Part 2 of Research Project. You will use the public   corporation that you selected and posted in the Week 1 discussion 2 and the   Part 1 of the Research Project that you submitted in Week 2.  Your Abstract will have the sentence you included in your Week 2 submission of Part 1 and add sentences briefly summarizing the content that you are added this week.

Page one of the body of the paper will have an introductory paragraph that briefly summarizes the content of your report in   the exact order that it appears in your report. The introductory paragraph is   like a table of contents in sentences. You will keep the one or two   paragraphs without any quoted material that you had in your week 2 submission. Edit using any feedback and guidance received via your grade   book.

You will now add the common-sized Income Statements   (i.e., started in the Week 4 class discussion) and Balance Sheets (i.e.,   started in the Week 5 class discussion). Discuss the trends that you see as   compared to Industry Averages (i.e., started in Week 1 class discussion) for   your corporation.

Have headings and sub-headings in your report.

Add a Summary with Conclusions paragraph at the end of your report. The last page is your reference list. Every item in the   reference list must be actually cited in your writing. Every item cited in your writing must appear as a reference list item. 

• SynnexCorporationPartI.docx
• IncomeStatement.docx
• BalanceSheet.xlsx

 

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•  

MUST BE 400 word count FOR EACH ASSIGNMENT (TWO ASSIGNMENTS TOTAL)

ANY OUTSIDE SOURCES MUST BE IN APA FORM THROUGHOUT THE PAPER AND WITH AN REFERENCE PAGE.  ALL SOURCES MUST BE FROM SCHOLARLY ARTICLES…

ASSIGNMENT 1

Read the article “Overcome the Five Main Reasons People Resist Change.”

WEBSITE LINK TO GO TO READ IT : http://www.forbes.com/sites/lisaquast/2012/11/26/overcome-the-5-main-reasons-people-resist-change/#3093da083393

After reading the article,

ANSWER THE FOLLOWING NUMBERS BELOW THOROUGHLY

1. identify three reasons for resistance to change.

2. Which of these reasons is likely to be the most critical in your organization?

3.As a leader, how would you overcome this type of resistance? 

ASSIGNMENT 2

Organizations face substantial change on a regular basis. Technology, out sourcing, and restructuring through downsizing or rightsizing are some of the key reasons for change.  

Answer the following numbers below thoroughly 

1.Assume you are receiving news that you are the point person within your department/division for one of the change factors listed above. What are the barriers you must address that could challenge the change initiative?  

2. What steps will you use to facilitate a successful change process?

 

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The purpose of this assignment is to allow the students to become familiar with and practice the measurement of Net Present Value (NPV), payback, and Weighted Average Cost of Capital (WACC) using Microsoft Excel. 

Assignment Steps 

Calculate the following problems using Microsoft® Excel®. Note – the system will not hold table formatting for presentation purposes here in the instructions; please review the template provided below in the resources section for numbers in proper alignment.

• Calculate the NPV for each project and determine which project should be accepted.

Project A Project B Project C Project D

Initial Outlay (105,000.00) (82,000.00) (110,000.00) (75,000.00)

Inflow year 1 53,000.00 51,000.00 25,000.00 45,000.00

Inflow year 2 50,000.00 47,000.00 55,000.00 50,000.00

Inflow year 3 48,000.00 41,000.00 15,000.00 30,000.00

Inflow year 4 30,000.00 52,000.00 21,000.00 62,000.00

Inflow year 5  35,000.00 40,000.00 35,000.00 68,000.00

Rate 7% 10% 13% 18%

• Your company is considering three independent projects. Given the following cash flow information, calculate the payback period for each. If your company requires a three-year payback before an investment can be accepted, which project(s) would be accepted?

