Marketing
Sampling Plan
A sampling plan in marketing refers to the method used to select a representative group of individuals or elements from a larger population for research or analysis. It outlines the criteria for selecting the sample, such as demographics or geographic location, and the sampling technique to be used, such as random sampling or stratified sampling. The goal is to ensure that the sample accurately reflects the characteristics of the larger population.
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eBook - PDF- Carl McDaniel, Jr., Roger Gates(Authors)
- 2020(Publication Date)
- Wiley(Publisher)
99 CHAPTER 5 Sample Design PeopleImages/Getty Images LEARNING OBJECTIVES 1. Understand the concept of sampling. 2. Learn the steps in developing a Sampling Plan. 3. Understand the concepts of sampling error and nonsampling error. 4. Understand the differences between probability samples and nonprobability samples. 5. Gain an appreciation of a normal distribution. 6. Learn how to determine sample size. As noted elsewhere in the text, the world that marketing researchers operate in has changed to a tremendous extent over the last 30 years. PCs, tablets, mobile devices in general, the Internet, and social media are major forces behind these changes. They present new chal- lenges and opportunities. One fundamental issue has not changed and that relates to the process of generating a sample that is representative of the population. Many think that really big samples, think big data, are a substitute for representative samples. But the basic rules still apply, the sample must be representative, it must be a miniature of the popula- tion. If we have a proper sample then we can determine the level of sampling error. All of these concepts are discussed in detail in this chapter. 100 CHAPTER 5 Sample Design Concept of Sampling Sampling, as the term is used in marketing research, is the process of obtaining information from a subset (a sample) of a larger group (the universe or population). We then take the results from the sample and project them to the larger group. The motivation for sampling is to be able to make these estimates more quickly and at a much lower cost than would be possible by other means. It has been shown time and again that sampling a small percent- age of a population can produce very accurate estimates about the population. One exam- ple that you are familiar with is polling in connection with political campaigns and elections.
eBook - PDF- Carl McDaniel, Jr., Roger Gates(Authors)
- 2016(Publication Date)
- Wiley(Publisher)
11 C H A P T E R LEARNING OBJECTIVES 1. Understand the concept of sampling. 2. Learn the steps in developing a Sampling Plan. 3. Understand the concepts of sampling error and nonsampling error. 4. Understand the differences between probability samples and nonprobability samples. 5. Understand sampling implications of surveying over the Internet. Basic Sampling Issues StockLib/iStockphoto StockLib/iStockphoto Concept of Sampling 243 Concept of Sampling Sampling, as the term is used in marketing research, is the process of obtaining information from a subset (a sample) of a larger group (the universe or population). We then take the results from the sample and project them to the larger group. The motivation for sampling is to be able to make these estimates more quickly and at a much lower cost than would be possible by any other means. It has been shown time and again that sampling a small percentage of a popu- lation can produce very accurate estimates about the population. An example that you are probably familiar with is polling in connection with political elections. Most major polls for national elections use samples of 1,000–1,500 people to make predictions regarding the voting behavior of tens of millions of people, and their predictions have proven to be remarkably accurate. The key to making accurate predictions about the characteristics or behavior of a large population on the basis of a relatively small sample lies in the way in which individuals are selected for the sample. It is critical that they be selected in a scientific manner, which ensures that the sample is representative—that it is a true miniature of the population. All of the major types of people who make up the population of interest should be represented in the sample in the same proportions in which they are found in the larger population. This same requirement remains as we move into the range of new online‐ and social media‐based data acquisition approaches.
