Isds tst 2
The normal distribution approximation is justified when
1. np> 5 2. n(1-p) >5 in other words, we want our sample size to be large enough so that there should be atleast 5 yes and at least 5 no answers expected in our sample (based on population proportion p and our sample size)
estimate
a particular value of the estimator (actual answer)
Simple Random Sample
a sample of n observations, where every individual has the same probability of being selcted. Edquivalently, every sample of size n has the same probability of being selected as any other sample of size n
estimator
a statistic that is used to estimate a population parameter (formula)
sample
a subset of the population
nonresponse bias
a systematic difference in preferences between respondents an non-respondents to a survey or a poll
selection bias
a systematic exclusion of certain groups from consideration for the sample
population
consists of all item of interest in a statistical problem
For a given sample size n,
decreasing the probability of a type I error alpha, will increase the probability of a type II error beta
Stratified Random Sampling
divide the population into mutually exclusive and exhaustive groups called strata, for each and every stratum, collect a SRS, weher the number of people for each SRS is proportional to that stratum's size *n
Cluster Sampling
divide the population into mutually exclusive and exhaustive groups, called clusters. randomly select k of the clusters and interview every observation in those k randomly selected clusters, and nobody in the non-selected clusters
Type II error occurs ehen we ____.
do not reject the null hypothessis wwhen it is actually false
FOr any population X with expected value mu and standard deviation sigma. the sampling distribution of x bar will be approximately normal if the sample size n is sufficiently small. As a general guidline, the normal distribution approximation is justified when n <30
false
On the basis of sample information, we either "accept the null hypothesis" or "reject the null hypothesis"
false
The alternative hypothesis typically agrees with the status quo.
false
We calculate a parameter to make inferences about a statistic
false
Alternative Hypothesis
states a claim about the population parameter, but it somehow disagrees with the null hypothesis
Null Hypothesis
states that there is no difference between a parameter and a specific value
If the null hypothesis is rejected at a 1% significance level, then _____________.
the null hypothesis will be rejected at a 5% significance level
bias
the tendency of a sample statistic to systematically overestimate or underestimate a population parameter
Bias refers to the tendency of a sample statistic to systematically over- or underestimate a population parameter
true
For a given sample size, any attempt to reduce the likelihood of making one type of error (Type I or Type II) will increase the likelihood of the other error.
true
Under the assumption that the null hypothesis is true as an equality, the p-value is the likelihood of observing a sample mean that is at least as extreme as the one derived from the given sample.
true
Central Limit Theorem
if X has any distribution and the sample size is sufficiently large (n>30) then the smapling distribtuin of x (bar) will be normal
For a sample of size n for a variable X:
if the population is normally distributed then the sampling distribution of x (bar) is also normal
A census is an example of _____/
population data
Selection bias occurs when _____.
portions of the population are excluded from the consideration for the sample
Systematic Random sampling
randomly pick a starting point like 51 and from then on out pick every 551 st of the objects
If the p-value for a hypothesis test is 0.027 and the chosen level of significance is .05 , then the correct conclusion is to ________________.
reject the null hypothesis
