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RES5115: RESEARCH PREPARATION: PRINCIPLES AND APPROACHES QUANTITATIVE ASSIGNMENT(SPSS)


RES5115: RESEARCH PREPARATION: PRINCIPLES AND APPROACHES QUANTITATIVE ASSIGNMENT(SPSS)

 

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SCHOOL OF SCIENCE
_______________________________________________________________________________________________
RES5115: RESEARCH PREPARATION: PRINCIPLES AND APPROACHES
QUANTITATIVE ASSIGNMENT
DUE DATE: Friday 28th of October 2016 before midnight
For this assignment, you are expected to perform all analyses using either SPSS or Excel/Real Statistics. However prior to this, you will need to generate your own sub-sample (unique to your student ID) from a larger sample using the random number generator in Microsoft Excel. To do this, you must first activate the Analysis ToolPak in Excel by following steps below.
Step 1: Open a new Excel spreadsheet as shown below.
2
Step 2: Go to File → Options.
Step 3: Click on Add-ins and then click Go…
3
Step 4: Select Analysis ToolPak and click OK.
You can now use the Analysis ToolPak under the Data tab by clicking on Data Analysis.
Note that the above steps are for Microsoft Excel 2010 and may differ slightly if you are using the 2013 version.
4
QUESTION 1 [25 MARKS]
BACKGROUND
A study was conducted to investigate the effects of short-term treatments with growth hormone (GH) on biochemical markers of bone metabolism in men with idiopathic osteoporosis. Subjects ranged in age from 32 to 57 years. Among the data collected were serum concentrations of insulin-like growth factor binding protein-3 at 0 and 7 days after the first injection and 1, 4, 8 and 12 weeks after the last injection (i.e. post- treatment) with GH. The serum concentration data for 116 men are given in the Excel file “Serum.xlsx”.
TASK 1 – SELECTING A SUB-SAMPLE
Open the Serum.xlsx data file as shown.
Click on the “Data” tab and then run the “Data Analysis” tool pack.
5
Select Random Number Generation and click OK.
Select “Uniform” in the drop-down menu next to “Distribution”. Then fill out the other boxes as shown. In the box corresponding to “Random Seed”, make sure you type the last two digits of your student ID here. This will ensure the set of random numbers is unique to you (unless someone else shares the same two numbers).
You should now be able to see 116 random numbers in Column H. Take note that your numbers will be different to those shown here.
Last two digits only
6
Highlight all the data in from Columns A to H using the mouse/keyboard. Then click on   and select Custom Sort…
Now click on  next to ColumnSort by and select (Column H). Make sure that under Order, it is set to Smallest to Largest. Then click OK.
The data are now sorted according to Column H. Again, note that what is shown here is very likely to be different to what you will have. Now, select the first 60 observations (i.e. Rows 2 to 61) from Columns A to G and copy this sub-sample across to SPSS or another Excel spreasheet (e.g. Sheet 2). These observations form the dataset that you will be working with for this question.
7
TASK 2 – ANALYSING THE DATA
(i) Use SPSS or Excel/Real Statistics and generate the necessary summary statistics and figures to describe the serum concentrations 0 and 7 days after the first GH injection. Proper interpretation of these output in the context of the problem is expected. (ii) Use the appropriate test in SPSS or Excel/Real Statistics and determine whether the GH treatment had any significant impact on serum concentration 7 days after the 1st injection. You will need to comment on the nature and extent of these differences (if any). Hypothesis statements are not necessary.  (iii) Confidence intervals should be presented and interpreted whenever possible. (iv) All relevant assumptions associated with your chosen test must be verified. (v) Repeat steps (i) – (iv), but in this instance compare the serum concentrations 1, 4, 8 and 12 weeks after the last GH injection. If the initial analysis suggests a difference, you will then need to perform a post hoc test to determine where the difference(s) lie. Hypothesis statements are not necessary. (vi) Based on the outcomes of the two analyses, comment on the short-term and post-treatment effect of GH treatment on serum concentrations.

