1. You are testing H0: µ = 0 against Ha: µ > 0 based on an SRS of 15 observations from a Normal population.

   • What values of the t statistic are statistically significant at the a = 0.005 level?

     1. t < - 3.326 or t > 3.326

     2. t > 2.977

     3. t < - 3.286 or t > 3.286

2. To study the metabolism of insects, researchers fed cockroaches measured amounts of a sugar solution. After 2, 5, and 10 hours, they dissected some of the cockroaches and measured the amount of sugar in various tissues. Five roaches fed the sugar D-glucose and dissected after 10 hours had the following amounts (in micrograms) of D-glucose in their hindguts - Amounts of D-glucose: 55.95 68.24 52.73 21.5 23.78

   • The researchers gave a 96% confidence interval for the mean amount of D-glucose in cockroach hindguts under these conditions. The insects are a random sample from a uniform population grown in the laboratory. We therefore expect responses to be Normal.

     1. The mean (±0.01) and the standard deviation (±0.0001) of the SRS are: x =_____   s = _________

     2. The critical value (±0.001) from the distribution for 96% confidence interval is: t*=______

     3. What confidence interval (±0.01) did the researchers give? _____ to _____

3. A study of commuting times reports the travel times to work of a random sample of 22 employed adults in Chicago. The mean is X= 28.28 minutes and the standard deviation is s = 17.2 minutes.

   • What is the standard error of the mean? _____

4. You are testing H0: µ = 100 against Ha: µ < 100 based on an SRS of 15 observations from a Normal population. The data give x⎯⎯⎯x¯ = 7 and = 4.7.

   • The value of the t statistic is _____

5. You are testing H0:μ=100 H0:μ=100 against Ha:μ<100 Ha:μ<100 with degrees of freedom of 24. The t statistic is 2.25

   • The P-value for the statistic falls between ____ and ____

6. You have an SRS of 14 observations from a Normally distributed population.

   • What critical value would you use to obtain a 99.5% confidence interval for the mean of the population? _____

7. The placebo effect is particularly strong in patients with Parkinson's disease. To understand the workings of the placebo effect, scientists measure activity at a key point in the brain when patients receive a placebo that they think is an active drug and also when no treatment is given. The same six patients are measured both with and without the placebo, at different times. The six differences (treatment minus control) had x⎯⎯⎯x¯ = -0.316 and s = 0.169.

   • The value of the t statistic is ______

   • Is there significant evidence of a difference between treatment and control?

     1. Yes

     2. No

8. Researchers claim that women speak significantly more words per day than men. One estimate is that a woman uses about 20,000 words per day while a man uses about 7,000. To investigate such claims, one study used a special device to record the conversations of male and female university students over a four- day period. From these recordings, the daily word count of the 20 men in the study was determined. Here are their daily word counts:                                                 

• • What value we should remove from observation for applying t procedures? ____

  • A 90% confidence interval for the mean number of words per day of men at this university is from ___ to ___ words

  • Is there evidence at the 10% level that mean number of words per day of men a this university differs from 10000?

    1. Yes

    2. No

• Cola makers test new recipes for loss of sweetness during storage. Trained tasters rate the sweetness before and after storage. Here are the sweetness losses (sweetness before storage minus sweetness after storage) found by 10 tasters for one new cola recipe:

• • Take the data from these 10 carefully tasters as an SRS from a large population of all trained tasters

  • Is there evidence at the 5% level that the cola lost sweetness? If the cola has not lost sweetness, the ratings after should be the same as before it was stored

  • The test statistic is t = _____

    1. Yes

    2. No

• There is evidence that cytotoxic T lymphocytes (T cells) participate in controlling tumor growth and that they can be harnessed to use the body's immune system to treat cancer. One study investigated the use of a T cell-engaging antibody, blinatumomab, to recruit T cells to control tumor growth. The data below are T cell counts (1000 per microliter) at baseline (beginning of the study) and after 20 days on blinatumomab for 6 subjects in the study. The difference (after 20 days minus baseline) is the response variable.

  Baseline:    0.04 0.02 0 0.02 0.36   0.24

After 20 days: 0 0.37 1.2   0.05 1.12 0.24

Difference: -0.04 0.35 1.2   0.03 0.76 0

• Do the data evidence at the 1% level that the mean count of T cells is higher after 20 days on blinatumomab?

