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MSIS 3223 Exam 2 Okstate|74 questions and answers
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MSIS 3223 Exam 2 Okstate|74questions and answers
Probabilities are expressed - -as values between 0 and 1
- classical definition of probability - -If the process that generates the
outcome is known, and can be deduced from theoretical arguments;
- relative frequency definition - -based on empirical data
- relative frequency definition - -probability that an outcome will occur is
simply the relative frequency associated with that outcome.
- subjective definition of probability - -based on judgment and experience as
sports experts might predict at the start of the football season—what is the
probability of a specific team winning the national championship?
- random variable - -a numerical description of the outcome of an
experiment, may be CONTINUOUS OR DISCRETE
- discrete random variable - -one for which the number of possible
outcomes can be counted.
- continuous random variable - -has outcomes over one or more continuous
intervals or real numbers
- expected value - -of a random variable corresponds to the notion of the
mean, or average for a sample. Expected value can be helpful in making a
variety of decisions
- What is the probability that a respondent is female and prefers Science? -
-3/13
- How do you find joint probabilities? - -the probability of the intersection of
two events, easily calculated by dividing the number of respondents needed
by the total of respondents. P(O1) = P(F and B1)
- How do you find conditional probabilities? - -the probability of occurrence
of one event A, given that another event B is know to be true or has already
occurred (can help predict future purchases based on past purchases),
multiplying the probability of the proceeding event by the probability of the.
succeeding or condition event. P(A/B) = P(A and B)/P(B)
, - How do you identify that two events are independent? - -P(A/B) = P(A),
multiply the probabilities of the two events together to see if they equal the
probability of them both happening together
- The variance of a discrete random variable - -may be computed as a
weighted average of the squared deviations from the expected value. A
common measure of dispersion.
- The variance measures the uncertainty of the random variable - -the
higher the variance, the higher the uncertainty of the outcome
- Bernoulli distribution - -The probability distribution of a random variable
with two possible outcomes, each with a constant probability of occurrence
- The bionomial distribution models - -n independent replications of a
Bernoulli experiment, each with a probability p of success
- The binomial distribution - -an assume different shapes and amounts of
skewness, depending on the parameters
- The Poisson distribution - -is a discrete distribution used to model the
number of occurrences in some unit of measure.
- normal distribution - -is a continuous distribution described by the familiar
bell shaped curve. MOST IMPORTANT DISTRIBUTION IN STATISTICS
- normal distribution - -the distribution is symmetric, so its measure of
skewness is zero
- normal distribution - -The mean, median, and mode are all equal. Thus,
half the area falls above the mean and half falls below it
- normal distribution - -The range of X is unbounded, meaning that the tails
of the distribution extend to negative and positive infinity
- 68-95-99.7 rule - -The empirical rules apply exactly for the normal
distribution
- Probability density functions - -The distribution that characterizes
outcomes of a continuous random variable
- Properties of Probability Density Functions: - -• A graph of the density
function must lie at or above the x-axis.
• The total area under the density function above the x-axis is 1.
• For continuous random variables, there are an infinite number of values.
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