8
QUESTION 2 [25 MARKS]
BACKGROUND
Mental illness within the Australian population is becoming more apparent. A nationwide survey in 2007 on mental health and wellbeing conducted by the Australian Bureau of Statistics (ABS) found that an estimated 3.2 million Australian (20% of the population between the ages of 16 and 85) had a mental disorder in the twelve months prior to the survey, and the estimated economic impact of mental health problems is up to $20 billion each year.
The mental health of fly-in/fly-out (FIFO) workers in resources sector became a subject of interest in recent years. Although the financial reward is great, reports of FIFO practices negatively impacting the workers and their Australian families are not uncommon.
To determine the extent of the mental health problem in the resources industry, a health and well-being survey was carried at a particular mining company. In the survey are questions relating to the worker’s demographics, behaviour in the past twelve months, work/lifestyle/family-related issues and others.
Also included in the survey are the Kessler’s mental health questions which will allow one to clinically determine the severity of mental health problems for an individual. The Kessler questions were developed by Professor Kessler and Mroczek (1992) to assess the severity (“1 = None of the time”, “2 = A little of the time”, “3 = Some of the time”, “4 = Most of the time” or “5 = All of the time”) of anxiety and depression related symptoms experienced in the past month. Collectively, they are the Kessler 10 or K10 questions. A K10 score is calculated by summing the scores of the 10 questions. The minimum possible score is 10 (low distress) and the maximum being 50 (very high distress).
Suppose that you are interested in examining whether there is an association between worker’s behaviours and their distress levels in the past 12 months.  The items of interest are presented in Table 1 and the relevant survey data are given in the Excel file “Mental Health.xlsx”. Note that a blank entry represents a missing response.
Table 1   Items of interest in the Health and Well-Being questionnaire Over the past 12 month (1 = Daily; 2 = Weekly; 3 = Monthly; 4 = Once or Twice; 5 = Almost never) (1) How often have you felt worn out? (2) How often have you been emotionally drained? (3) How often have you been irritable? (4) How often have you had aches and pains? (5) How often have you argued with a work colleague? (6) How often have you felt anxious? (7) How often have you had no energy or enthusiasm? (8) How often have you had 6 or more standard drink in one session? (9) How often have you used prescription or non-prescription drugs? (10) How often have you missed a meal? (11) How often have you argued with friends or family? (12) How often have you had trouble sleeping? (13) How often have you exercised?
9
TASK 1 – SELECTING A SUB-SAMPLE
Open the Mental Health.xlsx data file as shown.
Click on the “Data” tab and then run the Analysis ToolPak by clicking on Data Analysis.
Select Random Number Generation and click OK.
10
Select “Uniform” in the drop-down menu next to “Distribution”. Then fill out the other boxes as shown. In the box corresponding to “Random Seed”, make sure you type the last two digits of your student ID here. This will ensure the set of random numbers is unique to you (unless someone else shares the same two numbers).
You should now be able to see 1269 random numbers in Column O. Take note that your numbers will be different to those shown here.
Last two digits only
11
Highlight all the data in from Columns A to O using the mouse/keyboard. Then click on   and select Custom Sort…
Now click on  next to Column → Sort by and select (Column O). Then click OK.
The data are now sorted according to Column O. Again, note that what is shown here (next page) is very likely to be different to what you will have.
12
Now, select the first 150 observations (i.e. Rows 1 to 151) from Columns A to N. Copy this sub-sample across to another spreadsheet (e.g. Sheet 2) in Excel. In the example below, Sheet 2 was renamed to Sub- sample.

