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Tests of significance are the process of analyzing a particular conclusion in order to accept or deny the claims based on the sample data. Statistics is a branch of mathematics that deals with arithmetic calculation and collection of data. The significance of testing not only deals with data collection in math but it is widely used in the field of psychology, biology, medical field, etc. Test of Significance is a process of reaching a conclusion to accept or reject the results obtained by the collection of data. There are various processes by which significance can be tested. This particular process is called the significance test.
Read More: Concepts in Statistics and Probability
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Key Takeaways: Test of Significance, P value, Null hypothesis, Type I error, Type II error.
Test of Significance
When an experiment takes place, it is important to know the outcome which is significant or not. There is a need to assume the value or significance of the result. In this case, some predefined tests are used. The tests which are used for the purpose are known as tests of significance or significance tests. When the tests are done they sometimes fall to some degree of error. The researchers sometimes have to analyze the probability of sampling error in advance so as to avoid the errors. The significance testing is important for research in the field of statistics.
P-value is basically a level of significance testing. At this level, the tests are accepted only when the given experiment is statistically measurable.
P- Value Testing
In this context of statistical significance of data, the p-value is an important term in the test of hypothesis. This is a function of observed sample results of the experiments which happen. A value i.e known as threshold value should be taken before the test or experiment is performed. This threshold value is called the significance level. It is mainly 1% or 5%. It is represented by the letter α.
The sample data is said to be inconsistent when the p-value is smaller than the significance level i.e.(α). At this time, the null or inconsistent outcome has to be rejected. To make it correct, there should be another hypothesis accepted. It should be kept in mind that when the p-value is small, then the significance value will be bigger. When the value of p will be measured accurately in an experiment then the type I error may not become greater than (α).
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Steps for Tests Significance
There are some processes through which significance testing is done in order to reach the result. Hence, the process of significance testing is given below.
- Hypothesis for Research is given in the test.
- Null Hypothesis is explained.
- Selection of the Probability of Error Level.
- Selecting and Computing a Statistical Significance Test.
- Interpreting the results of the data.
Types of Error
When the significance testing is done, we sometimes get two types of errors. It can be said that there are two types of error in statistics.
Type I Error: Type I error happens when the researcher gets the result analyzed on the basis of a research hypothesis which can exist. Whereas in real life, there are some proofs that it does not exist. Entirely the researcher has to finally reject the outcome and also have to accept the null hypothesis. Hence, the probability, in this case, is represented by alpha (α).
Type II Error: It is just the reverse of the first one. This error happens when it is analyzed that a relationship does not exist. Whereas in reality it surely exists. The researcher is supposed to accept the hypothesis of research and have to reject the null hypothesis. But he does just the opposite of the hypothesis. This is represented by the symbol beta (β).
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Things to Remember
- Test of significance is a method of reaching a conclusion to accept or reject the results obtained by the collection of data or in an experiment.
- The p- value testing is an important part of the test of hypothesis.
- There are some processes for the occurrence of significance testing.
- It is not only used in the field of mathematics but widely used in the medical field, psychology, biology etc.
- There are two types of error based on the outcome of an experiment. Type 1 Error and Type 2 Error.
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Sample Questions
Ques. What is the significance of the test? (2 marks)
Ans. The significance of the test is a process in which claims are analyzed after the collection of the sample data. This is done after a series of test procedures.This is called a test of significance. In the process, researchers get conclusions about the experiment.
Ques. What do you mean by statistics? (2 marks)
Ans. Statistics is the branch of mathematics which deals with the collection, analysis, presentation, observation of numerical data. In simple words, it is a process of collecting, organizing the data in a proper format. This is known as statistics.
Ques. Define p- value testing. (2 marks)
Ans. In the test of significance, the p-value is the outcome of the probability. There is a slight difference that could be observed in case of random chance. Here, the p- value is small when the statistical significance is larger than p - value.
Ques. Mention the two types of hypothesis in the statistical significance. (2 marks)
Ans. Basically, there are two types of hypothesis can be seen in the tests. They are given below. The first one is Null Hypothesis which comes under the category where it doesn't have any difference. Whereas the second one is known as Alternative Hypothesis which acquires a significant difference.
Ques. Write the disadvantages of using the test of significance. (2 marks)
Ans. There are some disadvantages of using significance testing. Like it doesn't give the result exactly. Because the sample data is collected through chance.
Sometimes it doesn't give good outcomes if only the sample size of the data is small. The Null Hypothesis can be also wrong at some points.
Ques. What are the two types of error? (2 marks)
Ans. There are two types of error in the test of significance. They are discussed below.
- Type 1 Error - In this test whenever an error is found,then the researchers should reject the hypothesis on research and Null Hypothesis should be accepted but here the reverse is done by them.
- Type 2 Error - This is just the opposite of Type 1 error. In this case, the hypothesis of research should be accepted whereas the Null hypothesis should be rejected.But also vice versa happens.
Ques. In which fields the significance testing is performed? (2 marks)
Ans. The series of tests are applied not only in the field of mathematics but also used widely.It is almost used in various fields like, medical department, Psychology, biology department and many more.
Ques. Write the types of Statistical tests. (2 marks)
Ans.There are mainly two types of tests which are given below.
So the first is One-tailed and the other one is two-tailed. These two types of statistical tests are performed in a choosing pattern. This is done for the computation and organization of the data. They are also known as one-sided and two-sided tests.
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