499 WordsFeb 25, 20122 Pages

Week7
Sample size > 30 Approximately Normal (Central Lt Theorem)
S = ∑(X - µ)2 / √(n-1)
STDEV not P
±σ = 68.6% (For Z scale it will be 1Z, 2Z, 3Z 0,1 σ = 1)
±2σ = 95.4%
±3σ = 99.74%
Even if the distribution isn’t normal, sampling distribution (X) will be normal
(Std of mean error) σx = σ/√n
E(X) and E(Xbar) = µ n α 1/σ n σ Concentration around the mean (More precise)
Estimation = Confidence interval % CI α Z (Z – Confident statement) Margin of error = ±Z σ/√n Z = NORMINV([1+CP]/2, 0, 1) – std normal [1+CP]/2 = 0.5 + CP/2 [Left half + Rem] α – Error % α% times the mean of a sample will be outside the interval (CI) n/N < 0.1 correction can be ignored t – Population std not known =TINV(α, n-1) Confidence level α margin of error
Infinite Population 1. Normal Method (Using Eqn)
(i.e) (X – Z σx) < µ < (X+ Z σx), where σx = σ/√n
[Note: The mean, std is 0,1. Even if µ and σ are given]
(or)
Z = NORM.INV( [1+CL]/2,0,1)
2) Excel Method
[probability (Area-α), Mean (Pop), standard (sample)]
Finite Population 1) Sample size (n > 30)
2) Sample size (n < 30)
Population percentage interval (Percentage) p = x/n (x – No of bad/good___) P – success% as per our definition Normal method p – Zσp < ᴨ < p + Zσp Excel Method Lower Lt =NORM.INV(α/2, p, σp)
Upper Lt =NORM.INV(1-[α/2], p, σp)
Mention the rational 4 method upfront
Z – no pop σ; n>30 by central Lt theorem, Z theorem can be used
Week 8
Believe µ is real mean & build a model & Test ur model by comparing the sample with it
Take α% risk upfront (Type1 error – Alpha error)
α = P(Reject H0 | H0 is true) = risk
t function in excel is always a 2 tail test – for 1 tail test (Left or Right) use 2α
Population percentage interval P = µO

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