13
TASK 2 – SELECTING ITEMS FROM THE QUESTIONNAIRE TO ANALYSE
Now that you have your sub-sample, here you will determine which THREE (3) of the 13 items to analyse. Again, go to the “Data” tab and then run the “Data Analysis” tool pack. Select “Random Number Generation” and click “OK”.
Now generate 13 random uniform numbers and store them in Column P of the sub-sample spreadsheet. In the “Random Seed” box, type the last two digits of your student ID again.
You should now be able to see 13 random numbers in Column P. Take note that your numbers will again be different to those shown here. Now, type the numbers 1 – 13 (to represent the items) in Column Q and right next to the random numbers that you have just generated.
Last two digits only
14
Now, highlight all the numbers in Columns P and Q using the mouse/keyboard. Then sort the numbers by
clicking  and then   Sort Smallest to Largest.
The first three numbers in Column Q refer to the items in Table 1 that you will need to analyse. In this example, these are items (1), (3) and (13). Copy the relevant data for the 3 items and the corresponding K10 scores across to SPSS or another Excel spreadsheet (e.g. Sheet 3). These observations form the dataset that you will be working with for this question.
TASK 3 – ANALYSING THE DATA
(i) Use SPSS or Excel/Real Statistics and generate all necessary summary statistics and figures to describe the relationship between the workers’ mental health (according to the K10 scores) and each of your selected items (make sure you consider each item separately from the others). Proper interpretation of these output in the context of the problem is expected. (ii) Use the appropriate test in SPSS or Excel/Real Statistics and determine whether there is a difference in distress levels across the response categories for these each of these items. If so, perform a post-hoc test to determine where the difference(s) lie. You will need to comment on the nature and extent of these differences (if any). Hypothesis statements are not necessary.  (iii) Confidence intervals should be presented and interpreted whenever possible. (iv) All relevant assumptions associated with your chosen test must be verified.  (v) Briefly comment on the practical implications of your findings and how they may be useful.
15
SUBMISSION GUIDELINES:
This assignment must be completed using either SPSS or Excel/Real Statistics. It is expected that your assignment solutions are presented in the context of the problem. Simply stating the numbers from the output table will not suffice. Examples of this are given on Blackboard in the Quantitative weekly folders corresponding to the workshop weeks. The write-up of your analyses must be presented in Microsoft Word in Times New Roman format with 11-pt font with single spacing and in grammatically correct English. The page margins must be 2 cm for all sides. Failure to do so will result in deduction of marks. Furthermore, no handwritten assignments will be accepted. Copy only the relevant outputs, tables and/or figures from SPSS or Excel across to the Word document. All tables and figures must be labelled appropriately. The write-up for each question (not each part) must not exceed THREE (3) pages (including all tables and figures). Any lines exceeding the three-page limit will not be considered or read. Your assignment submission will also need to include the dataset that is unique to your student ID, along with a cover page (see page 16).
You are reminded of the declaration
“I certify that the attached assignment is my own work and that any material drawn from other sources has been acknowledged”.
that you sign when you complete the coversheet. The assignment solutions must be your own work.
You must submit your completed assignment via Turnitin by Friday 28th of October 2016 before midnight. In the interests of fairness, submission extensions will be given only in exceptional circumstances, and then only in accordance with University rules (see page 17).
Note: If your datasets do not match the ones generated with your student ID (last two digits only), you will be awarded a mark of zero regardless of whether the analysis is correct.
SUBMISSION CHECKLIST:
Your submission will need to be a single document containing the following:
o Cover sheet (1 page) o Your solutions to Questions 1 and 2 (maximum of 3 pages per question). o Your datasets (No restriction)
MARKING GUIDELINES:
(1) Adherence to submission guidelines above (10%) (2) Correct selection and implementation of tests and with correct findings (30%) (3) Proper presentation and interpretation of results in the context of the study and objective(s) (30%) (4) Use of statistics to support and re-inforce findings and arguments (15%) (5) Spelling, grammar and overall narrative (15%)
The above marking guidelines are estimates and variations may occur. If a test is incorrectly chosen, then only a maximum of 10 marks is attainable.
16
ASSIGNMENT COVER SHEET Electronic or manual submission
Form:  SSC-115-06-08
UNIT CODE:        TITLE:
NAME OF STUDENT (PRINT CLEARLY)                          FAMILY NAME                                  FIRST NAME
STUDENT ID. NO.
NAME OF LECTURER (PRINT CLEARLY)

DUE DATE
Topic of assignment

Group or tutorial (if applicable)

Course

Campus

I certify that the attached assignment is my own work and that any material drawn from other sources has been acknowledged.   Copyright in assignments remains my property.  I grant permission to the University to make copies of assignments for assessment, review and/or record keeping purposes.  I note that the University reserves the right to check my assignment for plagiarism.  Should the reproduction of all or part of an assignment be required by the University for any purpose other than those mentioned above, appropriate authorisation will be sought from me on the relevant form.
OFFICE USE ONLY
If handing in an assignment in a paper or other physical form, sign here to indicate that you have read this form, filled it in completely and that you certify as above.
Signature Date
OR, if submitting this paper electronically as per instructions for the unit, place an ‘X’ in the box below to indicate that you have read this form and filled it in completely and that you certify as above.  Please include this page in/with your submission.   Any electronic responses to this submission will be sent to your ECU email address. Agreement                    Date
PROCEDURES AND PENALTIES ON LATE ASSIGNMENTS (University Rule 39)  A student who wishes to defer the submission of an assignment must apply to the lecturer in charge of the relevant unit or course for an extension of the time within which to submit the assignment. (39.1)  Where an extension is sought for the submission of an assignment the application must:  be in writing  –  preferably before the due date; and   set out the grounds on which deferral is sought. ( see 39.2)  Assignments submitted after the normal or extended date without approval shall incur a penalty of loss of marks. (see 39.5) ACADEMIC MISCONDUCT (University Rule 40) All forms of cheating, plagiarism or collusion are regarded seriously and could result in penalties including loss of marks, exclusion from the unit or cancellation of enrolment. – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – –
ASSIGNMENT RECEIPT       To be completed by the student if the receipt is required
UNIT

NAME OF STUDENT

STUDENT ID. NO.

