Purpose of Null hypothesis?
I understand what it is but do not understand why it is needed.
I have read if you do not have one, and just have the alternative hypothesis, then there are so many possibility's that could cause the relationship between the variables. But if you collect data that proves the null hypothesis wrong then it doesn't necessarily suggest the alternative hypothesis is right and cant you come to the same conclusion as you would do without the null hypothesis (i.e it does/does not support your alternative hypothesis)? If you can prove the null hypothesis wrong with 95% certainty then why cant you prove the alternative hypothesis right/wrong with X amount of certainty?
Any help would be greatly appreciated, thanks!
I have read if you do not have one, and just have the alternative hypothesis, then there are so many possibility's that could cause the relationship between the variables. But if you collect data that proves the null hypothesis wrong then it doesn't necessarily suggest the alternative hypothesis is right and cant you come to the same conclusion as you would do without the null hypothesis (i.e it does/does not support your alternative hypothesis)? If you can prove the null hypothesis wrong with 95% certainty then why cant you prove the alternative hypothesis right/wrong with X amount of certainty?
Any help would be greatly appreciated, thanks!
(edited 10 years ago)
You're supposed to set the alternate hypothesis such that if the null hypothesis is false, the alternate hypothesis must be true. For example, if you're trying to investigate whether a group differs from another in some way (ie. IQ)
Null: Group 1's average IQ = Group 2's average IQ
Alternate: Group 1's average IQ =/= Group 2's average IQ.
(Bear in mind that you can't actually prove or disprove the null hypothesis, only reject or accept it based on how likely it is to be true or false)
Null: Group 1's average IQ = Group 2's average IQ
Alternate: Group 1's average IQ =/= Group 2's average IQ.
(Bear in mind that you can't actually prove or disprove the null hypothesis, only reject or accept it based on how likely it is to be true or false)
(edited 10 years ago)
But if you collect data that suggests your null hypothesis wrong, so favouring the alternate hypothesis, why can't you just not have a null hypothesis and then the data would still support the alternate hypothesis?
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