Project D Project E Project F

Cost 205,000.00 179,000.00 109,000.00

Inflow year 1 53,000.00 51,000.00 25,000.00

Inflow year 2 50,000.00 87,000.00 55,000.00

Inflow year 3 48,000.00 41,000.00 21,000.00

Inflow year 4 30,000.00 52,000.00 8,000.00

Inflow year 5 24,000.00 40,000.00 35,000.00

• Using market value and book value (separately), find the adjusted WACC, using 16% tax rate.

Component Balance Sheet Value Market Value Cost of Capital

Debt 5,000,000.00 6,850,000.00 8%

Preferred Stock 4,000,000.00 2,200,00.00 11%

Common Stock 2,000,000.00 5,600,000.00 13%

Include the functional formulas utilized in Microsoft® Excel® for your answers presented (in other words – do not simply type answers in the spaces required).

• FIN419RubricWk4.doc
• FIN419r6wk4CapitalBudgetingDecisionModelsTemplate.xlsx

 

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CHAPTER 15  PROBLEM 1

Use SPSS to analyze the data of Chapter 15, Problem 20, part b, p. 392 of the textbook.  For convenience, the problem is repeated here.

A sleep researcher conducts an experiment to determine whether sleep loss affects the ability to maintain sustained attention.  Fifteen individuals are randomly divided into the following three groups of five subjects each: group 1, which gets the normal amount of sleep (7-8 hours); group 2, which is sleep-deprived for 24 hours; and group 3, which is sleep-deprived for 48 hours.  All three groups are tested on the same auditory vigilance task.  Subjects are presented with half-second tones spaced at irregular intervals over a 1-hour duration.  Occasionally, one of the tones is slightly shorter than the rest.  The subject’s task is to detect the shorter tones.  The following percentages of correct detections were observed:

Normal

Sleep

Sleep-Deprived

for 24 Hours

Sleep-Deprived

for 48 Hours

85

83

76

64

75

60

58

76

52

63

60

48

38

47

50

What do you conclude, using α = 0.05.

If you choose to type the data into the Data Editor, name the variables, “Group” and “Pct_Corr.”  The saved data file for this problem is “Ch15prob1.”

SOLUTION

Step 1:  Enter and Name the Data.  As usual, you have three choices for entering the data: 1) by typing the scores directly into the Data Editor; 2) by downloading from the web the saved data file for this example, and 3) by opening the saved data file (for this example) that resides on your computer. 

Entering the scores by typing them directly into the Data Editor.  If you choose to type in the data, remember to name the grouping variable Group and the other variable Pct_Corr.  If you have any questions, please follow the instructions in Illustrative Example 1 for Chapter 15, substituting the variables and scores for this problem.

Entering the scores by downloading from the web, the saved data file for this example.  To enter the scores using this option, click here, and then click Open from the drop-down menu.  

Entering the scores by opening the saved data file (for this example) that resides on your computer.   If you choose to open the saved data file, the name of the file is Ch15prob1.  To enter the data and name the variables for this problem, please follow the instructions in Illustrative Example 1 for Chapter 15.

When the data are entered and named correctly, the Data Editor, Data View should look like Figure 15.1.1.

Figure 15.1.1.  Data Editor with Group and Pct_Corr scores entered.

Step 2:  Conclusion Regarding the Overall Effect of the Independent Variable, using α = 0.05.  The appropriate test to evaluate the overall effect of the independent variable is the One-Way Analysis of Variance.  To have SPSS do the analysis using this test,  

Click Analyze.

Select Compare Means.

Click One-Way ANOVA….

Click the ► button for the Factor:box.

Click Pct_Corr in the large box on the left.

Click the ► button for the Dependent List: box.

Click the Options button.

Click Descriptive.

Click Continue

Click OK.

This produces a drop-down menu.

This also produces a drop-down menu.

This produces the One-Way ANOVA dialog box with Group highlighted. 

This moves Group into the Factor: box.

This highlights Pct_Corr.

This moves Pct_Corr into the Dependent List:  box.  

This produces the One-Way ANOVA: Optionsdialog box.  

