An article in a magazine discussed the length of time till failure of a particular product. At the end of the product's lifetime, the time till failure is modeled using an exponential distribution with a mean of 500 thousand hours. In reliability jargon this is known as the "wear-out" distribution for the product. During its normal (useful) life, assume the product's time till failure is uniformly distributed over the range 200 thousand to 1 million hours. Complete parts a through c. a. At the end of the product's lifetime, find the probability that the product fails before 600 thousand hours. (Round to four decimal places as needed.)

Researchers often rely on surveys to capture a subjective assessment of well-being. One study finds that holding everything else constant, people seem to be least happy when they are in their 40's. Another study suggests that money does buy happiness, but its effects diminishes as income rises above $75000 a year. The accompanying data file includes survey daa of 100 working adults' self-assessed happiness on a scale of ) to 100, along with their age and annual income. Estimate and interpret a regression model based on Age, Age 2 and income. Predict happiness with income equal = to $80000 and age equal to 30, 45, and 60 Years Predict happiness with Age equal = to 60  and income equal to 25,000, 75000, and 125000   Happiness Age Income 69 49 52000 83 47 123000 86 72 112000 73 52 166000 89 68 90000 81 37 152000 75 48 58000 56 48 50000 75 56 93000 57 51 27000 77 60 173000 83 55 173000 85 75 68000 82 69 157000 63 39 40000 70 66 107000 78 34 109000 53…

If actual period demand varies from the forecast by more than 3MAD, this indicates: there is 3% chance that the forecast is wrong. there is a 98% chance that the forecast is wrong. there is a 97% chance that the forecast is wrong. there is a 3% chance that the forecast is correct Moving to the next question prevents changes to this answer:

Previously, De Anza's statistics students estimated that the amount of change daytime statistics students carry is exponentially distributed with a mean of $0.88. Suppose that we randomly pick 25 daytime statistics students. Find the probability that an individual had between $0.80 and $1.00. Graph the situation, and shade in the area to be determined.