James Lee - 000674770-1

Kajal Patel - 000598608-7

Victoria Raida 000652765-5 Sampling We will be looking at... This Presentation Firstly What is Sampling... What is Census and why would one choose a census over sampling? What are Sampling Errors and how can sampling errors be avoided? Scenario 3 Scenario 1 References Probability and non-probability Census and Sampling Sampling Errors and how they can avoided How does Probability techniques

differ from

non-probability techniques? Scenario 5 Scenario 2 This Presentation We will also be looking at... Evaluating Specific Scenarios Simple Random sampling Systematic Sampling What is Census and why would one

choose a census over sampling? What are Sampling Errors and how can

sampling errors be avoided? We are going to discuss 6 scenarios and analyse the sampling technique used We will give an evaluation and suggest a more appropriate approach Scenario 4 Scenario 6 Summary Overall we have explained what sampling is and its different approaches What is a Census and why would one choose a Census over sampling? We were attempting to look at shoppers attitudes towards a new ‘hand held’ shopping basket, so we decided to conduct a random sample of shoppers by stopping people outside a Tesco superstore on a Saturday morning.’

Evaluate this approach. Evaluation Recommended Approach Evaluation Recommended Approach A national Bank conducted a survey in 4 major city centres, aiming to understand user’s opinion of ‘Online Banking’. The surveys were undertaken in the main busy high street on a Friday morning between 8.30 and 9.30 am and again between 4.30 to 5.30pm. They were hoping to attract a good response, as they knew it would be busy at these times. However, they only managed to collect approximately 50 usable completed questionnaires from each city centre.

Evaluate this approach. 2 Marketing students undertaking a Level 2 consumer research Course set out to research consumer’s attitudes towards mobile phone networks. They decided to target heavy users of mobile phones aged between 18 and 34. They decided to use convenient sampling, as they felt this was the most appropriate sampling technique to adopt.

Would you agree with their approach? If not, what approach would you recommend? ‘LTC (a London base radio station) was planning to launch a new Radio Station targeted at 15 to 23 year olds. In order to find out the views of young people, we asked for volunteers and interviewed (via survey) 50 MA Marketing students from the University of Greenwich.

Evaluate this approach. ‘A local village crèche decided to conduct research on their facilities

and how they could improve their offering. They left a batch of A4 questionnaires

(one page of questions) near the doorway. After a week only 6 out of a

potential 60 were returned. The manager felt that 10% would be

sufficient to draw some conclusion for the board of governors.

What would you have done differently? A company has 100 Employees. They have asked you to address the following research question: ‘Is there a link between earnings and job satisfaction’.

The earnings distribution (£ per annum) is as follows:

Group 1: 1 member of staff: 150,000

Group 2: 1 member of staff: 100,000

Group 3: 2 members of staff: 75,000

Group 4: 4 members of staff: 50,000

Group 5: 8 members of staff: 45,000

Group 6: 32 members of staff: 30,000

Group 7: 50 members of staff: 25,000

Group 8: 2 members of staff: 20,000 How would you develop a Systematic Sampling approach using the list? Do the calculation, showing the distribution of the sample. Why might you choose Systematic Sampling over

Simple Random Sampling and why? What are Sampling Errors and how can sampling errors be avoided? 'the collection and analysis of data from every possible case or group member in a population'.

(Saunders et al. 2012) A Census is ... A Census is will provide more authentic and solid results A Census will provide reliable results because you are asking everyone 2 Hours throughout the day is not enough time The times that the surveys were undertaken were peak times - people do not have time and are unlikely to stand to answer a questionnaire The Town Centre will have a range of different age groups - if there are younger or older people they are unlikely to even use 'Online Banking'. Recommended Approach Asking specific users of the service via email or when they log onto

'Online Banking' Anyone who walks into a branch to be asked by a cashier if they wouldn't mind answering a questionnaire Evaluation To develop a systematic sampling approach using this list you must first:

1) Establish the population which is 100

2) Then decide a sample which is 10

3) Divide the population size by the sample size so, 100/10 = 10

4) Choose a number between 1 - 10. We have chosen 1.

5) Select every 10th listing. We have put the employees into groups according to their wages. Using the systematic sampling method with a skip interval of 10 then the results would be as follows:

Group 1: 1 member of staff

Group 2: N/A

Group 3: N/A

Group 4: N/A

Group 5: 1 member of staff

Group 6: 2 members of staff

Group 7: 5 members of staff

Group 8: 1 member of staff Systematic sampling may be chosen over simple random sampling because:

It spreads the sample more evenly over the population.

In random sampling, there is a chance of a clustered selection of subjects.

It is also easier to conduct over random sampling because it allows the researcher to add a degree of process. A sampling error is 'an error caused when the given sample is not representative of the population being studied.' Bryman, A & Bell, E (2007). Business Research Methods . 2nd ed. New York: Oxford University Press.

