Chi-Squared Test Where Continuous Data Has Been Transformed Into Categorical Data
Using Continuous data as categorical
Statistical analysis can provide a robust approach to assess data, using the raw data to generate useful results which may provide insights into the phenomena being examined. For the results to be meaningful and useful it is essential that the most appropriate method tests are utilized (Bryman & Bell, 2011). In the research undertaken by Razmjou et al., (2009) a decision way made to transform one type of variable, changing it from a continuous variable into a categorical variable. BMI, which is a continuous variable, was changed into categories of normal, overweight, and obese (Razmjou et al., 2009). Usually, transforming continuous data into categorical data results in a loss of detail, so is usually ill-advised, but in some circumstances may help to more useful data (Bryman & Bell, 2011). The circumstances under which continuous variables may benefit from being transformed into categorical variables include conditions under which there may be nonlinearity, for example the presence of a quadratic or exponential curve upwards or downwards, or when you may be a floor threshold effect, or ceiling effect (Bruce, 2009).
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Their pricing approaches, while in the boundaries of solid statistical analysis, are somewhat opportunistic. For Zillow to be more accurate, the use of a range of valuations for each property could be included. This would be more realistic to the true conditions of the market. Finally, the methodology used for this analysis is based on the latest 30 home sales; therefore the data itself and analysis are much timelier
Statistical Analysis Reported in Two Journal Articles Research endeavors, albeit it clinical, empirical, descriptive, historical, or case study oriented, must at all times adhere to the rigors of effective or best-fit research practice. Without stringent controls placed on the area of investigation no research endeavor will advance any body of knowledge. To this end all research must be finely tuned and described as to intent or purpose, phenomenon to be
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health care centers (PHCC) in Stockholm County, 40 of them were randomly selected using an old-fashioned, non-probability method of basically drawing names from a hat. The author notes, "every PHCC was given a unique number that was written on a paper card and placed in a pot. For transparency, two colleagues independently drew 20 paper cards each, a total of 40." Of these 40, one declined to participate. Therefore,
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