NAME OF LECTURER

RECEIVED BY
Topic of assignment

DATE RECEIVED
17
CONDITIONS FOR ASSIGNMENT EXTENSION
In accordance with ECU policy, extensions are given on the following grounds and must include all appropriate supporting documentation:
 Ill health or injury for an extended period of time – medical certificate is required;  Compassionate grounds – supporting documentation includes e.g. newspaper notice plus other evidence if not the same family name, e.g. marriage certificate;  Representation in sporting activities at a national or international level;  Representation in significant cultural activities;  Employment related intrastate, interstate and overseas travel – a letter from your employer, including your supervisors’ full contact details.
The following factors will NOT be considered as grounds for extension:
 Routine demands of employment;  Stress or anxiety normally associated with examinations, required assessments or any aspect of course work;  Routine financial support needs;  Lack of knowledge of the requirements of academic work;  Difficulties with English language;  Scheduled anticipated changes of address, moving home etc;  Demands of sport, clubs, social or extra-curricular activity other than those specified above;  Recreational travel (domestic or international);  Planned events such as weddings, birthday parties etc;  Misreading the deadline.
All extension requests will require students to complete the Assignment Extension Form (downloadable from the Quantitative Assignment folder on BB), along with appropriate documentation such as a medical certificate, letter from employer, etc. Original copies of these documents will then need to be provided. Scanned or photocopied documents are NOT acceptable. All documents must be provided no longer than ONE week after the assignment deadline.

Simply Click ORDER NOW and your paper details. Our support team will review the assignment(s) and assign the right expert whose specialization is same to yours to complete it within your deadline. Our Editor(s) will then review the completed paper (to ensure that it is answered accordingly) before we email you a complete paper 

Email Us for help in writing this paper for you at: support@customwritings-us.com

RES5115: RESEARCH PREPARATION: PRINCIPLES AND APPROACHES QUANTITATIVE ASSIGNMENT(SPSS)


1
SCHOOL OF SCIENCE
_______________________________________________________________________________________________
RES5115: RESEARCH PREPARATION: PRINCIPLES AND APPROACHES
QUANTITATIVE ASSIGNMENT
DUE DATE: Friday 28th of October 2016 before midnight
For this assignment, you are expected to perform all analyses using either SPSS or Excel/Real Statistics. However prior to this, you will need to generate your own sub-sample (unique to your student ID) from a larger sample using the random number generator in Microsoft Excel. To do this, you must first activate the Analysis ToolPak in Excel by following steps below.
Step 1: Open a new Excel spreadsheet as shown below.
2
Step 2: Go to File → Options.
Step 3: Click on Add-ins and then click Go…
3
Step 4: Select Analysis ToolPak and click OK.
You can now use the Analysis ToolPak under the Data tab by clicking on Data Analysis.
Note that the above steps are for Microsoft Excel 2010 and may differ slightly if you are using the 2013 version.
4
QUESTION 1 [25 MARKS]
BACKGROUND
A study was conducted to investigate the effects of short-term treatments with growth hormone (GH) on biochemical markers of bone metabolism in men with idiopathic osteoporosis. Subjects ranged in age from 32 to 57 years. Among the data collected were serum concentrations of insulin-like growth factor binding protein-3 at 0 and 7 days after the first injection and 1, 4, 8 and 12 weeks after the last injection (i.e. post- treatment) with GH. The serum concentration data for 116 men are given in the Excel file “Serum.xlsx”.
TASK 1 – SELECTING A SUB-SAMPLE
Open the Serum.xlsx data file as shown.
Click on the “Data” tab and then run the “Data Analysis” tool pack.
5
Select Random Number Generation and click OK.
Select “Uniform” in the drop-down menu next to “Distribution”. Then fill out the other boxes as shown. In the box corresponding to “Random Seed”, make sure you type the last two digits of your student ID here. This will ensure the set of random numbers is unique to you (unless someone else shares the same two numbers).
You should now be able to see 116 random numbers in Column H. Take note that your numbers will be different to those shown here.
Last two digits only
6
Highlight all the data in from Columns A to H using the mouse/keyboard. Then click on   and select Custom Sort…
Now click on  next to ColumnSort by and select (Column H). Make sure that under Order, it is set to Smallest to Largest. Then click OK.
The data are now sorted according to Column H. Again, note that what is shown here is very likely to be different to what you will have. Now, select the first 60 observations (i.e. Rows 2 to 61) from Columns A to G and copy this sub-sample across to SPSS or another Excel spreasheet (e.g. Sheet 2). These observations form the dataset that you will be working with for this question.
7
TASK 2 – ANALYSING THE DATA
(i) Use SPSS or Excel/Real Statistics and generate the necessary summary statistics and figures to describe the serum concentrations 0 and 7 days after the first GH injection. Proper interpretation of these output in the context of the problem is expected. (ii) Use the appropriate test in SPSS or Excel/Real Statistics and determine whether the GH treatment had any significant impact on serum concentration 7 days after the 1st injection. You will need to comment on the nature and extent of these differences (if any). Hypothesis statements are not necessary.  (iii) Confidence intervals should be presented and interpreted whenever possible. (iv) All relevant assumptions associated with your chosen test must be verified. (v) Repeat steps (i) – (iv), but in this instance compare the serum concentrations 1, 4, 8 and 12 weeks after the last GH injection. If the initial analysis suggests a difference, you will then need to perform a post hoc test to determine where the difference(s) lie. Hypothesis statements are not necessary. (vi) Based on the outcomes of the two analyses, comment on the short-term and post-treatment effect of GH treatment on serum concentrations.

