Study Guides (248,223)
Canada (121,413)
Statistics (35)
STAT 263 (15)
Final

finalformulaesheet1_7.pdf

4 Pages
150 Views
Unlock Document

Department
Statistics
Course
STAT 263
Professor
Charles Arthur Molson
Semester
Winter

Description
STAT 263 Formulas (these pages, and tables printed with exam) V 1.7.2a 3(meamedian) p SK = standard deviation indexp percentile () +1 100 x−µ xx− IQR = Q3− Q1 z = σ or z = s s σ CV =⋅ 100% or =C⋅V 100% Coefficient of Variation: x µ 1 Chebyshev's Rule: at leak2 of the data fall withink standard deviations of the mean j Median for grouped data (similar for any fractile):≈+c f Where L is the lower boundary of the class into which the median must fall, f is the frequency of this class, c is the class interval, and j is the number of values we still lack when we reach L. = PA )≥ 0 for any eAt ; A ( ) 1 for any vent P; (φ) P0; PA( ) ( ) 1 If A and B are mutually exclusive events, then P(A ∪B)=P(A)+P(B). If k events are mutually exclusive, then P(A1∪ A 2 A ∪3…. ∪ A )=k(A )+1(A ) 2…+ P(A ) k It is always true that: P(A ∪B)=P(A)+P(B) - P(A ∩ B) If P(B) is not equal to zero, then: P(A) ∩ P(BA ) = PB() If A and B are independent: P(A) = P(A|B) and P(A ∩ B) = P(A) P(B) It is always true that: ( A ∩B ) P ( B = )P( ) P ( A P ) ( ) P(APA ) ( ) Bayes’ Theorem: PA() = PB()A PBA()A + () ′ () ′ P(at least one success) = 1 – P(zero successes) If the probabilities of obtaining the amounts a , a , a , … , or a are p , p , p , … , and p , 1 2 3 k 1 2 3 k where 1 + 2 + 3 + … + pk= 1, then the mathematical expectation is1 1= a 2 2 a p + k ka p x n – x 2 Binomial : f(x) n x p (1 – p) for x = 0, 1, 2, …, or n,p, σ =np(1 − p) Hypergeometric : PX x == f x abxnx − for x = 0, 1, 2, …, or n; x < a, (n – x) < b ab n −λ x ) () == f = e λ Poisson: x! , µ =λ pen () x Poisson Approx. to the Binomial P(X x )f x ( ) assupmes n 10, 100 x! Z = x−µ Normal distribution: σ Sampling distribution for means – infinite population: σ σ x − µ x − µ µ σ = = =σ = = X X Z x X X X X n n σ x σ n Sampling distribution for means – finite population: σ X Nn − EX() =µµX X EX () σ X n N −1 Finding the sample size in estimation of means situations: 2 ⎡⎤zα⋅σ ⎢⎥ 2 σ Formula in text:n =⎢⎥ or use α E 2 n ⎣⎦ Estimating µ, σ known, (1 − α)·100%, (large sample case , use s for σ if σ not known): σ σ σ xZ− α α≤ ≤+xµ µ α equivale=±tto: 2 2n n 2 n Estimating µ, σ unknown, (1 − α)·100%, (small sample case): s s s + ≤xt ≤ α ±α xt µ α equivalentxto: n−1,2n−2 n n−, 2n 2 2 2 )1s− − )( 1n2 Estimating
More Less

Related notes for STAT 263

Log In


OR

Join OneClass

Access over 10 million pages of study
documents for 1.3 million courses.

Sign up

Join to view


OR

By registering, I agree to the Terms and Privacy Policies
Already have an account?
Just a few more details

So we can recommend you notes for your school.

Reset Password

Please enter below the email address you registered with and we will send you a link to reset your password.

Add your courses

Get notes from the top students in your class.


Submit