eBook - PDFMarketing Research
A Concise Introduction
- Bonita Kolb(Author)
- 2017(Publication Date)
- SAGE Publications(Publisher)
Question: Can you think of other ways technology could be used to make the selection process easier? Source: Sun, 2015 11.1 Sampling Issues One of the questions researchers face when developing a research plan is who will be chosen to be research participants. The word ‘population’ is commonly used to define everyone of interest who could be possibly included in a research study. Researchers may define a population by geographic area. In addition, they may also define a population using such demographic data as age, gender, income or ethnicity. Because marketing promotion is often targeted based on psychographic segmenta- tion, researchers may also define a population based on interests, values or lifestyles. Product usage can also be a means for defining a population, such as nonusers, occa- sional users and frequent users. These variables can also be used in combination. The resulting population may be very large, such as daily users of toothpaste who live in Germany, or very small, such as people over the age of 70 in the UK who are attending university as full-time students. A standard process should be followed when selecting a sample. First the popula- tion needs to be defined along with the frame, which are the people in the sample. A method for sampling from people in the frame will be the next issue, along with determining how many people need to be research subjects. Finally, the research subjects will be chosen. Sampling process • Decide on population to be studied • Develop sampling frame • Choose sampling method • Determine sample size • Choose sample participants (Continued) DETERMINING PROBABILITY SAMPLES 191 11.1.1 Using a census When conducting quantitative research, researchers are attempting to support a fact or hypothesis. This fact might be how many consumers would buy a product, what type of new promotion would work best, the effect of pricing on purchase behavior, or the best store in which to distribute a product.
eBook - ePubMarketing
A Relationship Perspective
- Svend Hollensen, Marc Oliver Opresnik(Authors)
- 2019(Publication Date)
- WSPC (US)(Publisher)
The main drawbacks of personal interviewing are the high costs and sampling problems. Group interview studies usually employ small sample sizes to keep time and costs down, but it may be hard to generalise from the results. Because interviewers have more freedom in personal interviews the problem of interviewer bias is greater.Thus there is no ‘best’ contact method – it all depends on the situation. Sometimes it may even be appropriate to combine the methods.Sampling Plan
A Sampling Plan is a scheme outlining the group (or groups) to be surveyed in a marketing research study, how many individuals are to be chosen for the survey, and on what basis this choice is made.Sampling unit:Except in very restricted markets it is both impractical and too expensive for a researcher to contact all the people who could have some relevance to the research problem. This total number is known statistically as the ‘universe’ or ‘population’. In marketing terms, it comprises the total number of actual and potential users/customers of a particular product or service.The population can also be defined in terms of elements and sampling units. Suppose that a lipstick manufacturer has aSampling Planto assess consumer response to a new line of lipsticks and wants to sample females over 15 years of age. It may be possible to sample females of this age directly, in which case a sampling unit would be the same as an element. Alternatively, households might be sampled and all females over 15 in each selected household interviewed. Here the sampling unit is the household, and the element is a female over 15 years old.What is usually done in practice is to contact a selected group of consumers/customers to be representative of the entire population. The total number of consumers who could be interviewed is known as the ‘sample frame’, while the number of people who are actually interviewed is known as the ‘sample’.
eBook - PDFResearch Methods For Business
A Skill Building Approach
- Uma Sekaran, Roger Bougie(Authors)
- 2016(Publication Date)
- Wiley(Publisher)
For this purpose, the first 15 people who chose the special item might be interviewed, and their reactions obtained. In such cases, having instant information may be more gainful than obtaining the most representative facts. It should, however, be noted that the results of such convenient samples are not reliable and can never be generalized to the population. THE SAMPLING PROCESS Sampling is the process of selecting a sufficient number of the right elements from the population, so that a study of the sample and an understanding of its properties or characteristics make it possible for us to generalize such properties or characteristics to the population elements. The major steps in sampling include: Low High F I G U R E 1 3 . 3 Normal distribution in a population 240 research methods for business 1. Define the population. 2. Determine the sample frame. 3. Determine the sampling design. 4. Determine the appropriate sample size. 5. Execute the sampling process. Defining the population Sampling begins with precisely defining the target population. The target population must be defined in terms of elements, geographical boundaries, and time. For instance, for a banker interested in saving habits of blue‐collar workers in the mining industry in the United States, the target population might be all blue‐collar workers in that industry throughout the country. For an advertising agency interested in reading habits of elderly people, the target population might be the German population aged 50 and over. These examples illustrate that the research objective and the scope of the study play a crucial role in defining the target population. Determining the sample frame The sampling frame is a (physical) representation of all the elements in the population from which the sample is drawn. The payroll of an organization would serve as the sampling frame if its members are to be studied.
