Hypothesis Testing Flashcards
Hypothesis testing formula for standard normal (SLIGHTLY DIFF)
Z = Xbar - μ / (√σ²/n)
~N(0,1)
What happens when we replace σ² with a sample estimator
Swap it for s² and becomes a T distribution not Z! Which mean degrees of freedom changes to T(n-1)
Error 1 in hypothesis testing, and notation for the probability of it occuring
Rejecting a hypothesis when it is true.
Notated by ∞
Error 2, and its notation.
Not rejecting a false hypothesis
Notation - β (probability of making error 2)
So how to reduce type 1 error?
Keep level of significance ∞ low e.g 0.05 (5%) , effectively meaning we are prepared to accept a 5% chance of committing a TYPE 1 ERROR
Technical appendix for properties of the expected value operator (5)
What are we assuming
Assuming a and b are constants
- E(a) = a e.g E(Xbar) = Xbar
- E(ax) = aE(X) i.e we can take constants out the bracket
- E(aX+b) = E(aX) + E(b) = aE(X) + b (Upholds 1st property)
- E(X+Y) = E(X) + e(Y)
- 𝐸(𝑋𝑌) ≠ 𝐸(𝑋)𝐸(𝑌) unless 𝑋 and 𝑌 are independent
Properties of variance
What assumption do we have to make
Assume a and b constant
- Var(b) = 0 as b is a constant and its value does not change
- Var(X+b