Shelia's measured glucose level one hour after a sugary drink varies according to the normal distribution with ?=132μ=132 mg/dl and ?=10.5σ=10.5 mg/dl.

What is the level L such that there is probability only 0.05 that the mean glucose level of 4 test results falls above ?L? Give your answer precise to one decimal place.

I need to know how to properly complete this question step by step in writing as well as using the ti-84?:

Random and independent samples of 900 men and 1200 women were asked if they believe that a good diet was very important to good health. Sample results are as follows

women men

believes a good diet is important 924 603

sample size 1200 900

conduct the appropriate hypothesis test to see if the proportion of all men who hold this view is less than the proportion of all women who hold this view. Using a significance level of a= 0,05. Use a p-value method

Steps to Complete the Week 6 Lab Find this article in the Chamberlain Library. Once you click each link, you will be logged into the Library and then click on "PDF Full Text". First Article: Confidence Intervals, ( I copied and pasted both articles at the bottom of this question).

1. Consider the use of confidence intervals in health sciences with these articles as inspiration and insights.

2. Describe how you could use confidence intervals to help make a decision or solve a problem in your current job, a clinical rotation, or life situation. Include these elements: Description of the decision or problem

3. How the interval would impact the decision and what level of confidence would be most appropriate and why What data would need to be collected and one such method of how such data could ideally be collected

Articles to use:

Confidence interval: The range of values, consistent with the data, that is believed to encompass the actual or “true” population value Source: Lang, T.A., & Secic, M. (2006). How to Report Statistics in Medicine. (2nd ed.). Philadelphia: American College of Physicians

Confidence interval: The range of values, consistent with the data, that is believed to encompass the actual or "true" population value Source: Lang, T.A., & Secic, M. (2006). How to Report Statistics in Medicine. (2nd ed.). Philadelphia: American College of Physicians

Hope this information helps:

1. Consider the use of confidence intervals in health sciences with these articles as inspiration and insights.
2. Describe how you could use confidence intervals to help make a decision or solve a problem in your current job, a clinical rotation, or life situation. Include these elements:
   1. Description of the decision or problem
   2. How the interval would impact the decision and what level of confidence would be most appropriate and why
   3. What data would need to be collected and one such method of how such data could ideally be collected

These are the articles provided for the homework:

To draw conclusions about a study population, researchers use samples that they assume truly represent the population. The confidence interval (CI) is among the most reliable indicators of the soundness of their assumption. A CI is the range of values within which the population value being studied is believed to fall. CIs are reported in the results section of published research and are often calculated either for mean or proportion data (calculation details are beyond the scope of this article). A 95% CI, which is the most common level used (others are 90% and 99%), means that if researchers were to sample numerous times from the same population and calculate a range of estimates for these samples, 95% of the intervals within the lower and upper limits of this range will include the population value. To illustrate the 95% CI of a mean value, say that a sample of patients with hypertension has a mean blood pressure of 120 mmHg and that the 95% CI for this mean was calculated to range from 110 to 130 mmHg. This might be reported as: mean 120 mmHg, 95% CI 110-130 mmHg. It indicates that if other samples from the same population of patients were generated and intervals for the mean blood pressure of these samples were estimated, 95% of the intervals between the lower limit of 110 mmHg and the upper limit of 130 mmHg would include the true mean blood pressure of the population. Notice that the width of the CI range is a very important indicator of how reliably the sample value represents the population in question. If the CI is narrow, as it is in our example of 110-130 mmHg, then the upper and lower limits of the CI will be very close to the mean value of the sample. This sample mean value is probably a more reliable estimate of the true mean value of the population than a sample mean value with a wider CI of, for example, 110-210 mmHg. With such a wide CI, the population mean could be as high as 210 mmHg, which is far from the sample mean of 120 mmHg. In fact, a very wide CI in a study should be a red flag: it indicates that more data should have been collected before any serious conclusions were drawn about the population. Remember, the narrower the CI, the more likely it is that the sample value represents the population value.

