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Understanding Statistics - Essay Example

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Scales of Measurement Scales of measurement determines the criteria for classifying various variables. The scales of measurements are more applicable in the academic and research scenarios as compared to the ordinary life situations…
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Understanding Statistics
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The ordinal scales provide no evident variation amongst the variables. This scale only evaluates the order of the values. The ordinal scales measure the concepts that are not numeric such as fulfillment, jovialness and discomfort among others. In any analysis, an individual can elucidate that number four is better than number three though the extent is not clear again, it is not easy to determine the variation between ok and happy. The interval scales encompass numeric scales that besides providing the order, they also provide the accurate differences between the variables in question. A standard example is the Celsius temperature such as the disparity between 30 and 40 degrees is 10 degrees. Time can also provide precise variations where the disparity between six and four minutes is two minutes. Ratio scales are essential in statistical evaluations to its flexibility for alterations seeking accuracy. The ratio scale can be multiplied, added, divided or subtracted and the central tendency measures estimated. A discrete variable involves well determined set of predetermined set of probable values-states. The variables include the provision that is either “true” or ”false”, the team that will win and the number of dime in a pouch amongst others. Nonetheless, the variables might appear to be discrete at one point and continuous at a different perspective. The continuous variable opts to take on a position between two extreme positions or values. Continuous variables encompass the indoor temperature, direction travelled or the water used. The discrete variable tends to depict a digital quantity whilst the continuous variable tends to be analog in quantity. According to the explanations provided on the above scales, the different statistical research studies can select any of the according to suitability for application. The continuous and the discrete variables have significance on the selection of the research methodologies to use since the experimental method would be appropriate with discrete data whilst the researches dealing with conventional aspects might find it appropriate to employ continuous variables in the research activity. The area under the normal distribution is proportional to the overall area. The total area covered in the normal curve is equivalent to one. The curves never attain the situation Y = 0 but move to the positive infinity and the negative infinity. The shape assumed by the normal curve is infinite and depends on the mean and the standard deviation. The z-score is a critical tool in data evaluation and is used to determine the extent to which a point x is high or below the population mean ?. It is the providence of the T-statistic with predetermined mean and the standard deviation. In case of interference with the degree of freedom to an extent of assuming population mean and the standard deviation from the availed sample, then it fails to be T-statistic. The percentile rank of a normally distributed population can be estimated readily through the use of z- scores. In the e vent that the area under a curve is apportioned above and below the mean, the partitions obtained are the similar to the probability picking a value in the similar range. For instance, the area between the standard deviation above and below t ...Download file to see next pagesRead More
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