True False BNAD 277
A confidence interval provides a value that, with a certain measure of confidence, is the population parameter of interest
FALSE
A parameter is a random variable, whereas a sample statistic is a constant
FALSE
A point estimate is a function of the random sample used to make inferences about the value of an unknown population parameter. A point estimator reflects the actual value of the point estimate derived from a given sample
FALSE
A sample consists of all items of interest in a statistical problem, whereas a population is a subset of the population. We calculate a parameter tomato inferences about the unknown sample statistic
FALSE
A population consists of all items of interest in a statistical problem
TRUE
If we had access to data that encompass the entire population, then the values of the parameters would be known and no statistical inference would be needed
TRUE
If we want to find the required sample size for the interval estimation of the population proportion and on reasonable estimate of this proportion is available, we assume the worst-case scenario under which p-bar = 0.5
TRUE
In stratified random sampling, the population is first divided up into mutually exclusive and collectively exhaustive groups, called strata. A stratified sample includes randomly selected observations from each stratum, which are proportional to the stratum's size.
TRUE
Nonresponse bias occurs when those responding to a survey or poll differ systematically from the non-respondents
TRUE
The required sample size for the interval estimation of the population mean can be computed if we specify the population standard deviation, the value of z alpha/2 based on the confidence level alpha and the desired margin of error.
TRUE
The standard normal distribution is a normal distribution with a mean equal to zero and a standard deviation equal to one
TRUE
The standard normal table is also referred to as the z table
TRUE
The t distribution has broader tails than the z distribution
TRUE
The letter Z is used to denote a random variable with any normal distribution
FALSE
Selection bias occurs when the sample is mistakenly divided into strata, and random samples are drawn from each stratum
FALSE
The mean and standard deviation of the continuous uniform distribution are equal
FALSE
The probability density function of a continuous uniform distribution is positive for all values between -infinity and +infinity
FALSE
When a statistic is used to estimate a parameter, the statistic is referred to as an estimator. A particular value of the estimator is called an estimate.
TRUE
An unbiased estimator is efficient if its standard error is higher than that of other unbiased estimators of the estimated population parameter
FALSE
Cumulative distribution functions can only be used to compute probabilities for continuous random variables
FALSE
Examples of random variables that closely follow a normal distribution include the age and the class year designation of a college student
FALSE
For a given confidence level (alpha) and sample size n, the width of the confidence interval for the population mean is narrower, the greater the population standard deviation
FALSE
For a given sample size n and population standard deviation, the width of the confidence interval for a population mean is wider, the smaller the confidence level alpha
FALSE
For any population x-bar with expected value mu and standard deviation omega, the sampling distribution of x-bar will be approximately normal is the sample size n is sufficiently small. As a general guideline the normal distribution approximation is justified when n < 30.
FALSE
For any sample size n, the sampling distribution of x-bar is normal is the population x-bar from which the sample is drawn is uniformly distributed.
FALSE
Given that the probability distribution is normal, it is completely described by its mean: mu > 0, and its standard deviation: omega > 0
FALSE
Just ask the case of the continuous uniform distribution, the probability density function of the normal distribution may be easily used to compute probabilites
FALSE
Like the z distribution, the t distribution is symmetric around 0, bell-shaped and with tails that approach the horizontal axis and eventually cross it
FALSE
The t distribution consists of a family of distributions where the actual shape of each one depends on the degrees of freedom. For lower values of df, the t distribution is similar to the z distribution.
FALSE
We are often interested in finding the probability that a continuous random variable assumes a particular value
FALSE
We calculate a parameter to make inferences about a statistic
FALSE
A continuous random variable is characterized by uncountable values and can take on any value within an interval
TRUE
A simple random sample is a sample of n observations which has the same probability of being selected from the population as any other sample of n observations
TRUE
An estimator is consistent if it approaches the estimated population parameter as the sample size grows larger
TRUE
An estimator is unbiased if its expected value equals the estimated population parameter
TRUE
Bias refers to the tendency of a sample statistic to systematically over- or underestimate a population paramater
TRUE
For a given confidence level (alpha) and population standard deviation, the width of the confidence interval for the population mean is narrower, the smaller the sample size n
TRUE
For any population proportion p, the sampling distribution of p-bar will be approximately normal if the sample size n is sufficiently large. As a general guideline, the normal distribution approximation is justified when np >= 5 and n(1-p) >= 5.
TRUE
If a random sample of size n is taken from a normal population with a finite variance, then the statistic formula finding T follows the t distribution with n-1 degrees of freedom
TRUE
The continuous uniform distribution describes a random variable, defined on the interval [a,b], that has an equally likely chance of assuming values within any subinterval of [a,b] with the same length.
TRUE
The mean of a continuous uniform distribution is simply the average of the upper and lower limits of the interval on which the distribution is defined
TRUE
The probability density function of a continuous random variable can be regarded as a counterpart of the probability mass function of a discrete random variable
TRUE
The probability density function of a normal distribution is in general characterized by being symmetric and bell-shaped
TRUE