8
QUESTION 2 [25 MARKS]
BACKGROUND
Mental illness within the Australian population is becoming more apparent. A nationwide survey in 2007 on mental health and wellbeing conducted by the Australian Bureau of Statistics (ABS) found that an estimated 3.2 million Australian (20% of the population between the ages of 16 and 85) had a mental disorder in the twelve months prior to the survey, and the estimated economic impact of mental health problems is up to $20 billion each year.
The mental health of fly-in/fly-out (FIFO) workers in resources sector became a subject of interest in recent years. Although the financial reward is great, reports of FIFO practices negatively impacting the workers and their Australian families are not uncommon.
To determine the extent of the mental health problem in the resources industry, a health and well-being survey was carried at a particular mining company. In the survey are questions relating to the worker’s demographics, behaviour in the past twelve months, work/lifestyle/family-related issues and others.
Also included in the survey are the Kessler’s mental health questions which will allow one to clinically determine the severity of mental health problems for an individual. The Kessler questions were developed by Professor Kessler and Mroczek (1992) to assess the severity (“1 = None of the time”, “2 = A little of the time”, “3 = Some of the time”, “4 = Most of the time” or “5 = All of the time”) of anxiety and depression related symptoms experienced in the past month. Collectively, they are the Kessler 10 or K10 questions. A K10 score is calculated by summing the scores of the 10 questions. The minimum possible score is 10 (low distress) and the maximum being 50 (very high distress).
Suppose that you are interested in examining whether there is an association between worker’s behaviours and their distress levels in the past 12 months.  The items of interest are presented in Table 1 and the relevant survey data are given in the Excel file “Mental Health.xlsx”. Note that a blank entry represents a missing response.
Table 1   Items of interest in the Health and Well-Being questionnaire Over the past 12 month (1 = Daily; 2 = Weekly; 3 = Monthly; 4 = Once or Twice; 5 = Almost never) (1) How often have you felt worn out? (2) How often have you been emotionally drained? (3) How often have you been irritable? (4) How often have you had aches and pains? (5) How often have you argued with a work colleague? (6) How often have you felt anxious? (7) How often have you had no energy or enthusiasm? (8) How often have you had 6 or more standard drink in one session? (9) How often have you used prescription or non-prescription drugs? (10) How often have you missed a meal? (11) How often have you argued with friends or family? (12) How often have you had trouble sleeping? (13) How often have you exercised?
9
TASK 1 – SELECTING A SUB-SAMPLE
Open the Mental Health.xlsx data file as shown.
Click on the “Data” tab and then run the Analysis ToolPak by clicking on Data Analysis.
Select Random Number Generation and click OK.
10
Select “Uniform” in the drop-down menu next to “Distribution”. Then fill out the other boxes as shown. In the box corresponding to “Random Seed”, make sure you type the last two digits of your student ID here. This will ensure the set of random numbers is unique to you (unless someone else shares the same two numbers).
You should now be able to see 1269 random numbers in Column O. Take note that your numbers will be different to those shown here.
Last two digits only
11
Highlight all the data in from Columns A to O using the mouse/keyboard. Then click on   and select Custom Sort…
Now click on  next to Column → Sort by and select (Column O). Then click OK.
The data are now sorted according to Column O. Again, note that what is shown here (next page) is very likely to be different to what you will have.
12
Now, select the first 150 observations (i.e. Rows 1 to 151) from Columns A to N. Copy this sub-sample across to another spreadsheet (e.g. Sheet 2) in Excel. In the example below, Sheet 2 was renamed to Sub- sample.

