Binomial conditions<span>fixed number of trials
each trial must be either a success or a fail
trails must be independent
the value of P must remain constant</span>Binomial E(X)npBinomial Var(X)np(1-p)Poisson conditions<span>events must be independent
events must occur singly in space or time
event must occur at a constant rate</span>poisson E(X)£Var(X)£binomial to normal<span>n is large
p is close to 0.5
N(np,np(1-p)
np>10</span>binomial to poisson<span>n is large
p is small
Po(np)
np<10</span>poisson to normal<span>n is large
N(£,£)</span>populationa collection of itemscensusinformation obtained from every member of a populationsamplea selection of indvidual members from a populationpopulation parameterany characteristic of a population which is measurablefinite populationa population in whihc every individual member can be given a numberinfinite populationa population which is impossible to give a number to every individualadvantage censusevery single member of a population is used, unbiased, gives an accurate answerdisadvantage censustime consuming, costly, difficult to ensure that the whole population is surveyeddisadvantage sample<span>natural variation
bias</span>advantage sample<span>sample is representative
cheaper
data more readily avalible</span>poisson<span>events occur randomly
singly in space or time
independently of each other
constant rate</span>binomial<span>fixed number of trials
each trail either a success or failure
trails independent
probability of success constant</span>significance levelprobability of incorrectly rejecting the null hypothesisstatisticrandom variable quantity calculated soley from observations in a sample does not involve any unknown parameters numerical property of a samplesampling distributionall possible values of a test statistic and their probabilitiessampling framea list of all the sampling units within a populationsampling unitsthe individual units of a populationsample surveyan investigation using a samplerandom samplingevery possible sample of size n has an equal chance of being selectedhypothesisa statement made about the value of a population parameternull hypothesishypothesis that is assumed to be correcttest statistica form of a statistic in which the evidence from a sample in a hypothesis test is summarisedcritical valuesthe values on the boundaries
Let’s first make a blank equation in slope-intercept form: y=mx+b
To find the slope, we find the perpendicular slope to 4x+2y-7=0. First, change this to slope-intercept form:
4x+2y=7
2y=7-4x
y=-2x+(7/2)
The slope of this line is -2, so the perpendicular slope will be the opposite inverse, or 1/2. This is the first component.
Second, to find the x-intercept of 2x+3y-12=0, we have to set y=0 and solve:
2x+3(0)=12
2x=12
x=6 or (6,0)
So in total, we need a line with a slope of 1/2 passing through (6,0). Plug this back into y=mx+b:
0=1/2(6)+b
0=3+b
b=-3
So in total, the equation is y=(1/2)x-3.
Answer:
450
Step-by-step explanation:
639 is what percent of 142? = 450.
Answer:
(-∞,∞)
Step-by-step explanation:
The domain is restricted by values where the y value does not exist, like dividing by zero. Since x + 3 exists for all values of x, the domain will be (-∞,∞)
Step-by-step explanation:
hear is your answer please