Imagine you are a manager at a major bottling company. Customers have begun to complain that the bottles of the brand of soda produced in your company contain less than the advertised sixteen (16) ounces of product. Your boss wants to solve the problem at hand and has asked you to investigate. You have your employees pull thirty (30) bottles off the line at random from all the shifts at the bottling plant. You ask your employees to measure the amount of soda there is in each bottle. Note: Use the data set provided by your instructor to complete this assignment.

 Bottle Number Ounces Bottle Number Ounces Bottle Number Ounces 1 14.5 11 15 21 14.1 2 14.6 12 15.1 22 14.2 3 14.7 13 15 23 14 4 14.8 14 14.4 24 14.9 5 14.9 15 15.8 25 14.7 6 15.3 16 14 26 14.5 7 14.9 17 16 27 14.6 8 15.5 18 16.1 28 14.8 9 14.8 19 15.8 29 14.8 10 15.2 20 14.5 30 14.6

Write a two to three (2-3) page report in which you:

1. Calculate the mean, median, and standard deviation for ounces in the bottles.
2. Construct a 95% Confidence Interval for the ounces in the bottles.
3. Conduct a hypothesis test to verify if the claim that a bottle contains less than sixteen (16) ounces is supported. Clearly state the logic of your test, the calculations, and the conclusion of your test.
4. Provide the following discussion based on the conclusion of your test:

a. If you conclude that there are less than sixteen (16) ounces in a bottle of soda, speculate on three (3) possible causes. Next, suggest the strategies to avoid the deficit in the future.

Or

b. If you conclude that the claim of less soda per bottle is not supported or justified, provide a detailed explanation to your boss about the situation. Include your speculation on the reason(s) behind the claim, and recommend one (1) strategy geared toward mitigating this issue in the future.

• Be typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides.  No citations and references are required, but if you use them, they must follow APA format. Check with your professor for any additional instructions.
• Include a cover page containing the title of the assignment, the student’s name, the professor’s name, the course title, and the date. The cover page and the reference page are not included in the required assignment page length.

The specific course learning outcomes associated with this assignment are:

• Calculate measurements of central tendency and dispersal.
• Determine confidence intervals for data.
• Describe the vocabulary and principles of hypothesis testing.
• Discuss application of course content to professional contexts.
• Use technological tools to solve problems in statistics.
• Write clearly and concisely about statistics using proper writing mechanics.

rieman Sums 44 questions how much

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MCQS Precalculus

1) A medical clinic in a small city in the state of Washington wants to estimate the mean serum cholesterol level (measured in mg of cholesterol per 100 mL of blood) of teenage males. Based on the following summary data taken from a random sample of 10 teenage males from this community, compute a 90% confidence interval for the mean serum cholesterol level of teenage males in this city. Assume that the sample was taken from a normal distribution. Round your confidence limits to 2 decimal places.
Summary Data: n = 10, , s = 24.920
A. (207.15, 240.67)
B. (209.12, 238.01)
C. (210.12, 239.56)
D. (213.34, 242.83)
E. None of the above
2) Questions on a statistics exam are considered good questions provided the questions discriminate between students who have studied for the exam and those who have not studied. Suppose that on a particular statistics exam the students were separated into two groups, the group that studied and the other group that had not studied. Data was collected and a 95% confidence interval for the difference in the proportion of those passing the exam from the group that studied and the proportion of those passing the exam from the group that had not studied. The confidence interval turned out to be . Note that sample 1 is from the group that studied and sample 2 is from the group that did not study. Select the best answer.
A. The data fails to show with 95% confidence that these questions discriminated between those who studied and those who did not study.
B. We are 95% confident that those who studied had a higher passing rate than those who did not study.
C. We are 95% confident that those who studied had a lower passing rate than those who did not study.
D. None of the these are correct.

SAMPLING

NAME:

INSTITUTION:

DATE:

It is evidence that was basing our argument on the analysis above; it is clear that several conclusions and observation can be met. The analysis gives us the importance of sampling and how it can be applied in real life. Through sampling, one can tend to understand the behavior and characteristic of an individual population without necessarily interviewing the entire population.

I found my own personal sample of 30 players by starting at the player named in the email that accompanied this assignment. Start counting with the next person on the list, and take every third person on the list until I get 30 people. The data can be found in the spreadsheet “Sample Data”.

Using Excel, we found the following five-number summary for the data “Weight”.  The calculations were made in Excel.

 Min Q1 Median Q3 Max 175 196.25 217.50 238.75 300

We draw a box whisker plot of the sample data as follows:

Using Excel, we calculated that the sample mean was 220.6 pounds, and the sample standard deviation was 33.84 pounds.  We used the sample mean of 220.6 pounds and sample standard deviation of 33.84 pounds to get an Empirical Rule graph as follows:

The maximum and the minimum values which were 175 and 300 respectively. Through the evaluation of data, we were able to obtain the median value as 217.50. The values were used to come up with a perfect and modern football field that can fit a game. This proofs that sampling can be used to code a game that can be utilized in a current phone or a computer hence making it one of the most significant aspect of programming.
The data was used to plot box-whisker, and it turned to be a perfect shape of the football field. The box-whisker was plotted using minimum and maximum values. The plot also demonstrated the upper and the lower quartile. The sampling is one of the most vital aspects of probability and statistic, hence gives the mean of the data. Sampling also helps in coming up with meaningful information.

As the population has a mean of 214.6 pounds with a population standard deviation of 42.2 pounds, the sample data has a mean of 220.60 pounds with a standard deviation of 33.84 pounds, which is very close to the population parameters. Thus, we would say that the sample statistics fairly represent the population parameters.

The above box whisker plot shows the data is skewed to right, so looks differently than the Empirical Rule graph. So, the data does not follow the Empirical Rule.

The sample standard deviation and the sample mean were used to construct empirical rule graph. The figure aids in getting the skewness of the data being analyzed. In the test distribution of normality, the empirical graph can also be used. The size of the deviations is calculated in the form of standard deviation and equated to the expected frequency. The normal skewed figure was applied in this case of analysis hence the data follow the empirical rule and can be used in the additional study.
Finally, it can be concluded that sampling has turned to be one of the most important aspects of the data analysis. It is clear that from the above analysis, sampling can be used to represent the entire population. When taking samples, one should be very careful so as to make the only correct data to avoid wrong analysis that leads to erroneous in conclusion.