13
TASK 2 – SELECTING ITEMS FROM THE QUESTIONNAIRE TO ANALYSE
Now that you have your sub-sample, here you will determine which THREE (3) of the 13 items to analyse. Again, go to the “Data” tab and then run the “Data Analysis” tool pack. Select “Random Number Generation” and click “OK”.
Now generate 13 random uniform numbers and store them in Column P of the sub-sample spreadsheet. In the “Random Seed” box, type the last two digits of your student ID again.
You should now be able to see 13 random numbers in Column P. Take note that your numbers will again be different to those shown here. Now, type the numbers 1 – 13 (to represent the items) in Column Q and right next to the random numbers that you have just generated.
Last two digits only
14
Now, highlight all the numbers in Columns P and Q using the mouse/keyboard. Then sort the numbers by
clicking  and then   Sort Smallest to Largest.
The first three numbers in Column Q refer to the items in Table 1 that you will need to analyse. In this example, these are items (1), (3) and (13). Copy the relevant data for the 3 items and the corresponding K10 scores across to SPSS or another Excel spreadsheet (e.g. Sheet 3). These observations form the dataset that you will be working with for this question.
TASK 3 – ANALYSING THE DATA
(i) Use SPSS or Excel/Real Statistics and generate all necessary summary statistics and figures to describe the relationship between the workers’ mental health (according to the K10 scores) and each of your selected items (make sure you consider each item separately from the others). Proper interpretation of these output in the context of the problem is expected. (ii) Use the appropriate test in SPSS or Excel/Real Statistics and determine whether there is a difference in distress levels across the response categories for these each of these items. If so, perform a post-hoc test to determine where the difference(s) lie. You will need to comment on the nature and extent of these differences (if any). Hypothesis statements are not necessary.  (iii) Confidence intervals should be presented and interpreted whenever possible. (iv) All relevant assumptions associated with your chosen test must be verified.  (v) Briefly comment on the practical implications of your findings and how they may be useful.
15
SUBMISSION GUIDELINES:
This assignment must be completed using either SPSS or Excel/Real Statistics. It is expected that your assignment solutions are presented in the context of the problem. Simply stating the numbers from the output table will not suffice. Examples of this are given on Blackboard in the Quantitative weekly folders corresponding to the workshop weeks. The write-up of your analyses must be presented in Microsoft Word in Times New Roman format with 11-pt font with single spacing and in grammatically correct English. The page margins must be 2 cm for all sides. Failure to do so will result in deduction of marks. Furthermore, no handwritten assignments will be accepted. Copy only the relevant outputs, tables and/or figures from SPSS or Excel across to the Word document. All tables and figures must be labelled appropriately. The write-up for each question (not each part) must not exceed THREE (3) pages (including all tables and figures). Any lines exceeding the three-page limit will not be considered or read. Your assignment submission will also need to include the dataset that is unique to your student ID, along with a cover page (see page 16).
You are reminded of the declaration
“I certify that the attached assignment is my own work and that any material drawn from other sources has been acknowledged”.
that you sign when you complete the coversheet. The assignment solutions must be your own work.
You must submit your completed assignment via Turnitin by Friday 28th of October 2016 before midnight. In the interests of fairness, submission extensions will be given only in exceptional circumstances, and then only in accordance with University rules (see page 17).
Note: If your datasets do not match the ones generated with your student ID (last two digits only), you will be awarded a mark of zero regardless of whether the analysis is correct.
SUBMISSION CHECKLIST:
Your submission will need to be a single document containing the following:
o Cover sheet (1 page) o Your solutions to Questions 1 and 2 (maximum of 3 pages per question). o Your datasets (No restriction)
MARKING GUIDELINES:
(1) Adherence to submission guidelines above (10%) (2) Correct selection and implementation of tests and with correct findings (30%) (3) Proper presentation and interpretation of results in the context of the study and objective(s) (30%) (4) Use of statistics to support and re-inforce findings and arguments (15%) (5) Spelling, grammar and overall narrative (15%)
The above marking guidelines are estimates and variations may occur. If a test is incorrectly chosen, then only a maximum of 10 marks is attainable.
16
ASSIGNMENT COVER SHEET Electronic or manual submission
Form:  SSC-115-06-08
UNIT CODE:        TITLE:
NAME OF STUDENT (PRINT CLEARLY)                          FAMILY NAME                                  FIRST NAME
STUDENT ID. NO.
NAME OF LECTURER (PRINT CLEARLY)

