Stats 151 - Sample Distribution and Probability in Normal Distribution

Descrição

Chemistry 101 Stats 151 FlashCards sobre Stats 151 - Sample Distribution and Probability in Normal Distribution, criado por jennabarnes12387 em 24-02-2014.
jennabarnes12387
FlashCards por jennabarnes12387, atualizado more than 1 year ago
jennabarnes12387
Criado por jennabarnes12387 mais de 10 anos atrás
38
1

Resumo de Recurso

Questão Responda
if a school has a GPA of 2.8 and a standard deviation of 0.8 what percent of students have a GPA less then 2? greater then 3? P(x< or equal to 2) = P(Z < -1) = 0.1587 P(x>3) = P(Z>0.25)=1-P(X< of equal to 0.25) = 1-0.5987 = 0.4013
between 2 and 3? - P(2<x<3) = P(-1<Z<0.25)P(Z < 0.25) – P(Z<-1)0.5987 – 0.1587 = 0.4400
What is the minimum GPA needed to be in the top 10% creates two areas, 0.1, and 0.9. find the Z score for 0.9 which is 1.28 and then use to solve for x in the equation Z = x-u/sigma
what is a normal probability plot? a scatter plot of the normal Z score pairs
how do you find the Z score pairs? order the data from smallest to largest. then us table 3 to find the normal sores using the z scores. then plot the data (z,x)
the mean of X is always equal to____ no matter the width of the distribution? x bar
what is parameter? a number calculating a population and describes the characteristics of a population
what is a statistic? a number calculated from and describing the characteristics of a sample
how do we find x bar? u, sigma/ square root of n
the avergae adult weight is 175 pounds with a standard deviation of 25 pounds. an elevator has a weight limit of 10 people or 2000 pounds. What is the probability that the ten people who get on an elevator exceed the weight limit? P(overload) = x1 + x2 + ………x10 > 2000 pounds = X1 + x2 + ……….. x10 / 2 = 2000/10 = 200. the Z score for 200 is 3.16. 1-p(z < or equal to 3.16) = 0.9992 = 0.0081-p(z < or equal to 3.16) = 0.9992 = 0.008

Semelhante

Statistics 151 - Data Collection
jennabarnes12387
Stats 151 - Z-Scores
jennabarnes12387
Stats 151 - Mean, Standard Deviation, and Empire Rule for Random Variables and Binomial Distribution
jennabarnes12387
Statistics 151 - Qualitative Con. and Quantitative Data
jennabarnes12387
Stats 151 - Normal Curve Z Scores and Probability
jennabarnes12387
Stats 151 - Assigning Probability to Events
jennabarnes12387
Stats 151 - Range, 68-95-99.7 rule, Chebychev's rule, and percentiles
jennabarnes12387
Stats 151 - Random Variables and Probability Mas Function
jennabarnes12387
Stats 151 - Representation of Continuous Random Data
jennabarnes12387
Stats 151 - Estimating population mean from sample mean
jennabarnes12387
Stats 151 - Testing a Hypotheses
jennabarnes12387