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Suppose that the number of accidents occurring in an industrial plant is described by a Poisson distribution with an average of one accident per month. Let x denote the time (in months) between successive accidents.a Find the probability that the time between successive accidents is
(1) More than two months.
(2) Between one and two months.
(3) Less than one week (1/4 of a month).b Suppose that an accident occurs less than one week after the plant's most recent accident.
Would you consider this event unusual enough to warrant special investigation? Explain.
Determine the lowest weight a student can have and still be qualified to enter the school.
The NY Dept of Motor Vehicles (DMV) designs its license plates with space for 7 letters or numerals. In the most recent iteration, the DMV uses three letters followed by 4 numbers.
The data show the total number of medals (gold, silver, and bronze) won by each country winning at least one gold medal in the 2006 Winter Olympics. Find the mean, median, and mode of the numbers of medals won by these countries.
The State of Ohio plays a daily (except Sunday) three digit lottery, where the player chooses any three numbers, 1 thru 10, three different times.
A researcher believes that the percentage of people who exercise in California is greater than the national exercise rate. The national exercise rate is 20%. The researcher gathers a random sample of 120 individuals who live in California and find..
An insurance company has determined that each week an average of nine claims are filed in their Atlanta branch. What is the probability that during the next week
Following data from an x bar chart, is the process capable (capability index>1.33)?
The data show that 48 of the doctors picked Brand X. If these data are evaluated using a chi-square test for goodness of fit, what is the expected frequency for Brand X?
How might you go about creating a stronger regression model? For example, you have a multiple regression model with an adjusted R-Square of 0.49, which would explain 49% of the variance of the dependent measure
Let X be a random variable uniformly distributed on the interval (0,1). Let Y be a new random variable defined as Y = X2. What is the probability density function of Y given by?
Construct three scatter plots for: (1) percentage alcohol versus calories, (2) percentage alcohol verses carbobydrates, and (3) calories versus carbohydrates
One table has a standard deviation of $50 while the other has a standard deviation of $150. What conclusion can be drawn from the data?
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