• The test statistic is t = ____

  1. Yes

  2. No

Research is an integral part of all professional fields. Designing a research study can be a complicated task that can be simplified if the appropriate techniques can be identified. This assignment will give you the opportunity to design an experiment, including finding relevant prior research, determining the appropriate sample, data analysis techniques, and discuss the results you hope to see. Working from the topic chosen earlier in the topic selection, you will be designing your own statistical study. In a 1,250-1,500 word report discuss the design of an experiment that would expand on or relate to the research in the previously chosen article. See the attached document for detailed instructions on how to complete the project. A minimum of four additional scholarly resources are required. MAT-274 Final Project Detailed Criteria Background information explaining the importance of the research (why it should be done) and what has been done in the past. This background section can be a large portion of your paper, perhaps around 25% of the entire word count. Here you explain what previous research has been done on your topic and how this inspired your new study/experiment. You are required to reference four scholarly articles in your final paper. Make sure to mention how the study you designed is different from the previous work you read in your primary research articles. You can also include information in this section about why the topic is important to your field of study or relevant to you in general. Sampling and experimental design with rationale. In this section, you should include your sampling technique, how you are achieving appropriate randomization, and why this technique is the most appropriate for your particular experiment. Make sure you address any possible bias in your sampling technique and how you will consider this in your final results. Conclude this section with a discussion of your population for generalization and how the demographics of your sample achieve this goal. Data analysis techniques (specific inferential test that would need to be used and why, include tests that would need to be done to validate the assumptions needed for the chosen inferential test). This section is the heart of your final paper. The final grading of the project will focus most heavily on this content. There are at least three paragraphs worth of material to comment on in this section. It is essential that you clearly articulate which type of inferential test you are using (z, t, pairedt,pooled t,chi-squared, ANOVA+F-test, etc.). In addition to stating the type of test, you must explain why this test is appropriate. Every statistical test has certain conditions that must be satisfied to make the test have reasonable inferential power (see lecture slides on Loud Cloud). You need to verify that these assumptions are satisfied for your experiment/sample and explain what types of information you would collect to show this; mention any calculations, graphs, charts, and plots you would use. It would be very nice to include some information on how you would use Excel to implement these calculations/charts. The hypothesis test needs to be formally stated (null and alternative clearly and correctly given with variable names and inequalities/equalities in the correct spot). Describe whether this is a one-tailed or two-tailed test, your chosen significance level (with justification), and what the p-value would tell you in the context of your problem. If your test requires follow-up analysis (such as ANOVA, paired-t), you need to mention explicitly what type of follow up you will do and how these calculations would be performed. Why do you need the follow up calculations? What does this analysis tell you? Expected results as well as the questions this research will serve to answer This section can consist of a single paragraph and should discuss what exactly you hope to answer by performing your inferential test described in the previous part. State what results you expect to see for your hypothesis test, what do you expect the p-value to be approximately? What does the p-value tell you about your null/alternative? Would reject/fail to reject the null? Explain what your hypothesis test outcome means in language relevant to your chosen topic. Suggestions for future research. Your paper should end with a concluding paragraph that discusses how your experiment might influence future research. Decide on future experiments that might be performed based off your work here and previous research. Outline any sample size/experimental design changes you would recommend to future researchers. How would this future research expand the work already completed?

Research is an integral part of all professional fields. Designing a research study can be a complicated task that can be simplified if the appropriate techniques can be identified. This assignment will give you the opportunity to design an experiment, including finding relevant prior research, determining the appropriate sample, data analysis techniques, and discuss the results you hope to see. Working from the topic chosen earlier in the topic selection, you will be designing your own statistical study. In a 1,250-1,500 word report discuss the design of an experiment that would expand on or relate to the research in the previously chosen article. See the attached document for detailed instructions on how to complete the project. A minimum of four additional scholarly resources are required. MAT-274 Final Project Detailed Criteria Background information explaining the importance of the research (why it should be done) and what has been done in the past. This background section can be a large portion of your paper, perhaps around 25% of the entire word count. Here you explain what previous research has been done on your topic and how this inspired your new study/experiment. You are required to reference four scholarly articles in your final paper. Make sure to mention how the study you designed is different from the previous work you read in your primary research articles. You can also include information in this section about why the topic is important to your field of study or relevant to you in general. Sampling and experimental design with rationale. In this section, you should include your sampling technique, how you are achieving appropriate randomization, and why this technique is the most appropriate for your particular experiment. Make sure you address any possible bias in your sampling technique and how you will consider this in your final results. Conclude this section with a discussion of your population for generalization and how the demographics of your sample achieve this goal. Data analysis techniques (specific inferential test that would need to be used and why, include tests that would need to be done to validate the assumptions needed for the chosen inferential test). This section is the heart of your final paper. The final grading of the project will focus most heavily on this content. There are at least three paragraphs worth of material to comment on in this section. It is essential that you clearly articulate which type of inferential test you are using (z, t, pairedt,pooled t,chi-squared, ANOVA+F-test, etc.). In addition to stating the type of test, you must explain why this test is appropriate. Every statistical test has certain conditions that must be satisfied to make the test have reasonable inferential power (see lecture slides on Loud Cloud). You need to verify that these assumptions are satisfied for your experiment/sample and explain what types of information you would collect to show this; mention any calculations, graphs, charts, and plots you would use. It would be very nice to include some information on how you would use Excel to implement these calculations/charts. The hypothesis test needs to be formally stated (null and alternative clearly and correctly given with variable names and inequalities/equalities in the correct spot). Describe whether this is a one-tailed or two-tailed test, your chosen significance level (with justification), and what the p-value would tell you in the context of your problem. If your test requires follow-up analysis (such as ANOVA, paired-t), you need to mention explicitly what type of follow up you will do and how these calculations would be performed. Why do you need the follow up calculations? What does this analysis tell you? Expected results as well as the questions this research will serve to answer This section can consist of a single paragraph and should discuss what exactly you hope to answer by performing your inferential test described in the previous part. State what results you expect to see for your hypothesis test, what do you expect the p-value to be approximately? What does the p-value tell you about your null/alternative? Would reject/fail to reject the null? Explain what your hypothesis test outcome means in language relevant to your chosen topic. Suggestions for future research. Your paper should end with a concluding paragraph that discusses how your experiment might influence future research. Decide on future experiments that might be performed based off your work here and previous research. Outline any sample size/experimental design changes you would recommend to future researchers. How would this future research expand the work already completed?

