data science basics.docx - Basic Concepts of Data Science:...

Basic Concepts of Data
Science: Technical Concept
Every Beginner Should Know
Data Science is the field that helps in extracting meaningful insights from data using programming
skills, domain knowledge, and mathematical and statistical knowledge. It helps to analyze the raw data
and find the hidden patterns.
Therefore, a person should be clear with statistics concepts , machine learning, and a programming
language such as Python or R to be successful in this field. In this article, I will share the basic Data
Science concepts that one should know before transitioning into the field.
Whether you are a beginner in the field or want to explore more about it or you want to transition into
this multifaceted field, this article will help you understand Data Science more by exploring the
basic Data Science concepts .
Statistics Concepts Needed for Data Science
Statistics make a central part of data science. Statistics is a broad field that offers many applications.
Data scientists must know the statistics very well. This can be inferred from the fact that statistics help
to interpret and organize data. The descriptive statistics and knowledge of probability are must-
know data science concepts .
Below are the basic Statistics concepts that a Data Scientist should know:
1. Descriptive Statistics
Descriptive statistics help to analyze the raw data to find the primary and necessary features from it.
Descriptive statistics offers a way to visualize the data to present it in a readable and meaningful way. It
is different from inferential statistics as it helps to visualize the data in a meaningful way in the form of
plots. Inferential statistics, on the other hand, help in finding insights from data analysis.
2. Probability
Probability is the mathematical branch that determines the likelihood of occurrence of any event in a
random experiment. As an example, a toss of a coin predicts the probability of getting a red ball from a
bag of colored balls. Probability is a number whose value lies between 0 and 1. The higher the value,
the event is more likely to happen.
There are different types of probability, depending upon the type of event. Independent events are the
two or more occurrences of an event that are independent of each other. Conditional probability is the
probability of occurrence of any event having a relationship with any other event.

3. Dimensionality Reduction
Dimensionality reduction means reducing the dimensions of a data set so that it resolves many
problems that do not exist in the lower dimension data. This is because there are many factors in the
high dimensional data set and scientists need to create more samples for every combination of features.