Study Notes on Hypothesis Testing (Part II)

By Mohit Choudhary|Updated : February 28th, 2022

UGC NET Exam is conducted twice a year by NTA. There are ten units in Paper-1 and each unit has equal weightage in the examination. Most Important Topics in UGC NET Environment, Logical Reasoning, Teaching Aptitude, Research Aptitude, Communication, ICT, Higher Education.

In the previous post 'Study Notes on Hypothesis Testing Part I', you got to know about the nature of the Hypothesis test and now you will learn about the process involved in Hypothesis testing. 

Process of Hypothesis Testing

Testing of a hypothesis is done by using statistical methods. Testing is used to accept or reject an assumption or hypothesis about a random variable using a sample from the distribution. 

  • The assumption is the Null hypothesis (H0 ), and it is tested against some Alternative hypothesis (H1 )
  • Statistical tests of the hypothesis are applied to sample data. 
  • The procedure involved in testing a hypothesis is 

        A) select a sample and collect the data. 

        B) convert the variables or attributes into a statistical form such as mean, proportion.

        C) formulate hypotheses. 

        D) select an appropriate test for the data such as t-test, Z-test. 

        E) perform computations. 

        F) finally draw the inference of accepting or rejecting the null hypothesis. 

Let’s try to understand the process of Hypothesis testing with the help of an example :  

Assume that a radio station selects the music it plays based on the assumption that :

‘the average age of its listening audience is 30 years’. 

To determine whether this assumption is valid, a hypothesis test could be conducted with the null hypothesis as 

Null hypothesis (H0): µ = 30 and 

Alternative hypothesis as H1: µ ≠ 30.

  • Based on a sample of individuals from the listening audience, the sample mean age, ‘X’, can be computed and used to determine whether there is sufficient statistical evidence to reject H0. 
  • Conceptually, a value of the sample mean that is “close” to 30 is consistent with the null hypothesis, while a value of the sample mean that is “not close” to 30 provides support for the alternative hypothesis. 
  • What is considered “close” and “not close” is determined by using the sampling distribution of ‘X’.
  • Ideally, the hypothesis-testing procedure leads to the acceptance of H0 when H0 is true and the rejection of H0 when H0 is false. 
  • Unfortunately, since hypothesis tests are based on sample information, the possibility of errors must be considered.

Hope you guys now have a better understanding of the topic of Hypothesis testing. If you have any other queries, please comment.

Thank you!

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