Supplies are dropped from an airplane to land at a certain point. The velocity of the package at release from the airplane is the speed of the airplane, v0x=250ft/s. The acceleration of the package due to gravity isay= -32.2 ft/s2. The displacement in the y direction can be found using the following equation: y - y0 = v0yt + ½ayt2. The final position of the package (y) is on the ground, and y0 represents the height of the plane when the package is dropped. The initial velocity in the y direction (v0y) is zero. Therefore the equation becomes: y = y0 + ½ayt2. The distance the package travels in the x direction can be found from the equation: x - x0 = v0xt + ½axt2. The final position of the package (x) is measured from the initial position (x0). If x0 is taken as zero, and if the plane is traveling at a constant speed (ax is zero), then the equation becomes: x = v0xt. Step-by-step Excel Instructions: 1. Create a table for the initial data: i. In cell B2 put the label “Plane height:” ii. In cell C2 put the initial height of the plane in feet (ft): 350 iii. In cell B3 put the label “Acceleration (g):” iv. In cell C3 put the acceleration of gravity in ft/s^2: -32.2 v. In cell B4 put the label “Velocity:” vi. In cell C4 put the velocity in ft/s: 250 vii. In cells D2, D3, and D4, place the appropriate units 2. Create a table for the data and calculations: i. In cells B6, C6, and D6 respectively, put the labels “t”, “x”, and “y”. ii. In cell B7, enter the initial time: 0 iii. Increment the time in ½-second intervals in column B, from B8 to B16. iv. Center all of the labels and data in columns B, C, and D. v. Enter the formulas to calculate 1) x in cell C7 and 2) y in cell D7. vi. Copy the formula from C7 to C8 through C16 and from D7 to D8 through D16. vii. Format the numbers in the y column to one decimal point. 3. Create separate graphs of 1) “x vs. t” and of 2) “y vs. t”. Using the “x vs. t” graph as an example: i. Select the x data (C7:C16), and then select the “line with markers” plot type. ii. To add the time on the horizontal axis, right-click on the chart and chose “Select Data…”. In the “Select Data Source” dialog box, chose “edit” for the Horizontal (Category). In the next dialog box, simply select (drag the mouse over) the time data (B7:B16). iii. Add major vertical gridlines, chart titles, and axis labels using the buttons under the “Layout” tab. Include the correct units in the axis titles and rotate the vertical axis title to the horizontal. iv. Remove the “series” labels from these two charts (Layout/legend). v. Repeat these steps for the “y vs. t” graph. 4. Create a graph of “x and y vs. t” i. highlighting the x and y data before choosing the chart type or by copying and modifying one of the existing charts using the “Select Data…” command. ii. Change the series labels to read “x” and “y” or “horizontal distance” and “vertical distance”. iii. Add the appropriate chart title and axis labels. 5. Use trial and error: i. Change the values in the “t” column to determine, by trial and error, the time at which the package hits the ground. b. Using the “Goal Seek” tool: i. Goal Seek can be found under the “Data” tab, “What-If Analysis” button. ii. To use goal seek, open the Goal Seek dialog box: Set cell: D16, To Value: 0, By changing cell: B16. iii. Record your answer in B18, then return the spreadsheet to its initial configuration. What to Submit: Write a memorandum to the instructor that explains the data tables and the graphs. DO NOT refer to “cell B18” or any other cell (When looking at the data table in a Word document, how can you locate cell D9?). 1. Copy and paste the graphs (3) and the data tables into a Word document. It is recommended that you paste the data tables and each graph separately as a Picture (Windows or Enhanced Metafile). Do not paste the data or the graphs as a Graphic Object, or as an Excel Object (use “Paste Special” found under “Paste” on the Ribbon). Use appropriate titles or captions. 2. Explain each graph and data table. In the text, refer to each graph and table using appropriate labels. 3. Explain the number (time) obtained by using the “Goal Seek” function. 4. Carefully arrange the text, data tables, and charts to print correctly (use Print Preview). 5. Insert page numbers and a header if you have multiple pages.

