What are the major statistical concepts found in data science?

Data science is an important discipline in statistics that is used in data cleaning. The use of statistics involves collecting and structuring data. This eventually helps in converting raw inputs to machine learning algorithms. Different statistical methods are beneficial to calculate the numerical value, like variance, mean, probability and distribution. Some students find statistics and maths difficult to understand. And this is why do my assignment aim to provide proper guidance to such students. You can find enough resources on their website that is reliable and easy to understand.

A few of the primary statistical concepts of data are-

• Probability

Probability is the basis of data science which helps you in predicting real-life scenarios. If you want to pursue a career in data science understanding the concept of predictions and estimates are must. Also, working as a data scientist probability becomes a guide to examine and predict random phenomena, data and the occurrence of unwanted events.

• Population and sampling

These are the two types of data that are used in performing statistical testing. The population represents the entire data set that is available for analysis. Similarly, the sample is the subset of the population data. You can distinguish population as finite, infinite, existent and hypothetical population. Population data can be costly and time-consuming. In addition to this, the process of selecting a sample from a population is known as sampling.

• Data distribution

You might have noticed the shape that is placed on the graph. It happens when you plot each value on the data set on a frequency graph. Data distribution can be of three types normal distribution, positive skewness and negative skewness. You see a normal distribution when the distribution of data is symmetric and forms a bell-shaped curve. In a positively skewed distribution, the graph contains a tail on the right and large data points on the left. And the negatively skewed distribution is the reverse of the positively skewed distribution.

• Measures of central tendency

The regulation of a single value for an entire data set is termed as measures of central tendency. The central tendency can help you deduce an accurate understanding of an entire distribution. In central tendency, you will find three important measures such as mean, median and mode.

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