Provide a thorough response to the two following

rhedynogh0rp

rhedynogh0rp

Answered question

2022-03-28

Provide a thorough response to the two following questions.
1. What is hypothesis testing? Provide all basic components, including error types, with explanations.
2.What is the difference between chi-square goodness of fit and chi-square test of independence? What do they have in common?

Answer & Explanation

Jamie Maldonado

Jamie Maldonado

Beginner2022-03-29Added 10 answers

Hypothesis is the statement or assertion about certain parameters of statistical distribution. It can be said that hypothesis is a claim to be tested. 
There are two types of hypotheses as, null hypothesis and alternative hypotheses. 
Null hypothesis : The hypothesis with no difference is called as null hypothesis, denoted by H0. 
Alternate hypothesis: The hypothesis to be accepted in case of rejection of null hypothesis is the alternate hypothesis. 
Steps in testing of hypotheses are: 
1. Set null and alternate hypothesis.
2. Choose appropriate test statistic. 
3. Compute numerical value of the test statistic. 
4. Calculate critical value or p-value. 
5. Provide appropriate result according to critical value and p-value at provided level of significance.
While testing the hypothesis one can commit two types of errors as type I error and type II error. 
 Actual  Decision   Situation  Reject H0 Accept H0H0 is True  Type I error  Correct Decision H0 is False  Correct Decision  Type II error 
Type I error : Rejecting H0 when it is true.
Type II error : Accepting H0 when it is false.
For given data, when one try to fit some probability distribution. Since there are many probability distributions which distribution will fit appropriately is the question of interest, in these cases chi-square test for goodness of fit is used. The degrees of freedom while testing the goodness of fit is (k-p-1) where k are number of observations, p is number of pooled observations. 
For the chi-square test of independence data is segregated according to categories by obtaining a contingency table. It follows chi-square distribution with degrees of freedom as (r-1)(c-1) where r is number of rows and c is the number of columns. 
Both situation follows chi-square distribution but degrees of freedom changes according to type of the test.

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