4.1 Research Approaches. One Of The Questions That An Organization

this study is the use of convenience sampling, as previously mentioned. Black et al. (2000) make

According to Acharya, Prakash, Saxena, and Nigam (2013), sampling designs are classified into two categories: probability sample and non-probability sample. Probability sampling aids in the generalizability of the results because individuals in the population have an equal chance of being selected to participate in the study (Acharya et al., 2013). With the non-probability sampling method, every individual does not have the same chances of being included (Frankfort-Nachmias, & Nachmias,

The sample size is a non probability sampling. The problem with non probability sampling is that an element being drawn is not known, so there is no way to tell if the sample chosen represents the population (Madden & Walker, 2005, p. 333). Although there are slight problems in using a non probability sampling, it is more convenient, less expensive, and easier to collect data than other sampling methods (Madden & Walker, 2005, p. 333).

In a probability sample each element or unit of the population have a known chance of being selected for the sample study. Probability samples also permit a precise estimate of parameters. Since all elements have an equal chance of being selected for your survey, you can randomly select participants without missing portions of your population; you have a complete sampling frame. With probability samples you can generalize your results from this random sample. With Non-probability samples some people have a greater, but unknown, chance than others of selection into the sample study. Nonprobability samples are used when there is not a complete population list available. Some units are unable to be selected; therefore you have no way of knowing the size and effect of sampling error. Nonprobability samples are not random and often bias; you cannot generalize your results to an entire population with a high level of confidence. Probability samples are the best for the purpose of making valid

| To find the marks of a class of 20 students in a physics exam

Sampling involves selecting a subset of elements from the population. In this case, Stratified Random Sampling, and Simple Random Sampling plans are compared as data collection methods for a sample that a researcher would consider using for a business survey for a marketing/advertising campaign. Simple Random Sampling is a sampling procedure whereby the researcher defines the target population and then selects a sampling frame from the population. He then selects individual elements within the sampling frame with each element having an equal probability of being chosen.

The purpose of this exercise is to convey some basic concepts in regards to sampling while at the same time deriving sampling distributions empirically. Deriving sampling distributions empirically works best when there are a large number of samples. The idea here is that each student in the class will create 20 samples for two populations, using two different sampling procedures, for a total of 80 samples. These samples will be combined into common datasets which will be used in class (and made available to all students in the class.

Sampling is taking a few items from a population that fairly represent the population to obtain information about the population from them. It is usually one of the key steps in research because it determines the validity and reliability of research results. This crucial yet arduous task in research has led statisticians and software developers to create software that can ease this process for many researchers in various fields of study. An example of such a sampling software is the Visual Sample Plan version 7.0 (VSP 7.0).

This way households are selected by random selection. My sample size, that is the number of subjects in my study, will be around five hundred people. The type of sample that is best suited to answer my research question is

Research methodology is a way how the research is conducted step by step and in order. There are two methods used for data collection which is the primary data and secondary data. These data can be obtained and used many ways. The data is taken and analyzed in advance to produce a result that we can use for research and future reference. This study will relate to the objective we want to achieve and finding the answer to every objective we seek. In order to successfully achieve the objectives we seek, we must know

Exploratory research: - Firstly explore the demand from these outlets. Various methods will be implemented to conduct research on the following groups.

Systematic random sampling: can be described as a most commonly used method in which after a number has been allocated to an individual in the population frame, the first person is selected using a random number table or out of a hat and subsequently those who take part in it are selected or picked using a fixed sample interval (Mathers, Sampling for surveys, 2009, p. 11).

There are three main types of descriptive methods: observational methods, case-study methods and survey methods. This article will briefly describe each of these methods, their advantages, and their drawbacks. This may help you better understand research findings, whether reported in the mainstream media, or when reading a research study on your own.

In order to conduct a research study, there should be a complete objective and purpose for it. For that reason, the research studies revolve around three dissimilar purposes, exploratory, descriptive, and explanatory (Kumar, 2012). The merely difference is the process through which arrangement of research queries are conserved. These three types deviate from each other in different manners that are being elaborated below;

One of four research methods included under the descriptive-oriented research strategy is the Survey Research Method. It is operationally defined as a research method characterized by several principal