Understanding Hypothesis Testing

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

Example :
Given a coin and it is not known whether that is fair or tricky so let’s decide null and alternate hypothesis

and similarly, we Toss 6 consecutive time and got the result as all heads, now P-value =
But we set our significance level as error rate we allow and here we see we are beyond that level i.e. our null- hypothesis does not hold good so we need to reject and propose that this coin is a tricky coin which is actually because it gives us 6 consecutive heads.

Error in Hypothesis Testing


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