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Business Statistics (BUSI.2305), Type of Variable, Module 3: Data…

- - - - This type of data is data that was collected for other purposes and becomes useful for what you need it. Secondary data, is search up data records in websites, articles, etc... that can be support primary data. (AS)
  - - - Stratified Random Sampling
        
        Stratified Random Sampling is a method of sampling strata; people who are subdivided into smaller groups based on shared characteristics like education, income, location, age, religion or nationality. (DC)
      - Cluster Sampling
        
        A Cluster Sample is a partition the populace into groups (gatherings) and afterward haphazardly select a portion of the clusters.All the individuals from these groups are in the cluster sample. For instance, assuming that you arbitrarily test four divisions from your school populace, the four offices make up the cluster samples. Partition your school personnel by department.The offices are the clusters. Number every division, and afterward pick four distinct numbers utilizing basic irregular examining. All individuals from the four offices with those numbers are the cluster sample. (SL)
      - Systematic Sampling
        
        Systematic sampling is mostly the one used, because of its simplicity. This is a simple sample, because , to create one you just need to randomly select a starting point and take every nth piece of data from a listing of any thing. (EC)
      - Convenience Sampling
        
        convenience sampling is a type of sampling that has random people selected recruited from open spaces, people that can be easy to have contact with. An example of it will be in public places such as markets, down the street, and any kind of places where you can find people easily. (AS)
      - Judgment Sampling
        
        When the study population includes of extremely intelligent people who cannot be selected using any other statistical or non-probability sampling technique, judgmental sampling is used. Besides the researcher's interests, there are no guidelines for choosing a sample. As a result, he or she can easily contact with the intended audience of their selection and achieve results. Since the members of the sample can have sufficient information and understanding of the subject, a short survey could be completed with people using critical selection. (KF)
    - - Sample Mean: X with a bar over it is used to represent the sample mean, there are many ways to make sure that the sample mean is selected correctly but one of the most important one is to find the most accurate estimate of the Population mean and for it to be taken in the most truly random form. (ZM)
      - Sample Proportion
        
        Sample Proportion means that it depends on the sample of the variable in order to get a close number. With it being a sample it may be difficult to predict. The way to solve this would be dividing x being the count of successes by n being the sample size which will give you the result of P being sample proportion. (A.G)
    - - Finite Population
        
        Finite Population is know as population that can be counted for. In simpler form finite population is the population of all individuals or objects that are finite. In a finite population the number of units are denoted by N where N is the size of the population. (M.H)
      - Infinite Population is the population that cannot be calculated easily. An example of the something that cannot be calculated easily would be the amount of germs inside a sick person. (J.H)
  - - - Ordinal
        
        Ordinal data are the kind of data used in economics where the values are sorted logically. Economic status (poor wealth, midrange wealth, high wage), education level (high school, BS, MS, PhD), and economic status are examples of ordinal variables. (KF)
      - Interval
        
        Data measured using and ordinal scale can be ordered. Responses are ordered by the most desired to the least desired but differences between any two pieces of data gathered cannot be measured. Similar to nominal scale data, ordinal scale data cannot be used in calculations. (M.H)
        
        An interval relationship in Statistics is where there is order and there is a difference between two values, but are meaningful. AN example of this could be the grade an student receives in an SAT test where there 200-800 points. (E. C.)
      - Nominal
        
        Nominal measurement is qualitative and is a category that can have a numerical count. It can be a label, or a name. This type of data can be classified into the groups in which it best fits. (R.F)
      - Ratio
        
        Is data with a starting point that can be ordered; the differences have meaning and ratios can be calculated. (S.L)
    - - An element variable is the individual and/or entity a data set is being collected on, such as persons, vehicle models, animals, ice cream brands (DC)