A random sample presupposes that all the elements of a particular frame are given the same selection probability. A random sample can be of great use in creating and analyzing surveys carried out among the customers of a particular company.
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A stratified sample is probabilistic. It is utilized when every single element is considered unique, and therefore, the samples cannot be analyzed through the lens of an average mean.
A systematic sample presupposes that every nth element of a list be selected. For instance, systematic sampling is used when every 5th person must be chosen from a total of 250 people.
A cluster sample demands that the total number of samples should be split into several smaller groups, which is chosen with the help of a probability method. A cluster sample technique may work for an analysis of a particular phenomenon within a multiethnic group.
A multistage sample is a kind of cluster sampling that splits the elements of the cluster chosen randomly into several sub-clusters. For example, after dividing people into clusters by their ethnicity, a particular cluster can be chosen to be split into sub-clusters based on the age of the research participants.
A convenience sample belongs to the non-probability methods and presupposes that the people that can be reached easily should be included. The people that are currently in a certain shop can be viewed as a convenience sample for a survey on the services in the shop (Brase and Brase “Getting Started” 3–18).
A steam-and-leaf display, known as a device that allows for structuring and presenting quantitative information, helps sort the aforementioned information based on a particular parameter, starting from the pieces of information that have the lowest rate to the ones that have the highest one. To construct an SLD, one must put the acquired information in ascending order (Brase and Brase “Organizing Data” 24).
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To construct an SLD, the data must be split into two columns. As it has been stressed above, it is crucial that the data should be sorted in ascending order; as a rule, the procedure of data sorting can be done manually. The left column incorporates the stems, whereas the right column includes the leaves, each being mentioned only once. The leaves repeated in the specified data set are not to be skipped.
Naturally, one may encounter negative numbers when working with different types of data. These are also to be included in the SL. There is no particular difference between listing the negative and the positive data – both are sorted in the same ascending manner, the negative being placed before the number. It should be kept in mind, though, that the list should start with the negative number that has the greater value, with the number of a lesser value following it. SLD are traditionally used in defining the density and shape of data (Brase and Brase “Organizing Data” 30). Allowing for sorting options, SLD is most helpful for big and medium data sets.
Brase, Henry Charles and Corrinne Pellillo Brase. “Getting Started.”Understanding Basic Statistics. 6th ed. Ed. Henry Charles Brase and Corrinne Pellillo Brase. Pacific Grove, CA: Brooks/Cole Publishing Company. 2013. 3–18. Print.
—. “Organizing Data.” Understanding Basic Statistics. 6th ed. Ed. Henry Charles Brase and Corrinne Pellillo Brase. Pacific Grove, CA: Brooks/Cole Publishing Company. 2013. 19–32. Print.