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QMB 3200 MIDTERM QUESTIONS AND ANSWERS / LATEST
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QMB 3200 MIDTERM QUESTIONS AND ANSWERS / LATEST
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QMB 3200 MIDTERMwhat do you use for bivariate distributions? - ANSWERS-covariance and
correlation coefficient (measure linear association between the two random
variables)
in bivariate empirical discrete probability distributions, bivariate probabilities are
basically equal to - ANSWERS-joint probabilities
if you find that correlation coefficient is 0, you consider the 2 variables -
ANSWERS-independent
in finance, what is a good measure of risk? - ANSWERS-standard deviation
Binomial Probability Distribution is based on 4 properties - ANSWERS-1. the
experiment consists of a sequence of n identical trials
2. two outcomes are possible on each trial: success or failure
3. the probability of success (p) and the probability of failure (1-p) does not
change from trial to trial
4. the trials are independent
*we care about the number of successes
,discrete random variable - ANSWERS-a random variable that may assume either a
finite number of values or an infinite SEQUENCE of values (0, 1, 2, ... or 5,10,15,...)
•ex: number of people passing thru toll booth in one hour
Computing binomial probabilities in excel - ANSWERS-=Binom.Dist(x value,
number of trials, probability of success as a decimal, T/F)
in excel, they ask you to put TRUE or FALSE on the end of many equations. what
do they mean? - ANSWERS-TRUE means it will calculate the independent
probability
FALSE means it will calculate the cumulative probability
Poisson Probability Distribution - ANSWERS-The probability distribution for a
discrete random variable used for estimating the number of occurrences over a
specified interval of space/time
Properties of a Poisson Experiment - ANSWERS-1. The probability of an
occurrence is the same for any two intervals of equal length.
2. The occurrence or nonoccurrence in any interval is independent of the
occurrence or nonoccurrence in any other interval.
in a poisson distribution, what two values are equal? - ANSWERS-mean and
variance
,calculate poisson probability distribution in excel - ANSWERS-=Poisson.Dist(x
value, mean, T/F)
Hypergeometric probability distribution - ANSWERS-a probability distribution that
is similar to the binomial distribution BUT the trials are not independent and the
probability of success changes from trial to trial
• r is the number of successes in population N, and N-r is the number of failures
calculating hyper geometric probabilities in excel - ANSWERS-=Hypergeom.Dist(x
value, mean, r value, N value for population, T/F)
*it is actually =hypgeom.dist
continuous random variable - ANSWERS-a random variable that may assume any
numerical value in an interval or collection of intervals
•ex: time between phone calls
continuous random variables are based on - ANSWERS-measurement scales (ie
time, weight, distance, temperature)
, difference between discrete and continuous random variables (long) - ANSWERS-
1. Discrete random variables are computed where the random variable takes on a
specific value/number. it's an integer (IT IS NEVER A DECIMAL)
• continuous random variables are computed where the random variable is within
an interval (it can be a decimal)
2. the probability of a continuous random variable within some given interval (X1
to X2) is defined to be the area under the graph of the probability density
function between X1 and X2. (a single point is an interval of 0, so the probability
of a single value in the continuous case is 0)
—> basically you will end up with different values if the probability density
function is uniform, normal, exponential; also continuous random variables can't
be calculated for single points
difference between calculating discrete and continuous random variables
(summary) - ANSWERS-Discrete:
• discrete random variables are INTEGERS, never decimals
• for discrete RVs, we compute the probability at a SPECIFIC VALUE of x
Continuous:
• these random variables can be within an interval (it can be a decimal)
• for continuous RVs, we compute the probability that the random variable
assumes any value in an interval (we are computing the area under the
probability density function f(x)) BUT WE ARE NOT CALCULATING FOR A SINGLE
POINT
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