STAT 218 EXAM 1

false

A *plausible* model is one in which there is no reasonable explanation for the data we observed

false

A categorical variable has at least three possible options

true

A sampling frame is the set of all possible observational units in the population

true

A two-sided test estimates the p-value by considering results that are as extreme as the observed result in either direction

true

All binary variables are also categorical variables

false

Normal distributions have a right skewed distribution

false

The central limit theorem predicts the behavior of the null distribution when validity conditions are met

true

The standardized statistic is commonly denoted by the variable t or z

false

a p-value is the proportion of failures in the sample

false

a parameter is the quantity of interest computed for the sample

false

a standardized statistic is the raw distance between the sample statistic and the population mean

true

a statistic is the quantity of interest computed for the sample

validity conditions

categorical: nπ > 10 n(1-π) > 10 quantitative: n> 20

categorical variable

category designations ex: eye color, hair color etc

parameter

ch 1: the long-run proportion (probability) of an outcome-- measured by π ch 2: population mean-- the long-run average, true average, true mean-- measured by mu

type 2 error

fail to reject H0 but in reality H0 is actually false

binary variable

have 2 possible outcomes; success/failure, heads/tails, pass/fail, etc

standardized statistic

how many standard deviations away is the observed statistic from the center of the null distribution neg? --> observed statistic is less than the center pos?--> observed statistic is greater than the center

observational unit

individual person, animal, thing on which you measure data; what or who you are observing

quantitative variable

numerical values; height, weight, age, etc

false

pˆ is the symbol for the sample mean

type 1 error

reject the null when H0 is actually true

p-value

the probability of obtaining a value of the statistic at least as extreme as the observed statistic when the null hypothesis is true the smaller the p-value, the stronger the evidence against H0

statistic

the sample proportion of an outcome --- pˆ also= xbar

true

the validity conditions for a hypothesis test on a quantitative variable are to have 20 observations and a not-strongly-skewed distribution

true

α is the probability of a Type I error

true

π is the symbol for the population proportion