BNAD Ch. 1, 3, 7, 8 LearnSmart Questions

the mean of the standard normal distribution is equal to

zero

95% confidence interval for the population proportion is calculated as (0.40, 1.00) the margin of error for the interval is

0.30

the probability that a normal random variable X is less than its mean is equal to

0.50

Scenarios that use nominal scale

1- designating males as 1 and females as 2 compare gender performance on a test 2- noting the racial composition of an undergraduate class

for a 95% confidence the sample mean xbar will fall into the interval mu + or - (_____) x sigma over (sqr. n)

1.96

the height of the probability density function F(x) of the uniform distribution defined on the interval [A,B]

1/(B-A)

an investment strategy has an expected return of 12% and a standard dev of 10%. if an investment returns are normally distributed, the probability of earning a return less than 2% is closest to

16%

number of parameters that are needed to fully describe any normal distribution

2

sample mean and sample standard dev are calculated as 50 and 25. T=2.131 and there is a sample of 16

50 + or - 2.131(25/sqr. 16)

if x has a normal distribution with mu=100 and sigma=5, then the probability P(90<90<95) can be expressed in terms of the standard normal random variable Z as

P(-2<Z<-1)

it is known that the length of a certain product X is normally distributed with Mu=20 inches. How is the probability P(X>16) related to the probability P(x<16)

P(X>16) is greater than P(X<16) because the first is greater than 0.50 so P(X<16) is less than 0.50

it is known that the length of a certain product X is normally distributed with Mu=20 inches. how is P(x<20) related to the P(x<16)

P(x<20) is greater than P(x<16)

due to symmetry, the probability that the normal random variable Z is greater than 1.5 is equal to

P(z> -1.5)

Northern university college of business wants to determine the average starting salary for last years graduates. What is the population from which the survey is taken?

all of last years graduates from northern college of business

the interval scale of measurement

allows for the use of negative values

if the population from which the sample is drawn is normally distributed, then the sampling distribution of the sample mean is

always normally distributed

a significant weakness of the ordinal scale is

an inability to measure differences between the ranked values

how does an interval estimator differ from a point estimator?

and INTERVAL estimator provides a range of values for the population parameter whereas a POINT estimator provides a single value

the central limit theorem states that, for any distribution as N gets larger, the sampling distribution of the sample mean become

closer to a normal distribution

for a continuous random variable x, the function used to find the area under F(x) up to any value is called the

cumulative distribution funciton

some of the desireable properties of a point estimator si

efficeincy, unbiasedness, consistency

if an unbiased estimator is ____ its standard error must be lower than that of the other unbiased estimators

efficient

for a continuous random variable, one characteristic of its probability density function, F(x) is that the area under f(x) over all values of x is

equal to 1

for a continuous random variable X, it is only meaningful to calculate the probability that the value of the random variable

falls within some specified inteval

a discrete random variable can assume an uncountable number of values

false

the sample size required to approximate the normal distribution depends on

how much the population varies from normality

stratified sampling is preferred to cluster sampling when the objective is to

increase population

the most practical way to reduce the margin of error is to

increase the sample size

The branch of statistics that draws conclusions about a large set of data based on a smaller set of data is often referred to as

inferential statistics

the normal distribution is completely described by these two parameters:

mean and variance

cluster sampling works best when

most of the variation in a population is within groups and not between groups

calculating standard dev of x bar

mu/sqr.n (mean/ square root sample size)

if we were to sample repeatedly from a given population, the average value of the sample mean will follow

normal

the estimator xbar folows a normal distribution when the underlying population follows a distribution

normal

the shape of the population from which a simple random sample is drawn is normal, then the shape of the sampling distribution of x bar is

normal

In general, we use sample data because

obtaining data from the population is often an expensive process

the probability of the sample mean is commonly referred to as the

sampling distribution of x bar

a sample of N observations that have the same probability of being selected from the population as any other sample of N observations is called a

simple random sample

for a given confidence level and standard dev, the width of the interval is wider for a

smaller sample size AND larger standard dev

when the finite population correction factor is applied to the sample proportion, the resulitng standard deviation for the sample mean is equal to

sqr. [P-(1-p)/N] * sqr. (N-n)/(N-1)

Which is DESCRIPTIVE statistics?

summarizing the variability of the exam scores of 40 students based on all 40 exam scores

Which is an example of INFERENTIAL statistics

testing the longevity of all light bulbs based on a sample of 100 light bulbs

a confidence interval narrow if the following is accomplished

the chosen confidence level decreases ALSO the sample size increases

all of the following are examples of random variables that likely follow a normal distribution except...