Part I The input to the program will be a text file containing the information for a tolerance table. An example follows using the values from the first lecture on tolerance analysis. These values will be stored in a text file. The data is comma delimited, which means that each data field is separated by a comma. If the first word is ‘PART’ the following values are the nominal size, +/- impact, tolerance, and fixed/variable. If the first word is ‘GAP’ the following values are the minimum and maximum gap sizes. (Note: assume all units are inches.) PART,2.000,-1,0.050,V PART,0.975,-1,0.025,V PART,3.000,+1,0.010,F GAP,0.000,0.080 These input values will be processed using the methods taught in class. A sample output for the first stage is given. Actual Gap Mean: 0.025” Actual Gap Tolerance: 0.085” The Maximum Gap (0.110”) is (Greater) than specified (0.080”) The Minimum Gap (-0.060”) is (Less) than the specified (0.000”)  

Part II The second stage extends the Stage 1 analysis. In this stage the program will suggest various combinations of part dimensions and tolerances to meet the gap specifications. The fixed dimension parts are not able to have their dimensions or tolerances adjusted. Take the required adjustment to all the variable parts and apply this adjustment to each part equally as a percentage of the total part dimension. Round dimensions to the nearest thousandth. Do the same application to adjust the gaps of all parts to have the gap fully use the available tolerance. Example Input: PART,2.000,-1,0.050,V PART,0.975,-1,0.025,V PART,3.000,+1,0.010,F GAP,0.000,0.080 Example Output: Recommended Adjustments to meeting GAP,0.000,0.80: PART,1.990,-1,0.020,V PART,0.970,-1,0.010,V PART,3.000,+1,0.010,F Math used to get to the result Variable parts should add to (3 – 0.04) = 2.96 Variable parts actually add to (2 + 0.975) = 2.975 All variable parts must be adjusted to 2.96/2.975 = 99.496% of the original value Variable tolerance should add to (0.04 – 0.01) = 0.03 Variable tolerance actually add to (0.05 + 0.025) = 0.075 All variable parts’ tolerance must be adjusted to 0.3/0.073 = 40% of the original value

Part III The third stage involves a statistical analysis called Monte Carlo simulation. Basically each of the dimensions is varied randomly and the gap is calculated. This random calculation is repeated hundreds or thousands of times. For each iteration, the individual gap value is calculated and stored in an array and in a file. The array of values will be used to compute the mean and standard deviation of the gap. The file will be opened using a spreadsheet program to graph a histogram, calculate an average, and calculate the standard deviation, which should match the result from your program. These values will then be used to estimate the number of rejected assemblies during production. It is reasonable to assume that the tolerance for a part is 3 standard deviations (99.73% of parts will fall within the tolerance). So for any part, we can generate random realistic values by taking the nominal value and adding/subtracting a random number, which represents variations due to the tolerance. To do this, we will need to generate a specific type of random numbers. The standard random number function in most programming language (rand() in C included) has a uniform distribution. This means that if we are finding random numbers from 0.0 to 1.0, the probability of getting 0.5 is the same as getting 0.1. This is not realistic for our application, since it will be more likely that we have our dimensions change by 0.1 than it is 0.5. For this reason, we need to modify the numbers from the rand() function so that they have a Gaussian (Normal) Distribution, which is sometimes referred to as the “bell curve”. This can be accomplished by using the Box-Muller Transformation. Although it sounds complicated, this transformation can be easily done and applied to generate a random dimension with the code given. Summary of Part 3: Apply the random_dimension() function below to get an output of a random_value of each part that will follow the explanation above. This will create a statistically likely value for each dimension given that you can then use to rerun the “actual mean gap” calculation from Part 1 1000 times. For each calculation, have the program store the value as a line in a text file (.csv extension.) You’ll be able to open this file up using Excel as a .csv file. In Excel, graph a histogram, calculate the average gap of all assemblies (of parts), and the standard deviation of the gap of all assemblies. void random_dimension(double nominal, double tolerance, double *random_value){ double r1, r2, r12; double sigma = tolerance / 3; do{ r1 = (double)( rand() % 10001 ) / 10000; }while(r1==0); r2 = (double)( rand() % 10001 ) / 10000; r12 = sqrt(-2*log(r1))*cos(2*M_PI*r2); *random_value = nominal + sigma * r12; }

