better monitoring and quality control. • Fewer people have to respond in the RESPONSE BURDEN sample.
7. 7. • A census is a survey conducted on the full set of observation objects belonging to a given population or universe. • The United Nations defines the essential features of population and housing censuses as "individual enumeration, universality within a defined territory, simultaneity and defined periodicity", and recommends that population censuses be taken at least every 10 years.
8. 8. Reasons: Census data are published in a wide variety of formats to be accessible. Data can be represented visually or analyzed in complex statistical models. Census data offer a unique insight into small areas and small demographic groups.
9. 9. WHY RESULTS FROM A CENSUS MIGHT DIFFER FROM THE TRUE VALUES IN THE POPULATION?
10. 10. The accuracy of a survey estimate refers to the closeness of the estimate to the true population value. Where there is a discrepancy between the value of the survey estimate and true population value, the difference between the two is referred to as the error of the survey estimate.
11. 11. Error (statistical error) describes the difference between a value obtained from a data collection process and the 'true' value for the population.
12. 12. Sampling error which arises when only a part of the population is used to represent the whole population. It occurs solely as a result of using a sample from a population, rather than conducting a census the population. It refers to the difference between an estimate for a population based on data from a sample and the 'true' value for that population which would result if a census were taken.
13. 13. POPULATION SPECIFICATION ERROR •This error occurs when the researchers does not understand who they should survey. SAMPLE FRAME ERROR •A frame error occurs when the wrong sub-population is used to select a sample. SELECTION ERROR •This occurs when respondents self select their participation in the study – only those that are interested respond. Selection error can be controlled by going extra lengths to get participation.
14. 14. SAMPLING ERROR - These errors occur because of variation in the number or representativeness of the sample that responds. Sampling errors can be controlled by
15. 15. • Caused by factors other than those related to sample selection. • Occur at any stage of a sample survey and can also occur with censuses. • It refers to the presence of any factor, whether systemic or random. • Results in the data values not accurately reflecting the 'true' value for the population.
16. 16. COVERAGE ERROR NONRESPONSE ERROR RESPONSE ERROR • Unit in the sample is incorrectly excluded or included, or is duplicated in the sample. • The failure to obtain a response from some unit • because of absence, non-contact, refusal, or some other reason. • Respondents intentionally or accidentally providing inaccurate responses. • Concepts, questions or instructions are not clearly understood by the respondent.
17. 17. INTERVIEWER ERROR PROCESSING ERROR • Interviewers incorrectly record information; are not neutral or objective; influence the respondent to answer in a particular way; or assume responses based on appearance or other characteristics. • Errors that occur in the process of data collection, data entry, coding, editing and output.
18. 18. The greater the errors, the less reliable are the results of the study . A credible data source will have measures in place throughout the data collection process to minimize the amount of error. be transparent about the size of the expected error so that users can decide whether the data are 'fit for purpose'.
19. 19. Two common measures of error: Relative Standard Error (RSE) Standard Error (SE) -
20. 20. The standard error can be used to construct a confidence interval. • C.I is a range in which it is estimated the true population value lies. • C.I of different sizes can be created to represent different levels of confidence that the true population value will lie within a particular range.
21. 21. CALLBACKS REWARD AND INCENTIVES DATA CHECKS TRAINED INTERVIEWERS QUESTIONNAIRES CONSTRUCTION
22. 22. Example: We want to conduct a survey about the UiTM cafeteria in UiTM Machang. The survey is based on the customers’ satisfaction on the food, price, facilities and services provided by every cafeteria in UiTM Machang. The customers’ are selected from the all UiTM students in that campus.
23. 23. As for sampling error happen because: SAMPLE FRAME SELECTION
24. 24. As for non-sampling error happen because: COVERAGE ERROR NON-RESPONSE ERROR May happen due to unit in the sample is incorrectly excluded or included or is duplicate in the sample. Some of the respondents might not respond or not answers the questions being asked. RESPONSE ERROR Respondents not understand about the survey or question that being asked. PROCESSING ERROR Occur in the process of data collection, data entry, coding, editing and output.
25. 25. REFERENCES  http://www.statcan.gc.ca/edu/power-pouvoir/ch6/sampling-echantillonage/5214807eng.htm  http://www.qualtrics.com/blog/frequent-sampling-errors/  http://www.abs.gov.au/websitedbs/a3121120.nsf/home/statistical+language++types+of+error  http://www.nss.gov.au/nss/home.nsf/NSS/4354A8928428F834CA2571AB002479CE?op endocument  http://srmo.sagepub.com/view/using-published-data/n1.xml  http://stats.oecd.org/glossary/detail.asp?ID=3787  http://support.sas.com/rnd/app/da/new/dasurvey.html  http://stats.oecd.org/glossary/detail.asp?ID=301