No longer available |Learn more- (Author)
- 2014(Publication Date)
- Orange Apple(Publisher)
________________________ WORLD TECHNOLOGIES ________________________ Chapter- 1 Introduction to Sampling Sampling is that part of statistical practice concerned with the selection of a subset of individual observations within a population of individuals intended to yield some knowledge about the population of concern, especially for the purposes of making predictions based on statistical inference. Sampling is an important aspect of data collection. Researchers rarely survey the entire population for two reasons (Adèr, Mellenbergh, & Hand, 2008): the cost is too high, and the population is dynamic in that the individuals making up the population may change over time. The three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data. Each observation measures one or more properties (such as weight, location, color) of observable bodies distinguished as independent objects or individuals. In survey sampling, survey weights can be applied to the data to adjust for the sample design. Results from probability theory and statistical theory are employed to guide practice. In business and medical research, sampling is widely used for gathering information about a population. Process The sampling process comprises several stages: • Defining the population of concern • Specifying a sampling frame, a set of items or events possible to measure • Specifying a sampling method for selecting items or events from the frame • Determining the sample size • Implementing the Sampling Plan • Sampling and data collecting Population definition Successful statistical practice is based on focused problem definition. In sampling, this includes defining the population from which our sample is drawn. A population can be
No longer available |Learn more- (Author)
- 2014(Publication Date)
- Orange Apple(Publisher)
________________________ WORLD TECHNOLOGIES ________________________ Chapter- 1 Sampling Sampling is that part of statistical practice concerned with the selection of a subset of individual observations within a population of individuals intended to yield some knowledge about the population of concern, especially for the purposes of making predictions based on statistical inference. Sampling is an important aspect of data collection. Researchers rarely survey the entire population for two reasons (Adèr, Mellenbergh, & Hand, 2008): the cost is too high, and the population is dynamic in that the individuals making up the population may change over time. The three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data. Each observation measures one or more properties (such as weight, location, color) of observable bodies distinguished as independent objects or individuals. In survey sampling, survey weights can be applied to the data to adjust for the sample design. Results from probability theory and statistical theory are employed to guide practice. In business and medical research, sampling is widely used for gathering information about a population. Process The sampling process comprises several stages: • Defining the population of concern • Specifying a sampling frame, a set of items or events possible to measure • Specifying a sampling method for selecting items or events from the frame • Determining the sample size • Implementing the Sampling Plan • Sampling and data collecting Population definition Successful statistical practice is based on focused problem definition. In sampling, this includes defining the population from which our sample is drawn. A population can be
No longer available |Learn more- (Author)
- 2014(Publication Date)
- Orange Apple(Publisher)
________________________ WORLD TECHNOLOGIES ________________________ Chapter- 6 Sampling Sampling is that part of statistical practice concerned with the selection of a subset of individual observations within a population of individuals intended to yield some knowledge about the population of concern, especially for the purposes of making predictions based on statistical inference. Sampling is an important aspect of data collection. Researchers rarely survey the entire population for two reasons (Adèr, Mellenbergh, & Hand, 2008): the cost is too high, and the population is dynamic in that the individuals making up the population may change over time. The three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data. Each observation measures one or more properties (such as weight, location, color) of observable bodies distinguished as independent objects or individuals. In survey sampling, survey weights can be applied to the data to adjust for the sample design. Results from probability theory and statistical theory are employed to guide practice. In business and medical research, sampling is widely used for gathering information about a population. Process The sampling process comprises several stages: • Defining the population of concern • Specifying a sampling frame, a set of items or events possible to measure • Specifying a sampling method for selecting items or events from the frame • Determining the sample size • Implementing the Sampling Plan • Sampling and data collecting Population definition Successful statistical practice is based on focused problem definition. In sampling, this includes defining the population from which our sample is drawn. A population can be
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