Introduction:

As a healthcare professional, you will work to improve and maintain the health of individuals, families, and communities in various settings. Basic statistical analysis can be used to gain an understanding of current problems. Understanding the current situation is the first step in discovering where an opportunity for improvement exists. This course project will assist you in applying basic statistical principles to a fictional scenario in order to impact the health and wellbeing of the clients being served.

This assignment will be completed in phases throughout the quarter. As you gain additional knowledge through the didactic portion of this course, you will be able to apply your new knowledge to this project. You will receive formative feedback from your instructor on each submission. The final project will be due on week 10.  

Scenario:

You are currently working at NCLEX Memorial Hospital in the Infectious Diseases Unit. Over the past few days, you have noticed an increase in patients admitted with a particular infectious disease. You believe that the ages of these patients play a critical role in the method used to treat the patients. You decide to speak to your manager and together you work to use statistical analysis to look more closely at the ages of these patients. You do some research and put together a spreadsheet of the data that contains the following information:

Client number

Infection Disease Status

Age of the patient

You need the preliminary findings immediately so that you can start treating these patients. So let’s get to work!!!!

Background information on the Data:

The data set consists of 60 patients that have the infectious disease with ages ranging from 35 years of age to 76 years of age for NCLEX Memorial Hospital. Remember this assignment will be completed over the duration of the course.

Perform the hypothesis test

Claim: The average age of all patients admitted to the hospital with infectious diseases is less than 65 years of age. Test the claim using alpha=0.05 and assume you data is normally distributed and sigma is unknown.

Document the following steps.

1. Write the null and alternative hypothesis symbolically and identify which hypothesis is the claim.

2. Is the test two-tailed, or right-tailed? Explain

3. Which test statistic will you use for your hypothesis test; z-test or t-test? Explain.

4. What is the value of the test statistic? Show your calculation

5. What is the P-value? Explain how you determined it.

6. What is the critical value? Explain how you calulated it.

7. What is your decision? Reject the null or do not reject the null? Explain why you made your decision including the results for your p-value and the critical value.

8. State the final conclusion in non-technical terms.

Please show your work for the construction of the test-statistic and explain your process for finding the p-value and critical value. You may use the Equation Editor to format your calculation steps on the Word document or attach an Excel spreadsheet clearly showing each calculation for #B4 and #B5, but your answers still need to appear on the Word document. Also, be sure to number each response in your paper using the same numbers as above

1. Start a new worksheet and name it Z-scores. Use the STANDARDIZE function in Excel to calculate the z-scores for problems 2 and 4 on page 401 and problems 2 and 4 on page 412. Read Examples T.3 and T.4 on page 422 to see examples of how to use STANDARDIZE with means and proportions. Your output should look like the partial worksheet at right, except that cells C3, C4, C9, and C10 should be filled with the correct z-scores for each problem. (4 pts)

2. Start a new worksheet and name it Puppies. Then, complete the following: Suppose you are thinking about getting a puppy and want to know the amount of time people spend caring for their puppies. You survey 31 puppy owners and find that the mean amount of time they spend caring for their puppies is 108.0 minutes per day, with a standard deviation of 17.0 minutes. Construct and interpret a 98% confidence interval for the mean amount of time puppy owners spend on their puppies. Be sure to read page 500 and then use either Example T.7 or T.8 as a guide, whichever applies to this situation. Store your margin of error in cell A1. Then, write two (or more) complete sentences stating and interpreting your confidence interval. Write these in your worksheet in cell A4. For rounding, use the rounding rule on page 432.

Worth 4 points: 1 point for inputting data correctly, 1 point for getting the correct margin of error, and 2 points for correctly stating and interpreting the confidence interval.

3. Start a new worksheet and name it Chips. A random sample of 200 computer chips is obtained from a factory and 4% are found to be defective. Construct and interpret a 95% confidence interval for the proportion of all computer chips from the factory that are defective. Use Example T.9 on page 501 as a guide and format your answer like the example. (Note: Be sure that you are clear about what x, n, and p-hat are in this problem before you just enter numbers into Excel.) Write your sentences in cell A9. (The function in Excel 2007 is NORMSINV, but you will need to read about the NORMSINV function and think about what the first parameter will need to be to do this problem correctly.)

