I'm new to statistics. I have some basic question on hypothesis and Type-I and II errors. I'm posting two scenarios on the same topic below. Need your help to get some knowledge on the 2nd scenario

**Scenario-1:**

Let us say

**Null Hypothesis:**

**Ho: I don't have covid**

But due to government terms and conditions, I'm giving my blood sample for testing. Based on the test results, below is the type-I and type-II errors

**Type-I error: Rejecting the true null hypothesis**

Test result says - I have covid but in reality I don't have. This is False positive

**Type-II error: Accepting the False null hypothesis**

Test result says - I don't have covid but in reality I have. This is False negative

I'm pretty clear about this scenario

**Scenario-2:**

This is the one which I'm not able to understand. Please help

This is the one which I'm not able to understand. Please help

Let us say

**Null Hypothesis: Ho: I have covid (Just opposite to Scenario-1)**

But due to government terms and conditions, I'm giving my blood sample for testing. Based on the test results, below is the type-I and type-II errors

**Type-I error: Rejecting the true null hypothesis**

Test result says - I don't have covid but in reality I have.

**Can we call this as False positive ? Logically speaking this is False negative rite ? Please advise**

**Type-II error: Accepting the False null hypothesis**

Test result says - I have covid but in reality I don't have.

**Can we call this as False negative ? Logically speaking this is False positive rite ? Please advise**

As per Hypothesis rule, Type-I error is called False positive and Type-II error is called False negative. That is the reason Scenario-2 is confusing for me. Please advise