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