STATS HELP !!!!!!!!! Also, Can you please check my other problems I already Fini
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STATS HELP !!!!!!!!!
Also, Can you please check my other problems I already Finished please...!!
An important part of any dispensing process is statistical quality control. Machines are supposed to dispense on average 600 ml of soda to every glass. At a random point each hour, the owner dispenses and checks a glass to determine the actual volume dispensed. One day the volumes are:
600.15 599.92 599.85 599.92
599.81 600.14 600.04 599.98
Is there sufficient evidence to conclude that the average volume of soda dispenses is different than 600 ml? Test at alpha = 0.05.
Reject Ho. There is evidence to support the alternative hypothesis that the true mean soda dispensed is different than 600 ml.
Reject Ho. There isn’t enough evidence to conclude the true mean is different than 600 ml.
Fail to reject Ho. There is evidence to support the alternative hypothesis
***Fail to reject Ho. There isn’t enough evidence that the true mean of soda dispensed is different than 600 ml
A packaging machine is supposed to fill boxes of breakfast cereal to a weight of 16 ounces. Eight filled boxes are selected at random and the weight of cereal is determined. The results (in ounces) are summarized in the following table.
16.7
16.0
16.4
15.9
16.5
16.2
15.9
16.2
A technician wishes to test the claim that the machine is overfilling the boxes. Assume the population standard deviation is 0.45 and a 5% level of significance. What is the hypothesized value for the test? (Assume the filling weights are normally distributed.)
a.
0.95
***b.
16
c.
0.45
d.
0.05
e.
16.225
Describe the two types of errors that might be made when a hypothesis test is carried out.
a.
A Type I error is rejecting Ho when Ho is false. A Type II error is failing to reject Ho when Ho is false.
b.
A Type I error is failing to reject Ho when Ho is true. A Type II error is rejecting Ho when Ho is true.
c.
A Type I error is rejecting Ho when Ho is false. A Type II error is failing to reject Ho when Ho is true.
***d.
A Type I error is rejecting Ho when Ho is true. A Type II error is failing to reject Ho when Ho is false.
e.
A Type I error is rejecting Ho when Ho is true. A Type II error is failing to reject Ho when Ho is true.
The reputation of many businesses can be severely damaged due to a large number of defective items during shipment. Suppose 300 batteries are randomly selected from a large shipment; each is tested and 9 defective batteries are found. At a 0.1 level of significance, does this provide evidence that the proportion of defective batteries is less than 5%?
***The true proportion of defective batteries is less than 5%
The true proportion of defective batteries is greater than 5%
The true proportion of defective batteries is 5%
There is not enough evidence that true proportion of defective batteries is less than 5%
The level of significance of a test is the probability of making a type I error, given that the null hypothesis is true.
***True
False
A t curve is bell-shaped like the z curve but is less spread out.
True
***False
A type II error is made by failing to reject a false null hypothesis.
***True
False
Reject Ho. There is evidence to support the alternative hypothesis that the true mean soda dispensed is different than 600 ml.
Reject Ho. There isn’t enough evidence to conclude the true mean is different than 600 ml.
Fail to reject Ho. There is evidence to support the alternative hypothesis
***Fail to reject Ho. There isn’t enough evidence that the true mean of soda dispensed is different than 600 ml
cii Seoure httFs.utsabacoboard.com/webapps/as id 154152 18course id_127272 18content ida_3144956 1step-null Question Completion Status: Some city leaders have attempted to improve air cuality by decreasing the rates of air pollution. Does the summary data below prove that San Antonio has decreased pollution levels from the previous year's average uf 44 ppb? Use an alpha level of.01 Poliution Reaalin Mean Standard Error Median Modle Standard Deviation Sample Variance Kurtosis Skewness Rarnge Minimu Maximum Sum Count Confidence Level(95.0% 41.25 1.838663 #N/A 6.369316 40.56818 1.17825 0.34277 31 4.04687 We reject the null hypothesis, San Antonio has proven a significant decrease in pollution levels. We reject the null hypothesis, San Antonio has Not proven a significant decrease in pollution levels. We fail to reject the null hypothesis, San Antonio has Not proven a significant decrease in pollution levels. We fail to reject the null hypothesis, San Antonio has proven a significant decrease in pollution levels. lick Save and Submit to sme and subomit. Click Save AN AnSTs to save all ansuxers Save AlAnswers Save and SubmiitExplanation / Answer
TS = ( 41.25 - 44)/1.838663
= -1.495652
critical value for df = 12-1 = 11
is -2.71
since |TS| < |critical-value|
we fail to reject the null hypothesis
option C) is correct
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