Ccording to researchers, the mean lengtn of imprisonment for motor-venicle-theit offenders in a fhation is 15.8 montns. One hundred randomly the 10% significance level, do the data provide sufficient evidence to conclude that the mean length of imprisonment for motor-vehicle-theft offenders in the city differs from the national mean? Assume that the population standard deviation of the lengt mprisonment for motor-vehicle-theft offenders in the city is 8.0 months. ck here to view page 1 of the table of areas under the standard normal curve. Click here to view page 2 of the table of areas under the standard normal curve. nide-heit offenders in a city in the hation had a mean lengin of imprisonmer et up the hypotheses for the one-mean z-test Ho: L H, (Type integers or decimals. Do not round.) ne test statistic is z= Round to two decimal places as needed.) lentify the critical value(s). Select the correct choice below and fill in the answer box within your choice. Round to two decimal places as needed.) OA. The critical value is z,= OB. The critical values are za/2= OC. The critical value is -z, = V the null hypothesis. The data V sufficient evidence to conclude that the mean length of imprisonment for motor-vehicle-theft offenders in the city is the mean length of imprisonment for motor-vehicle-theft Tenders in the nation.

Q: 24. Find d²4 zP 2. xp 4=3x² +34-8

A: Differentiate two times

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A:

Q: C3x2 + – 4 kx - 5x- 6.

A:

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A: 1. It is "Greater than"  2. Slope = 0.0016

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A: I have to answer for part-d and part-e, so i use the previous result .

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A:

Q: 4. X = 100

A:

Q: 1 Evaluate. 5P3 • 6C4 900 300 150

A: Use the formula and evaluate.

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A: We have to simplify the expression : 3u5v4 / ( 9v3y6 + 15v5 ).

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A:

Q: O 8. Simplify. (a*b®) (a°b*) O a'z8

A: The given expression,      a5b6a2b2

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A: Laplace transform is used to find the solution of the dependent variable of a differential equation.…

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A: Solution

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A:

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A: Given : 30  = 6+z

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A:

Q: 1. (3, x) 2. (3x + 3, y) 3. (y, cos x) 4. (x + y, x – Y)

A: using online vector field graphing we get 1-A 2-C

Continuous Probability Distributions

Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.

Normal Distribution

Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!