Part 1, which appeared in the February 2012 issue, introduced the concept of confidence intervals (CIs) for mean values. This article explains how to compare the CIs of two mean scores to draw a conclusion about whether or not they are statistically different. Two mean scores are said to be statistically different if their respective CIs do not overlap. Overlap of the CIs suggests that the scores may represent the same "true" population value; in other words, the true difference in the mean scores may be equivalent to zero. Some researchers choose to provide the CI for the difference of two mean scores instead of providing a separate CI for each of the mean scores. In that case, the difference in the mean scores is said to be statistically significant if its CI does not include zero (e.g., if the lower limit is 10 and the upper limit is 30). If the CI includes zero (e.g., if the lower limit is -10 and the upper limit is 30), we conclude that the observed difference is not statistically significant. To illustrate this point, let's say that we want to compare the mean blood pressure (BP) of exercising and sedentary patients. The mean BP is 120 mmHg (95% CI 110-130 mmHg) for the exercising group and 140 mmHg (95% CI 120-160 mmHg) for the non-exercising group. We notice that the mean BP values of the two groups differ by 20 mmHg, and we want to determine whether this difference is statistically significant. Notice that the range of values between 120 and 130 mmHg falls within the CIs for both groups (i.e., the CIs overlap). Thus, we conclude that the 20 mmHg difference between the mean BP values is not statistically significant. Now, say that the mean BP is 120 mmHg (95% CI 110-130 mmHg) for the exercising group and 140 mmHg (95% CI 136-144 mmHg) for the sedentary group. In this case, the two CIs do not overlap: none of the values within the first CI fall within the range of values of the second CI. Thus, we conclude that the mean BP difference of 20 mmHg is statistically significant. Remember, we can use either the CIs of two mean scores or the CI of their difference to draw conclusions about whether or not the observed difference between the scores is statistically significant.

Use the case below to answer the following question(s) (Total marks = 100)

A certain restaurant located in a resort community is owned and operated by Karen Payne. The restaurant just completed its third year of operation. During this time, Karen sought to establish a reputation for the restaurant as a high quality dining establishment that specialises in fresh seafood. The efforts made by Karen and her staff proved succesful, and her restaurant is currently one of the best and fastest-growing restaurant in their neighbourhood. Karen concluded that, to plan better for the growth of the restaurant in the future, she needs to develop a system that will enable her to forecast food and beverage sales by month for up to one year in advance. Karen compiled the following data on total food and beverages sales for the three years of operation.

Food and beverage sales for the restaurant (R1000s):

Perform an analysis of the sales data for the restaurant. Prepare a report for Karen that summarises your findings, forecasts, and recommendations. Include the following:

(i) A graph of the time series

(ii) An analysis of the seasonality of the data. Indicate the seasonal indexes for each month, and comment on the high seasonal and low seasonal sales months. Do the seasonal indexes make intuitive sense. Discuss

(iii) Stating any assumptions you make make, provide forecast sales for January through December of the fourth year

(iv) Recommendations as to when the system that you developed should be updated to account for new sales data that will occur

Two independent methods of forecasting based on judgment and experience have been prepared each month for the past 10 months. The forecasts and actual sales are as follows:

a. Compute the MSE and MAD for each forecast. (Round your answers to 2 decimal places.)

b. Compute MAPE for each forecast. (Round your intermediate calculations to 5 decimal places and final answers to 4 decimal places.)

c. Prepare a naive forecast for periods 2 through 11 using the given sales data. Compute each of the following; (1) MSE, (2) MAD, (3) tracking signal at month 10, and (4) 2s control limits. (Round your answers to 2 decimal places.)

Hypothesis Test: Difference Between Means

Sample A: 35 Observations, Mean = 10.255, Variance=0.310

Sample B : 20 Observations, Mean= 9.004, Variance= 0.831

alpha=0.05

Can you run a hypothesis test for the difference between two means?

Debate if “failing to reject the null” is the same as “accepting the null.” Support your position with examples of acceptance or rejection of the null.

More images for certain company produces and sells frozen pizzas to public schools throughout the eastern United States. Using a very aggressive marketing strategy, they have been able to increase their annual revenue by approximately $10 million over the past 10 years. But increased competition has slowed their growth rate in the past few years. The annual revenue, in millions of dollars, for the previous 10 years is shown.

Year Revenue

1. 8.43

2. 10.94

3. 13.08

4. 14.11

5. 16.21

6. 17.21

7. 18.37

8. 18.55

9. 18.50

10. 18.33

(a.) construct a time series plot, determine the appropriateness of the linear trend.

(b.) develop a quadratic trend equation that can be used to forecast revenue.

(c) Using the trend equation developed in part (b), forecast revenue (in millions of dollars) in year 11.

How do you solve this using R?

The file "flow-occ.csv" contains data collected by loop detectors at a particular location of eastbound Interstate 80 in Sacramento, California, from March 14-20, 2003. For each of three lanes, the flow (the number of cars) and the occupancy (the percentage of time a car was over the loop) were recorded in successive five-minute intervals. There were 1740 such five-minute intervals. Lane 1 is the farthest left lane, lane 2 is in the center, and lane 3 is the farthest right.