Worth 4 points: 1 point for inputting data correctly, 1 point for calculating the correct margin of error, and 2 points for correctly stating and interpreting the confidence interval.

Part 2

For problems 4-5, perform hypothesis tests for each of the following scenarios. You may use Excel, manual calculation, or a TI-83 or TI-84 calculator to compute your results. Submit your project to the Project 3 assignments folder on Brightspace by the due date. The easiest way to complete this project is to just take this Word document, fill in your answers, save it and submit to the assignments folder as Project3.docx. If you don’t have Word on your computer, you can print the pdf version of this document, write in your answers, and then scan it to a new pdf before submitting.

Grading for each problem is as follows:

Hypotheses: 1.5 points = To receive full points, hypotheses (both H0 and Ha) must be stated correctly, either in words or in symbols. Examples: “µ ≥ 35” or “Population mean is greater than or equal to 35”.

Test stat and value: 1 point = Identify the correct test statistic and its value (Example: t = 2.215)

P-value (or Critical Value): 1 point = Correct p-value (or Critical value on #4) of test is given.

Conclusion: 1.5 points = State how you decided and whether you reject or fail to reject null hypothesis. Then, include a full sentence description of what this means in this particular problem. (Example: “Since the p-value > the 0.05 significance level, fail to reject H0. There is not enough evidence to support the claim that listening to music while studying increases your chances of getting an A.”)

4. A children’s clothing company sells hand-smocked dresses for girls. The length of one particular size of dress is designed to be 26 inches. The company regularly tests the lengths of the garments to ensure quality control, and if the mean length is found to be significantly longer or shorter than 26 inches, the machines must be adjusted. The most recent simple random sample of 28 dresses had a mean length of 26.30 inches with a standard deviation of 0.77 inches. Perform a hypothesis test at the 0.01 level of significance to determine if the mean dress length has changed.

Hypotheses:

Test statistic and value:                                                                  P-value or Critical value:

Conclusion:

5. CNN/Money reports that the mean cost of a speeding ticket, including court fees, was $150.00 in 2002. A local police department claims that this amount has increased. To test their claim, they collected data from a simple random sample of 160 drivers were fined for speeding in the year 2002 and found that they paid a mean of $154.00 per ticket. Assuming that the population standard deviation is $17.54, is there sufficient evidence to support the police department’s claim at the 0.01 level of significance?

Hypotheses:

Test Statistic and value:                                                                     P-value:

Conclusion:

Jerry is a 35-year-old man who is studying horticulture part-time at his local TAFE and working part-time for the government in a forestry role. Jerry has had bipolar disorder since his late teens but was only officially diagnosed three years ago. Recently, Jerry has started staying up longer during the night working on his assignments, and for the past five days he has not slept at all. For the past month, Jerry has only been sporadically taking his prescribed medication. Last week Jerry’s neighbours made a complaint to the body corporate in the unit where Jerry lives after he did some gardening in his courtyard at 3 am, followed by mowing the communal areas at 4.30 am. Jerry thinks his neighbours need to ‘chill’ and that he was actually in the middle of a breakthrough that could result in reversing global warming. Jerry believes that his neighbours should mind their own business and stop interfering with his creativity, and he cannot understand why they are confused by his ideas. Jerry believes he is on the ‘verge’ of a major discovery. While he was writing his latest assignment, his research helped him unearth a discovery that will reverse global warming, resulting in him making millions of dollars. When the morning came, Jerry quit his job. Jerry’s major concern now is what will happen if he accidentally reverses global warming too much and the temperature becomes too cool. While he is worried about this, he believes everything will probably be okay, because it all comes down to the word ‘land’ and it will ‘even out’, but he does want to seek clarification on this. Jerry is reassured because people live in Iceland, Greenland, Ireland and Poland and these are all cold climates. It will all balance out because there are equal numbers of countries in warmer climates that have the word ‘land’ in them, too, such as Swaziland, Thailand, New Zealand and the Falklands. Outcomes being ‘even’ is of great importance to Jerry. Jerry’s father Paul visited him a few days ago for dinner and is worried about him. Despite Paul making dinner, Jerry couldn’t sit still long enough to eat it. Jerry doesn’t want to talk about the possibility that he may be unwell again, because, he says, ‘It’s not like last time, Dad.’ Yesterday, Jerry attended the Polish embassy requesting they work with him on his project. He demanded to see the ‘most senior person here’ because they would be the only one who could understand his discovery. Both the Thai and Irish embassies had refused to return his calls. Jerry became upset when a representative from the Polish embassy exports department would not meet with him. Jerry was talking rapidly and loudly, and staff could not follow the topic of his conversation. Jerry became irritated when staff didn’t provide the information he wanted and eventually security was called. Jerry was taken to his local hospital for assessment and later admitted.

