Hypothesis are statement about the given problem. Hypothesis testing is a statistical method that is used in making a statistical decision using experimental data. Hypothesis testing is basically an assumption that we make about a population parameter. It evaluates two mutually exclusive statements about a population to determine which statement is best supported by the sample data.
Example:
You say an average student in the class is 30 or a boy is taller than girls. All those are an example in which we assume or need some statistic way to prove those. We need some mathematical conclusion whatever we are assuming is true.
Need for Hypothesis Testing
Hypothesis testing is an important procedure in statistics. Hypothesis testing evaluates two mutually exclusive population statements to determine which statement is most supported by sample data. When we say that the findings are statistically significant, it is thanks to hypothesis testing.
Parameters of hypothesis testing

Null hypothesis(H0): In statistics, the null hypothesis is a general given statement or default position that there is no relationship between two measured cases or no relationship among groups.
In other words, it is a basic assumption or made based on the problem knowledge.
Example: A company production is = 50 unit/per day etc. 
Alternative hypothesis(H1): The alternative hypothesis is the hypothesis used in hypothesis testing that is contrary to the null hypothesis.
Example : A company production is not equal to 50 unit/per day etc. 
Level of significance
It refers to the degree of significance in which we accept or reject the nullhypothesis. 100% accuracy is not possible for accepting a hypothesis, so we, therefore, select a level of significance that is usually 5%. This is normally denoted withand generally, it is 0.05 or 5%, which means your output should be 95% confident to give similar kind of result in each sample. 
Pvalue
The P value, or calculated probability, is the probability of finding the observed/extreme results when the null hypothesis(H0) of a study given problem is true. If your Pvalue is less than the chosen significance level then you reject the null hypothesis i.e. accept that your sample claims to support the alternative hypothesis.
Example :
Given a coin and it is not known whether that is fair or tricky so let’s decide null and alternate hypothesis
 Null Hypothesis(H0): a coin is a fair coin.
 Alternative Hypothesis(H1) : a coin is a tricky coin.

=  Toss a coin 1st time and assume that result is head Pvalue =
(as head and tail have equal probability)  Toss a coin 2nd time and assume that result again is head, now pvalue =
Now let’s toss the coin and calculate pvalue (probability value).
and similarly, we Toss 6 consecutive time and got the result as all heads, now Pvalue =
But we set our significance level as
Error in Hypothesis Testing
 Type I error: When we reject the null hypothesis, although that hypothesis was true. Type I error is denoted by alpha.
 Type II errors: When we accept the null hypothesis but it is false. Type II errors are denoted by beta.
Recommended Posts:
 ML  Understanding Hypothesis
 The Lottery Ticket Hypothesis
 Understanding "register" keyword in C
 Understanding Logistic Regression
 ML  Understanding Data Processing
 Understanding Tensor Processing Units
 Understanding Types of Means  Set 1
 Understanding Types of Mean  Set 2
 Understanding different Box Plot with visualization
 Understanding Activation Functions in Depth
 OpenCV  Understanding Brightness in an Image
 Understanding of LSTM Networks
 Understanding BERT  NLP
 Understanding GoogLeNet Model  CNN Architecture
 Analysis required in Natural Language Generation (NLG) and Understanding (NLU)
 Understanding PEAS in Artificial Intelligence
 Basic Understanding of CURE Algorithm
 Basic Understanding of Bayesian Belief Networks
 Basic understanding of JarvisPatrick Clustering Algorithm
 Understanding Auxiliary Classifier : GAN
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.