Last Updated on by Kumar Raja

## Prominent Concepts in Statistics for Budding Data Scientists

The prominence of Statistics in Data Science must be clearly aware to everyone. Statistical Modeling in Data Science helps Data Scientists to better understand the data in hand. If you are a Data Science career enthusiasts who’s looking forward to learn Data Science then, developing statistical skills prior to joining the course becomes very crucial. If you are not sure about how to get started with the process of developing skills in Statistics & if you wish to learn Data Science from the scratch, then this Data Science Training in Hyderabad program can help you in this regard.

Now, let’s look at the prominent concepts in Statistics that you need to master to become a successful Data Scientist.

• Normal Distribution

This technique in Statistics is mainly sued to for representing medical findings. The graphical representation of normal distribution would be taking up the shape of a bell-shaped curve.

The best examples of the cases where Normal Distribution can be used are

• To obtain the average birth weight of all the newborns around the world.
• You can predict the returns you can expect on a particular stock by analyzing the historical data.
• Poisson Distribution

This form of technique in Statistics can be used to make accurate forecast how many number of events could occur over a specific period of time. This form of approach becomes handy when dealing with large volumes of discrete data where there is a less probability of occurrence of an individual event.

• Binomial Distribution

This form of Statistical technique is used in the condition where there’s one needs to find the likely hood of pass or fail outcomes in an experiment. This technique would be apt in the cases where True/False or Yes/No the only possible outcomes are

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