the number of states in the USA (this is not a variable)

the two pieces of info that are necessary to determine the value of T sub df are

the sample size or degrees of freedom ALSO the level of significance

bias refers to

the tendency of sample statistics to systematically over or under estimate a population parameter

if the expected value of an estimator is equal to the unknown parameter beign estimated, then the estimator is best characterized as an

unbiased estimator

a manager of a woman's clothing store... she decides to treat all outcomes for sales between these two values equally likely. If we define the random variable X as sales, then X follows the

uniform distribution

a characteristic of interest that differs among various observations is referred to as a

variable

the branch of statistics that uses sample statistics to estimate a population parameter or test a hypothesis about such a parameter is best referred to as

inferential statistics

a continuous random variable X follows the uniform distribution with a lower limit of a and an upper limit of b. The expected value of x

(A+B)/2

for a continuous random variable, one characteristic of its probability density function F(x) is:

F(x) < or equal to 1 for all values of x

the expected value and the variance of the standard normal random variable Z are both zero

FALSE, the expected value of Z is zero, but its variance is 1

as a general guideline, the normal distribution approximate can be used to describe the sampling distribution of the sample mean when

N> or equal to 30

the sample statistic Pbar is an estimator of

P

a parameter is a numerical measure that describes a population

True

if you have data that describes the entire population, then there is not need to make inference using sample data

True

which of the following random variables is depicted with a bell-shaped curve?

a normal random variable

which of the following statements is most accurate

a parameter is a constant although its value may be unknown

in a statistical problem, a population consists of

all items of interest

an estimator that tends to produce more accurate estimates of the population parameter as the sample size increases is best characterized as

consistent estimator

suppose you were told that the delivery time of your new washing machine is equally likely over the period of time from 9 am to noon. if we define the random variable X as delivery time then x follows a

continuous normal distribution

Number of people in a household

discrete variable

when a sample statistic is used to make inferences about a population parameter, it is referred to as:

estimator

if X is normally distributed with expected value mu and standard deviation sigma, then x bar is normally distributed with

expected value of mu and standard deviation of sigma/sqr. N

in general, the variability between sample means is _____ the variability between observations

less than

the allowed probability that an interval estimate of a population mean will not contain u is referred to as the

level of significance

the expected value of xbar is equal to

mu

the value of the finite population correction factor is always less than

one

the variance of the standard normal distribution is equal to

one

A ______ includes all items of interest in a statistical problem

population

the paramter P represents the

population proportion

selection bias occurs when

portions of the population are excluded from the consideration for the sample

the probability distribution of a continuous random variable is called its

probability density function

if X is a normally distributed random variable then...

the mean the median and the mode are all equal

a company wants to estimate the mean price of oil over the past 10 years. what kind of data does the company need?

time series data

the expected value of x bar is equal to mu (the mean)

true

if x is normal, we can transform it into the standard normal random variable as

z= (xbar-mu)/(sigma/sqr. n)

Samples are primarily used to

Make inferences about population parameters

for any population proportion P, the sampling distribution of the sample proportion is approximately normally distributed if

NP > or equal to 0.05 N

The inverse transformation, X=mu+Z(sigma) is used to______

compute X values for given probabilities

the inverse transformation, x=mu +z(sigma) is used to

compute x values for given probabilities

a continuous random variable has the uniform distribution on the interval [A,B] If it's probability density function F(x)

is constant for all x between A and B

which of the following is true about a sample statistic such as sample mean or sample proportion

it is a random varaible

when the population standard deviation is unknown, the standard error for the sample mean is

s/(sqr.N)

which of the following scenarios is an example of the interval scale?

the outside temperature (in degree Fahrenheit)

what does cumulative probabilities mean?

the probability that Z is less than or equal to a given z value

which of these is a characteristic of a "bad" sample

the sample is not representative of the population we are trying to describe

for a given sample size and standard deviation, the width of the confidence interval is _____ for a greater confidence level

wider

the probability distribution of the sample mean is commonly referred to as

xbar

an investment strategy that has an expected return of 12% and a standard deviation of 10%. If investment returns are normally distributed the probability of earning a return of more than 32% is closest to:

2.5%

a 95% confidence for the pop mean is calculated as (40, 80) the point estimate for this interval is

60 because (40+80)/2= 60

due to symmetry, the probability that the standard normal random variable Z, is less than zero is equal to

0.50

the area under the normal curve below its expected value is

0.50

a 95% confidence interval for the population mean implies that

for repeated samples, 95% of the sample means will fall within the interval

for a continuous random variable x, how many distinct values can it assume over an interval?

infinite

which of the following is an example of a continuous random variable?

normal random variable

in order to derive a confidence interval for mu, the estimator x bar must have a

normal sampling distribution

all of the following are examples of cross-sectional data except:

quarterly sales for a computer company for t he last five years

a research analyst collects data on the weekly closing price of gold throughout the year, the scale of data is

ratio

the central limit theorm state that the distribution of the sample mean will be approximately normal if

the sample size is sufficiently large as a general guideline N> or equal to 30

what does it mean when we say that the tails of the normal curve are asymptotic to the x-axis?

the tails get closer and closer to the x axis but never touch it

the lower the confidence interval, the narrower the confidence interval

true

which is an estimate

xbar=20