DUE DATE
Topic of assignment

Group or tutorial (if applicable)

Course

Campus

I certify that the attached assignment is my own work and that any material drawn from other sources has been acknowledged.   Copyright in assignments remains my property.  I grant permission to the University to make copies of assignments for assessment, review and/or record keeping purposes.  I note that the University reserves the right to check my assignment for plagiarism.  Should the reproduction of all or part of an assignment be required by the University for any purpose other than those mentioned above, appropriate authorisation will be sought from me on the relevant form.
OFFICE USE ONLY
If handing in an assignment in a paper or other physical form, sign here to indicate that you have read this form, filled it in completely and that you certify as above.
Signature Date
OR, if submitting this paper electronically as per instructions for the unit, place an ‘X’ in the box below to indicate that you have read this form and filled it in completely and that you certify as above.  Please include this page in/with your submission.   Any electronic responses to this submission will be sent to your ECU email address. Agreement                    Date
PROCEDURES AND PENALTIES ON LATE ASSIGNMENTS (University Rule 39)  A student who wishes to defer the submission of an assignment must apply to the lecturer in charge of the relevant unit or course for an extension of the time within which to submit the assignment. (39.1)  Where an extension is sought for the submission of an assignment the application must:  be in writing  –  preferably before the due date; and   set out the grounds on which deferral is sought. ( see 39.2)  Assignments submitted after the normal or extended date without approval shall incur a penalty of loss of marks. (see 39.5) ACADEMIC MISCONDUCT (University Rule 40) All forms of cheating, plagiarism or collusion are regarded seriously and could result in penalties including loss of marks, exclusion from the unit or cancellation of enrolment. – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – –
ASSIGNMENT RECEIPT       To be completed by the student if the receipt is required
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NAME OF STUDENT

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CONDITIONS FOR ASSIGNMENT EXTENSION
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All extension requests will require students to complete the Assignment Extension Form (downloadable from the Quantitative Assignment folder on BB), along with appropriate documentation such as a medical certificate, letter from employer, etc. Original copies of these documents will then need to be provided. Scanned or photocopied documents are NOT acceptable. All documents must be provided no longer than ONE week after the assignment deadline.

Need Help-CEE 213—Deformable Solids


Need Help-CEE 213—Deformable Solids

The Mechanics Project Arizona State University CP 4—Plane Beam 1

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Computing Project 4 Plane Beam

The computing project Plane Beam concerns the solution of the problem of a prismatic beam subjected to a variable transverse load. The goal is to write a MATLAB program that will allow the solution for a variety of load distributions and for all possible boundary conditions (i.e., fixed, simple, slide, or free at either end). The theory needed to execute this project is contained in the set of notes (entitled CP 4— Plane Beam) that accompany this problem statement. Those notes provide an introduction to each aspect of the computation required to solve the problem. This project is very similar to CP 1—Axial Bar, and it would be a very good idea to use the code for that project as the starting point for this one. The general steps are as follows: 1. Develop a routine based upon Simpson’s Rule to numerically integrate the applied loading terms that produce the quantities I0, I1, I2, and I3 that are mentioned in the CP4 notes. To get this part working dust off the Simpson code segment from CP1 and add the new pieces (i.e., I2, and I3). Verify the numerical integration by comparing with integrals you can do by hand. 2. Develop a routine to set up and solve the system of equations that allow for the determination of the state variables (w, , M, and V) at both ends of the bar. This step will require some logic to make it work easily for different boundary condition cases (it should cover all of them). Debug your code with a problem that you can solve by hand (e.g., beam fixed at one end with a uniformly distributed load). 3. Develop a routine to integrate the governing equations from the left end to the right end using generalized trapezoidal rule to do the integration numerically. Store the results at each step along the axis and provide a plot of the applied load q, the transverse displacement w, the rotation of the cross section , the bending moment M, and the net shear force V as functions of x. A good way to verify this step is to just plot the functions and verify that they go to the right values at x=L. 4. Generate a library of load forms, including some simple ones (e.g., uniform load) to verify the code. You should be able to use your MATLAB function LoadFunctionCP.m for this task with little or no change. 5. Use the library to explore aspects of the problem. For example: CEE 213—Deformable Solids The Mechanics Project Arizona State University CP 4—Plane Beam 2 a. Explore how the distribution of load affects the displacement, rotation, moment and shear along the length of the beam. b. Investigate a distributed load over a small segment of the bar (with no load over the rest of it) to see how a distributed load in the limit does the same thing as a concentrated load. Make sure to increase the amplitude of the distributed load as you decrease the length of its action so that the total force is equal to a fixed value (i.e., the value of the concentrated force you are comparing it to). What happens to the shear diagram? What does the moment diagram look like? c. Explore how the state variables work to meet the boundary conditions (e.g., the slope of the rotation function should go to zero at a free end). d. Explore any other feature of the problem that you find interesting. Write a report documenting your work and the results (in accord with the specification given in the document Guidelines for Doing Computing Projects). Post it to the Critviz website prior to the deadline. Please consult the document Evaluation of Computing Projects to see how your project will be evaluated to make sure that you can get full marks. Note that there is no peer review process for reports in this course.

