What is Hypothesis – Troubleinthepeace

What is hypothesis testing?

Hypothesis testing aka Statistical hypothesis testing is a method that helps us to draw general conclusions based on the collected data.

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Take an example: Mr.RJ Ice Cream Bakery just bought a new toaster. The owner wants the baked goods to have an average weight of 30g.

The question is: So will these new machine-baked pies meet his desired requirements? or in other words is the mass of each cake equal to 30 g?

We will take 50 samples of the cake after baking, weigh it and run a Sample T test. This method will help us find the answer.

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Some concepts in Hypothesis testing:

Assumption Ho- Null Hypothesis

Alternative hypothesis Ha- Alternate Hypothesis

In there:

A cough is a statement that assumes that the values ​​are all equal (or is understood to mean that there is no significant difference between the samples).

Ha is a substitute clause for Ho (also known as ). Reject Ho), that is, the values ​​are not equal (or it is assumed that there is a significant difference between the samples).

Specifically, from the above example, we have the following information:

A cough: the cakes are all 30g

Ha: baked goods with a weight other than 30g

Hypothesis Test Errors

In there Alpha is a coefficient set by the user. Value Alpha = 0.05which means we are willing to accept 5% chance (risk) that we were wrong in rejecting Ho. In some cases, the user can choose a larger Alpha like 0.1.

Before going any further into statistical hypothesis testing, we need to note some usage of words in this method.

Sometimes we often say: “Accept the hypothesis Ho”, that is not appropriate. Since this method is not used to conclude the hypothesis is true or false, this method is only used to prove that there is a difference or there is no difference.

What is P-Value (Probability Value)?

P-Value is the value that we will get after running the T-test and using it to draw conclusions.

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The formula is as follows:

Ho: Average weight of cake = 30 g

Ha: Average weight of cake 30 g

P-Value = 0.01 and α = 0.05

With α = 0.05, we allow a 5% chance that we were wrong in rejecting Ho. But in fact we only calculate 1%. That means we are not wrong to refute Ho or in other words must reject Ho

Speaking of this, you may be very confused and confused because Statistical hypothesis testing are essentially negative assumptions of negation.

So there is a little trick to easily remember as follows:

“If P is LOW ….. Ho Must GO!” In other words, if P is low, reject Ho (there is a difference).

“If P is HIGH….Ho’s the Guy!” in other words P High then Fail to reject Ho (no difference)

Next time we will learn together specifically about the methods applied in Hypothesis Testing!

Han Vo