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Jessica7566 Jessica7566
wrote...
Posts: 366
Rep: 0 0
6 years ago
A continuous random variable is ________.
 
  A) a variable for which the number of possible outcomes can be counted
  B) a variable that has outcomes over one or more intervals of real numbers
  C) a characterization of the possible values that a random variable may assume along with the probability of each value
  D) a variable for which there is only one possible value

Q. 2

________ is an analytical method that determines the probabilities of the project completion times in project management models by assuming that the expected activity times define the critical path and that the distribution of project completion time
 
  is normal using the central limit theorem.A) Program Estimation and Research Technique
  B) Project Evaluation and Revise Technique
  C) Program Evaluation and Review Technique
  D) Project Estimation and Risk Technique

Q. 3

Calculate the total number of television sets shipped from the plant in Arizona. (Hint: Use Solver)
 
  A) 1400 units
  B) 1350 units
  C) 1300 units
  D) 1250 units

Q. 4

The level of confidence for a confidence interval is defined by 1 - . What does this  represent?
 
  What will be an ideal response?

Q. 5

When a single die is rolled, each of the six sides are equally likely. This is an example of a uniform distribution.
 
  Indicate whether the statement is true or false

Q. 6

Compare your answers to the F-test and Kruskal-Wallis test and explain how to interpret these results.
 
  What will be an ideal response?
Textbook 
Statistics, Data Analysis, and Decision Modeling

Statistics, Data Analysis, and Decision Modeling


Edition: 5th
Author:
Read 42 times
3 Replies

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Replies
wrote...
6 years ago
Ans. #1

B

Ans. #2

C

Ans. #3

D

Ans. #4

 is the probability that the confidence interval does not contain the true population mean.

Ans. #5

TRUE

Ans. #6

In the F-test, we rejected H0 at  = 0.05, but failed to reject H0 under same level of significance in the Kruskal-Wallis test. The reason is that under the assumption of normality in the populations, nonparametric tests such as Kruskal-Wallis are less powerful than parametric tests, such as ANOVA.
Jessica7566 Author
wrote...
6 years ago
Thank you

Can you answer the others that I've posted too? Face with Cold Sweat
wrote...
6 years ago
I'll take a quick look at them
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