To understand the statistics from a holistic point of view, every student should understand the two broad branches of statistics. Often, the types of work we do hide many aspects of statistics. However, it is essential to understand the whole idea of statistical analysis for you to feel the beauty of it. The two branches of statistics are descriptive statistics and inferential statistics. All these branches of statistics follow a specific scientific approach which makes them equally essential to every statistics student.

Descriptive StatisticsDescriptive statistics is considered as the first part of statistical analysis which deals with collection and presentation of data. Scientifically, descriptive statistics can be defined as brief explanatory coefficients that are used by statisticians to summarize a given data set. Generally, a data set can either represent a sample of a population or the entire populations. Descriptive statistics can be categorized into

Measures of central tendency Measures of variabilityTo easily understand the analyzed data, both measures of tendency and measures of variability use tables, general discussions, and graphs.

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Measures of Central Tendency

Measures of central tendency specifically help the statisticians to estimate the center of values distribution. These measures of tendency are:

**Mean**

This is the conventional method used in describing central tendency. Usually, to compute an average of values, you add up all the values and then divide them with the number of values available.

**Median**

This is the score found at the middle of a set of values. A simple way to calculate a median is to arrange the scores in numerical orders and then locate the score which is at the center of the arranged sample.

**Mode**

This is the frequently occurring value in a given set of scores.

Measures of VariabilityThe measure of variability help statisticians to analyze the distribution spread out of a given set of data. Some of the examples of measures of variability include quartiles, range, variance and standard deviation.

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The different types of calculation of inferential statistics include:

Regression analysis Analysis of variance (ANOVA) Analysis of covariance (ANCOVA) Statistical significance (t-test) Correlation analysisAt nlinux.org, we duly understand that statistics can be challenging especially due to the complex formulae involved. However, that should not stress you anymore with unreliable statistics math help. We are here to offer the most affordable and reliable "pay someone to do my homework" services.

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