1. You have been asked to formulate a risk assessmentfor Jerry. Based on the information in the case study, what risks would you identify? Use the form attached to this tutorial guide.
2. Describe these features of the presentation of mania: pressured speech, disinhibition, punning, grandiose delusions, and second person auditory hallucinations. Provide examples from the video, or from Jerry’s case study.
3. Jerry became irritated and security were called, and he was taken to his local hospital for assessment. What is the difference between ‘voluntary’ and ‘involuntary’ treatmentin the context of mental health act legislation in your state or territory?
4. Treatment for Bipolar Disorder includes antipsychotics, anxiolytics, antidepressants and most commonly mood stabilizers. Investigate the following psychotropic medications known as Mood Stabiliser- Lithium Carbonate, Sodium Valproate, Lamotrigine and Carbamazepine. Consider the importance of effective monitoring, consumer experiences(side effects) and safety factors(e.g. Lithium Toxicity). Discover the other therapeutic use for the last three medications.
5. The mental state examination (MSE) is a formal assessment used in both diagnostics and ongoing assessment. How can the principles of a therapeutic relationshipfacilitate the processof obtaining information through an MSE?
6. Australia’s legal system requires health care clinicians to operate within a ‘least restrictive’ framework. Discuss where this approach is evident in the mental health act legislation in your state.
7. What does the mental health legislation act in your state or territory stipulate about ‘recovery’?
8. How can the mental health nurse apply Bandura’s concept of self-efficacyto support consumers in medication self-management?

• Submit a business proposal for a new business (A new "start-up" venture that you or a group of people are contemplating)
• Submit a new project proposal (Possibly one that you and/or your firm is working on now or recently completed)

Prepare a proposal using the requirements list below. The proposal should focus on solving a organizational problem and provide for cost savings and/or revenue-generation. I suggest that you use a project that you have or plan to propose to your organization or a start new business that already exist and that you would like to start someday. It is much easier to work with actual figures than to make up a fictitious company and researching what the possible figures might be. The proposal should include all (but is not limited to) the following information:

• Briefly describe the Business venture/project and its relationship to the organizational mission.
• If this is a new business, what is the legal structure (Partnership, Corporation or S Corporation)?
• What method of accounting (Cash method Vs Accrual method) will you use? Why?
• How will you price your product and/or products? What is the mark up on the product? What pricing strategy, Target Price and/or Cost Plus Price? Use this in the Sales Budget.
• You should explain if you are tracking cost using Job Order Cost system, Process Cost system, Operating Cost system, Activity Based cost system (for overhead) and/or a combination of the systems
• Create a 1year Master Budget for the business/project.
• Prepare Cash budget (and/or Cash Flow statement) and provide a brief analysis of cash flows from Operation, Investing and Financing activities (Cash flow statement analysis)
• Break Even Analysis, Target Profit and Margin of Safety in units and Sales Dollars for the Business/Project
• Discuss the Return on Investment and/or Economic Value Added for the business/program/project to measure its projected performance.
• What is the Business/Project's Payback Period, Accounting rate of return and Net Present Value?
• If capital equipment is involved, is there a lease or buy decision - (NPV analysis).
• If new a Business or Project, calculate and show the Present Value of the Business or Project using NPV analysis based on the expected future cash flows (possibly from Cash Budget or Cash flow statement).
• Do you require new personnel, if so complete and submit a brief job description?
• How will you fund this new program? Raising capital for the Business/project/program through funds internally (Retained Earning) to the company or externally via Bonds/Loans and/or Equity from investors.
• Evaluation business/project comparing following ratios with Industry and/or major competitor
  • Profitability and Total Asset Management by calculating the following ratios: Profit Margin, Asset Turnover and Return on Asset
  • Solvency by calculating the following ratios: Debt to Equity and Time Interest Earned
  • Liquidity by calculating the following ratios: Cash flow yield, Cash flow to Sales, Cash flow to assets and finally Free Cash Flow and Time Interest Earned
• Have a conclusion convincing financer/management to finance the Business/Project.

This write up document in Microsoft word document should be no more than 10 pages. The cover sheet should include the type of proposal you are submitting, the name of your team members (if applicable) and their role in the project. Second page should be an executive summary giving a brief description of the project and any information you find pertinent (maximum 250 words). Your write up should provide analysis and summary touching on the requirements of the project. You can have supporting documents in the appendix that will not be counted towards the 10 pages of write up.

