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1. The time (in hours) until failure of a transistor is a random variable X which is exponentially distributed with mean = 50. It is observed that after 40 hours the transistor is still working. Find the conditional probability that X > 65.
2. Wires manufactured for the use in a computer system are specified to have resistances between 0.12 and 0.14 ohms. The actual measured resistances of the wires produced by company A have a normal distribution with a mean of 0.13 ohm and a standard deviation of 0.005 ohm. Find the probability that a randomly selected wire from company A's production will meet the specifications.
Bicycle helmet use. Table lists data from a cross-sectional survey of bicycle safety. The explanatory variable is a measure of neighbourhood socioeconomic status (variable_RFM). The response variable is "percent of bicycle riders wearing a helmet"..
Explain your answer to someone who is familiar with the T test for a single sample, but not with the T test independent means.
where the deviations εi are assumed to be independent and Normally distributed with mean 0 and standard deviation σ. This model was fit to the data using the method of least squares. The following results were obtained from statistical software.
A flour mill produces flour in small bags before distributing them to wholesalers. The average weight of each bags is 8 kg with a standard deviation of 0.5 kg.
The level of satisfaction in a consumer survey would represent what level of measurement?
Can college conclude that students in new program are significantly different from rest of freshmen class? Use two - tailed test with a = 0.05.
It has been reported that 3% of all cars on the highway are traveling at speeds in excess of 70 mph. If the speeds of four random automobiles are measured via radar, what is the probability that at least one car is going over 70 mph?
Give an example of two variables that probably have a significant linear correlation coefficient, but one variable does not necessarily cause the other.
Follow the conventions as described in the general guidelines for writing up Special Problems.
Use the Rare Event Rule. Does the evidence support the claim?
Test to determine if there is a significant negative relationship between the independent and dependent variable at a = .05 and .01
State the main points of the Central Limit Theorem for a mean. Why is population shape of concern when estimating a mean? What does sample size have to do with all?
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