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Statistics and Its Uses in Making Data Evaluation Simpler

We are faced with innumerable queries on a regular basis. What is our daily calorie intake? How many hours did we spend on traveling in a week? How much time did we spend at home? The list goes on. The answers to these questions are extremely difficult to figure out accurately since we can hardly keep track of time and other minute entities like calories intake so specifically. This is when statistical analysis is recruited.

Statistics comprises of a number of tools that does the most important job of arranging data and evaluating them. The most basic statistical tools are mean or the average of a set of data, median, mode, regression, correlation, etc. Techniques like standard deviation, relative standard deviation, calculation of percentile and so on. Questions like find the values of the 30th and 90th percentiles of the data 129 113 is commonly asked in tests.

Statistical analysis plays noteworthy roles in conducting medical surveys such as evaluating the extent to which diabetes diagnosed individuals have increased in a particular geographical boundary.

Detailed analysis of statistical tools and techniques

The most important requirements before proceeding with any statistical analysis are mentioned below-

  • Acquiring samples and data is the first step. To establish a well-analyzed conclusion, obtaining necessary data is the very first requirement.
  • Organization of the acquired data is the next in line for the to-do list. Following these steps while studying statics has helped me a great deal to solve elaborate problems. I would recommend budding students to opt for a systematic approach such as this to develop a clear understanding of this subject.
  • To conclude on a mass survey the detailed study of samples and populations is necessary.

Here some of the most commonly recruited statistical tools and techniques-

  • Mean

Mean or the arithmetic mean of a data sample is the average of that particular set. For instance, in the case of a clinical survey, it must be used to find the average age of an individual at which the symptoms genetic health disorders like cholesterol or diabetes tend to reflect.

  • Calculation of percentile

The percentile of a data is often denoted by “k” and has to range from zero to hundred. To calculate the percentile of a series of figures, they are firstly arranged in the ascending order following which the “k” is multiplied by the total number of values present in the set.

The obtained value is denoted as If the obtained number is not a whole number it is rounded up to the nearest whole number. The next step is to start counting the series from smallest to the largest until the number calculated from the above-mentioned step is reached. The corresponding number is the “kth” percentile of the set.

Likewise, when asked to find the values of the 30th and 90th percentiles of the data 129 113, students can easily solve it following the above-mentioned steps.

To make calculation simpler, statistical analysis is opted for almost always. It helps to understand numerical information and assist in representing them as comprehensible forms. Statistics is a vast subject and has important roles in all other major disciplines and only with dedicated involvement with it, one can fathom its diverse nature.

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