Format is important, and you are expected to present the information in an attractive, professional manner. If your use references, please make sure they are cited either in the footnotes or at the end of the paper. A title page and a table of contents lends to the organization of the paper. The document must be double-spaced, and professionally prepared (i.e., using basic APA style and/or www.isiresearchsoft.com for bibliographic formatting resources) spell-checked, clearly organized, and clearly summarized, with accurate citations for all referenced work.

You may only use Microsoft Word or Excel to develop your paper; remember that you must show your calculations. Papers submitted in .pdf format are also acceptable.
If you include proprietary information from your organization, please mark your paper confidential to ensure that its contents will not be used as an example in future classes.

Lastly, please make sure that the project employs some form of financial statements, capital expenditure worksheets, and/or any other pertinent accounting support schedules that we will employ throughout this course. Every project that is submitted must have some numerical support and accounting schedules, not just a written analysis.

The Orthotic Group case study demonstrates how performance management is important to continuously improve. As you read the case, think about the balanced scorecard approach and how you would set metrics for your team to generate the results needed to remain competitive. The Orthotic Group, located in Ontario, Canada, prides itself on providing superior service to healthcare professionals globally. A custom manufacturer of orthotics that can be inserted into footwear, the company also supplies compression hosiery and footwear. Healthcare professionals can order online through the website, through two technological options, Gaitscan or OHI1Scan or by sending foot impression forms through the postal service. With a strong customer base, The Orthotic Group is considered a leader in the industry as a result of their quality, order cycle time, and problem resolution process. In 2017, after a competitive analysis, it was determined that delivery times from order placement to delivery in the industry had become more competitive. Along with this new competitive requirement, performance metrics for the past 6 months had been slipping from their previous norms. While there had been some minor turnover amongst the production staff, the turnover was no more than previous years. A new manager had been hired who had been making changes. Some of these changes were popular with the production workers, while others were not. Work-in-Process (WIP) inventory began to pile up in key areas of the production line. The new manager left the organization 3 months prior to the busy fall season. The Vice-President Operations thought it would be a good opportunity to embark upon a Lean Process Improvement initiative with the employees. The goal was to reduce the turn-around-time (TAT) and work-in-process inventory (WIP), while maintaining and improving the quality of their orthotics. The Production Supervisor compiled a team of workers from production to gain their insights into what was slowing the team down. Through observations and collaboration with the team it was noted that the following conditions were preventing The Orthotic Group from achieving their targets: While the company had a metric board on the T.V. screen posted above the production line, the first production step, the Technician cell, did not know how many orthotics they produced as a team. Results were provided the next day as a component of the daily stand-up, Workers were processing orders in batches of 10 or more, There was a high degree of variability in worker productivity, First-in-First-Out (FIFO) priority system was not being maintained as workers would work on “easy” orders first instead of higher difficulty orders to push the orders through. At this point the Production Supervisor is preparing a report to discuss priorities with the Vice President – Operations.

The Orthotic Group case study demonstrates how performance management is important to continuously improve. As you read the case, think about the balanced scorecard approach and how you would set metrics for your team to generate the results needed to remain competitive.

Questions:1 Explain what a Lean Process Improvement plan is? What is involved in this type of initiative? (15%) Please use your original words and thoughts and only use direct quotes to prove a point in your arguments. References may be required if you are utilizing outside resources. Copying word for word or paraphrasing can lead to Academic Misconduct. This applies to all questions.

Question: 2 From a functional perspective, which category(ies) of performance metrics are likely currently in use at the manufacturing center prior to the Lean Improvement Process. Explain why you believe this? Is this the right approach going forward given the Lean Improvement initiative? (20%) See warning in Question 1.

Question: 3 What role does IT have in the company when it comes to performance measurement? In your opinion is the Information Technology resources being employed effectively? What are your recommendations? (20%) See warning in Question 1.

Question: 4 Develop 5-6 key metrics (for the balanced scorecard) the company should measure in the manufacturing environment as a result of a lean Improvement initiative. Why are these important? What purpose do they serve? Try to look beyond the textbook for key ideas of what will influence world-class performance for the company. (20%) See warning in Question 1.

Question: 5 Your group represents the team that has been operating the Lean Improvement Process and you are writing a short executive summary (1 page minimum) to the VP Operations so the VP can show the executive group the recommendations. Based on questions 1-4, and the problems they have identified, write up the executive summary with your conclusions and supporting rationale for these improvements. (25%) See warning in Question 1, and the problems they have identified, write up the executive summary with your conclusions and supporting rationale for these improvements. (25%) See warning in Question