Cohen, L., Manion, L., and Morrison, K., 2007. Research Methods in Education. 6th ed. New York: Routledge.

Unkown. (2013). Glossary. Available: A sampling error is ‘An error caused when the given sample is not representative of the population being studied.’ (http://www.quirks.com/search/glossary.aspx?search=sampling+errors&searchID=643397043). Last accessed 25th January 2013.

Saunders, M., Lewis, P. and Thornhill, A. (2012), Research Methods for Business Students, 6th ed. Harlow: Pearson Educated Limited.

Thompson, S. K., 2012. Sampling. 3rd ed. John Wiley & Sons Publication. Sampling errors can be avoided by increasing the size of the sample.

Stratification can also be used. What would you have done differently? In order to gain a higher response rate, we would have explained the questionnaire to the participants so that they could understand what is was and how it would be helpful.

We would also suggest that the questionnaire was not too long in as this also reduces response rates. Thank You For Your Time

Any Questions? A Random sampling technique is used Targeting shoppers at a local superstore in this case 'Tesco' Targets all ages groups and genders Targeting shoppers specifically who are alone at the time rather than with a family Targeting 'Tesco Express' shoppers as hand baskets are only available in store Going more than once and conducting at other supermarket outlets - Sainsburys and Asda for example We have looked at the errors that researchers make when sampling We have also evaluated some real life scenarios We have compared Probability and Non- Probability techniques Sampling refers to the selection of a subset of individuals from a population to form the sample for your survey. (Thompson, 2012) There are two types of sampling methods: Probability Sampling and Non-Probability Sampling. Probability Probability methods require a sample frame (a comprehensive list of the population of interest).

Rely on random selection in a variety of ways from the sample frame of the population.

They permit the use of higher level statistical techniques which require random selection.

Allow you to calculate the difference between your sample results and the population equivalent values so you can state that you know the population values. Non-probability methods do not. Probability Samples A probability sample is one in which each element of the population has a known non-zero probability of selection.

Not a probability sample of some elements if population cannot be selected (have zero probability).

Not a probability sample if probabilities of selection are not known. Simple Random Sampling Simple random sampling is a probability sampling procedure that gives every element in the target population, and each possible sample of a given size, an equal chance of being selected.

Statistical procedures required to analyze data and compute errors are easier Systematic Sampling A method of selecting sample members from a larger population according to a random starting point and a fixed, periodic interval.

Typically, every "nth" member is selected from the total population.

Hence, if the total population was 1,000, a random systematic sampling of 100 data points within that population would involve observing every 10th data point. Stratified Sampling A stratified sample is made up of different 'layers' of the population, for example, age groups. The sample size for each layer is proportional to the size of the 'layer'.

e.g. 1000 pupils in the school, you want answers from 50 people in total Cluster Sampling Survey method in which groups (clusters) of sampling units (and not individual units) are selected from a population for analysis. (Cohen et al. 2007)

With cluster sampling, the researcher divides the population into separate groups, called clusters.

A simple random sample of clusters is selected from the population. Non-probability Non-probability sampling does not involve random selection.

Non-probability samples cannot depend upon the rationale of probability theory.

Available even when you have no sample frame.

They may minimise the preparation costs of a survey, and be employed when you are actually unsure of the population of interest. Non-probability Continued... They are generally less complicated to undertake.

Forms of non-probability sampling are numerous, such as voluntary samples (only responses of volunteers are used), quota samples, expert samples. Convenience Sampling A statistical method of drawing representative data by selecting people.

Least time consuming.

Availability and the quickness with which data can be gathered. Judgemental Sampling A form of convenience sampling in which the population elements are purposely selected based on the judgment of the researcher.

Low cost, convenient and quick

Subjective and its value depends entirely on the researchers judgment, expertise and creativity. QOTA Sampling A sampling method of gathering representative data from a group.

As opposed to random sampling, quota sampling requires that representative individuals are chosen out of a specific subgroup.

For example, a researcher might ask for a sample of 100 females, or 100 individuals between the ages of 20-30. Snowball Sampling A snowball sample is a non probability sampling technique that is appropriate to use in research when the members of a population are difficult to locate.

The process is cheap, simple and cost-efficient.

This sampling technique needs little planning and fewer workforce compared to other sampling techniques. Evaluation This type of approach is cost effective - They are students This type of approach is also least time consuming This sampling approach is the best to use because... However this type of approach can be bias No sampling is done.

Radio Station targeted to 15-23 year olds.

Volunteers were asked and interviewed.

50 Marketing students from University of Greenwich. To ask more people from different areas between the ages 15-23.

Preferably quota sampling e.g. asking 100 individuals from the age group 15-23.

Interview more college and university students. (Quirks, 2013) Geography has been looked at - as they at major cities

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# Sampling

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