
The data points given were:

With the true mean calculated as : 24,387.28
Answer:
Given data:
10000,12500,15000,17500,20000,22500,25000,27500,30000,32500,35000,3500,40000,22506,28707,21567,23168,24782,27809,26081,31527,25964,20922,26206,20305,27316,14585,25908,25318,29754,26286,11908,24783,24184,20286,21376,29561,28873
Now to find the mean():
Mean()=sum of
observations/number of observations
=10000+12500+15000+17500+..................................................+20286+21376+29561+28873/38
=90062/38
=23702.16
Therefore the population mean() is
23702.16.
Therefore the probability of seeing rates within 5000 of the true
mean is 24,387.28
Yes,the result correlate to behaviour associated with the standard normal distribution.
The data points given were: With the true mean calculated as : 24,387.28 f. Given the distribution type and parameter...
The data points given were:
With the true mean calculated as : 24,387.28
f. Given the distribution type and parameter what is the probability of seeing rates within ± 5000 of the true mean? Does the result correlate to behavior associated with the standard normal distribution? Show work that supports your answer. Data Packets Per Hr (Bin) Packets Per HR 22506 10000 12500 28707 15000 21567 17500 23168 20000 24782 22500 27809 26081 25000 31527 27500 30000 25964 32500 20922...
We have data (given Below) that shows, the annual sales for four different companies (called company A, B, C and D) for duration of 2000-2010 years. Make two scatter plot for each company's annual sales. In first scatter plot show Linear regression, display its equations and the R-square value. And in the second scatter plot show Exponential Regression, display its equation and the R-square value. For each company answer which regression (linear or exponential) is a better fit for the...