(a) For each station, plot flow and occupancy versus time. Explain the patterns you see. Can you deduce from the plots what the days of the week were?

(b) Compare the flows in the three lanes by making parallel boxplots. Which lane typically serves the most traffic?

(c) Examine the relationships of the flows in the three lanes by making scatterplots. Can you explain the patterns you see?

(d) Make histograms of the occupancies, varying the number of bins. What number of bins seems to give good representations for the shapes of the distributions? Are they any unusual features, and if so, how might they be explained?

(e) Make plots to support or refute the statement, "When one lane is congested, the others are, too."

...there is more data that can't fit

Your math professor receives several student emails each day. The probability model shows the number of emails your professor receives from students in a given day.

1. How many emails should your professor expect to receive daily? Round your result to the nearest hundredth.
2. What is the standard deviation of the number of emails your professor should expect to receive? Round to the nearest hundredth.
3. If it takes your professor an average of 7 minutes to reply to each email s/he receives, how many should your professor expect to spend responding to student emails in a given day?
4. Your English professor expects the same mean number of emails with the same standard deviation. What is the mean and standard deviation of the difference in the number of emails the professors will receive.

Mean:

Standard Deviation:

Recall that Benford's Law claims that numbers chosen from very large data files tend to have "1" as the first nonzero digit disproportionately often. In fact, research has shown that if you randomly draw a number from a very large data file, the probability of getting a number with "1" as the leading digit is about 0.301. Now suppose you are the auditor for a very large corporation. The revenue file contains millions of numbers in a large computer data bank. You draw a random sample of n = 230 numbers from this file and r = 88 have a first nonzero digit of 1. Let p represent the population proportion of all numbers in the computer file that have a leading digit of 1.

(i) Test the claim that p is more than 0.301. Use α = 0.05.

(a) What is the level of significance?

State the NULL
State theALTERNATE HYPOTHESES

H0: p > 0.301; H1: p = 0.301

H0: p = 0.301; H1: p ≠ 0.301

H0: p = 0.301; H1: p > 0.301

H0: p = 0.301; H1: p < 0.301

(b) What sampling distribution will you use? The Student's t, since np > 5 and nq > 5. The standard normal, since np > 5 and nq > 5. The Student's t, since np < 5 and nq < 5. The standard normal, since np < 5 and nq < 5. What is the value of the sample test statistic? (Round your answer to two decimal places.)

(c) Find the P-value of the test statistic. (Round your answer to four decimal places.)

(d) Sketch the sampling distribution and show the area corresponding to the P-value.

Consider the following hypothesis test:

H(0): mu ≥ 10

H(a): mu < 10

The sample size is 120 and the population standard deviation is assumed known with σ = 5. Use alpha = .05. If the population mean is 9, what is the probability of making a Type II error if the actual population mean is 8 (to 4 decimals)? Please provide the appropriate formula in excel for solving this problem.

QUESTION 1

A sample of weights of 50 boxes of cereal yield a sample average of 17 ounces. What would be the margin of error for a 90% CI of the average weight of all such boxes if the population deviation is 0.48 ounces?

Round to the nearest hundredth

QUESTION 2

A sample of heights of 117 American men yields a sample average of 57.04 inches. What would be the margin of error for a 95.44% CI of the average height of all such men if the population deviation is 3.8 inches?

Round to the nearest hundredth

QUESTION 3

A sample of weights of 37 boxes of cereal yield a sample average of 17.8 ounces. What would be the margin of error for a 95% CI of the average weight of all such boxes if the population deviation is 0.35 ounces?

Round to the nearest hundredth

QUESTION 4

A sample of weights of 25 boxes of cereal yield a sample average of 16.5 ounces. What would be the margin of error for a 96% CI of the average weight of all such boxes if the sample deviation is 0.73 ounces?

The population of all such weights is normally distributed.

Round to the nearest hundredth

QUESTION 5

:

A confidence interval is to be found using a sample of size 676 and the sample deviation of 5.89.

If the critical value should be a z-score, type the number 0 below
If the critical value should be a t-score, type the number 1 below

*The computer is looking for either the input 0 or the input 1. It will not recognize anything else you type in

Let A and B be two subsets of the sample space of an experiment. If P(A) = 0.35, P(B) = 0.55, and P(A ∩ B) = 0.1, find (i) p(A ∩ Bc) (ii) p(A U B)c (iii) p(A ∩ B)c (iv) p(Ac ∩ Bc)