 

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Randy Smith, Inventory Control Manager


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Final Project (20% of final mark)

Randy Smith, Inventory Control Manager. Randy Smith was very proud of his new position as inventory control manager for the Johnson Trinket Company. His primary responsibility had been fairly clearly defined:

Maintain an inventory level in the warehouse that ensures that production will not run

out of stock, yet also maintain an inventory level that will minimize inventory holding and

control costs. Since Randy had recently had a course in materials management, he knew an

approach that should help him. He decided to make a list of inventory items in one small

section of the warehouse to see if he could develop a good plan for inventory control. If it

worked in the one small section, he could expand it to the rest of the more than 30,000

part numbers in the warehouse.

The following is the data Randy compiled:

Part Number

Part unit value in $ Quantity currently

in inventory

Average annual

usage

1234 $2.50 300 3000
1235 $0.20 550 900
1236 $15.00 400 1000
1237 $0.75 50 7900
1238 $0.76 180 2800
1239 $4.40 20 5000
1240 $1.80 200 1800
1241 $0.05 10 1200
1242 $17.20 950 2000
1243 $9.00 160 2500
1244 $3.20 430 7000
1245 $0.30 500 10000
1246 $1.10 25 7500
1247 $8.10 60 2100
1248 $5.00 390 4000
1249 $0.90 830 6500
1250 $6.00 700 3100
1251 $2.20 80 6000
1252 $1.20 480 4500
1253 $5.90 230 900

When Randy scanned the list, he noticed several things that disturbed him, and he asked

one of the experienced inventory clerks. The following list summarizes the part number

issues that concerned Randy, and the explanation from the clerk:

Part number 1236, a very expensive part with almost half-a-year’s worth of inventory.

This part is used for a product that has very cyclical demand, and the busy time of the

year is about to start.

Part number 1241 is very inexpensive, yet the inventory is very small. This part has a

supplier with an erratic delivery history, and the part also has a very long lead time. A

lot of 150 has been on order for some time, and is now several days past due.

Part number 1242, like 1236, is expensive with almost half a year worth of inventory—

this part is shipped to a location on the other side of the country and is being accumu-

lated into a large lot to save shipping costs.

Part number 1246 is not too expensive, with a low inventory. This part is produced in-

house, and has a quality tolerance that the older equipment, which was used to pro-

duce it, had a difficult time meeting. The last batch was rejected by the quality

department.

Part number 1253 is moderately expensive with a large inventory compared to usage.

This part was subject to a recent quality audit, and almost 150 of the items were

rejected as a result of that audit.

Once Randy understood some of the issues, suddenly he did not feel quite as confi-

dent that he had the best approach in mind to control the inventory to meet the

expectations of his boss.

Assignment

(1). Use Microsoft EXCEL and the information above to evaluate the current situation.

(2). Given your evaluation, try to develop an integrated inventory control policy that

Randy should consider.

(3). Is there other information that you would like to see that might help you to make a

more effective policy?

(4). If so, what would that information be and how would you use it to help you?

Instructions:

1) The research findings should be handed in before April 8th as a Word document using a font of 12 and spacing =1.5.

2) Personalize the style of your text. Imagine you are generating a report to inform the audience it is addressed to or to answer the requirement of your manager.

3) Be clear and organized in your presentation of the text: use bullet points, tables and brief texts to convey your message.

4) The assignment will count for 20% of your final mark.

7) Plagiarism could lead to obtaining a mark of zero on the project.

8) Both of electronic and printed versions should be sent to me before the deadline.

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