This puts a P in the Descriptive box, telling SPSS to compute some descriptive statistics and include them in the output.

This returns you to the One-Way ANOVA dialog box.

SPSS analyzes the Stress data and outputs the results to the Viewer.  The output is shown below in Figure 15.1.2.

Figure 15.1.2.  Results of One-Way ANOVA analysis.

The SPSS viewer shows two tables, the Descriptives table and the ANOVA table.  The ANOVA table is the table we use to conclude about the overall effect of the independent variable.  This table shows that Fobt = 14.062 and the obtained probability (Sig.) is .001.  Since .001 < 0.05, your conclusion is to reject H0.  Sleep deprivation appears to affect sustained attention.  Sure beats doing this by hand!!

 

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For this problem, we will use the experiment presented in Chapter 15, Problem 25, p. 394 of the textbook.  For convenience, the experiment is repeated here.

A university researcher knowledgeable in Chinese medicine conducted a study to determine whether acupuncture can help reduce cocaine addiction.  In this experiment, 18 cocaine addicts were randomly assigned to one of three groups of 6 addicts per group.  One group received 10 weeks of acupuncture treatment in which the acupuncture needles were inserted into points on the outer ear where stimulation is believed to be effective.  Another group, a placebo group, had acupuncture needles inserted into points on the ear where stimulation is known not to be effective.  The third group received no acupuncture treatment; instead, addicts in this group received relaxation therapy.  All groups also received counseling over the 10-week treatment period.  The dependent variable was craving for cocaine as measured by the number of cocaine urges experienced by each addict in the last week of treatment.  The following are the results.

Acupuncture +

Counseling

Placebo +

Counseling

Relaxation +

Counseling

4

7

6

5

2

3

8

12

11

8

10

7

12

7

9

6

11

6

Use SPSS to do a one-way independent groups ANOVA on the data, with a = 0.05 to determine if at least one of the groups differs significantly from at least one of the other groups.  Do a planned comparison between the Acupuncture + Counseling group and the Placebo + Counseling group, using α = 0.052 tail.  If the one-way ANOVA yields significant results, do the Tukey HSD post hoc test to see which groups differ from each other, again using α = 0.052 tail.

If you choose to enter the data by typing it into the Data Editor, name the variables, “Group” and “Urges.”  The saved data file for this problem is “Ch15prob2.”

See Solution Below.

SOLUTION

Step 1:  Enter and Name the Data.  As usual, you have three choices for entering the data: 1) by typing the scores directly into the Data Editor; 2) by downloading from the web the saved data file for this example, and 3) by opening the saved data file (for this example) that resides on your computer. 

Entering the scores by typing them directly into the Data Editor.  If you choose to type in the data, remember to name the grouping variable Group and the other variable Urges.  If you have any questions, please follow the instructions in Illustrative Example 1 for Chapter 15, substituting the variables and scores for this problem.

Entering the scores by downloading from the web, the saved data file for this example.  To enter the scores using this option, click here, and then click Open from the drop-down menu.  

Entering the scores by opening the saved data file (for this example) that resides on your computer.   If you choose to open the saved data file, the name of the file is Ch15prob2.  To enter the data and name the variables for this problem, please follow the instructions in Illustrative Example 1 for Chapter 15.

When the data are entered and named correctly, the Data Editor, Data View should look like Figure 15.2.1.

Figure 15.2.1.  Data Editor with Group and Urges scores entered.

Step 2:  Conclusion Regarding the Overall Effect of the Independent Variable, using α = 0.05 Plus Planned and Post Hoc Comparisons.  The appropriate test to evaluate the overall effect of the independent variable is the One-Way Analysis of Variance.  To have SPSS do the analysis using this test,  

Click Analyze.

Select Compare Means.

Click One-Way ANOVA….

Click the ► button for the Factor:box.

Click Urges in the large box on the left.

Click the ► button for the Dependent List: box.

Click the Options button.

Click Descriptive.

Click Continue.

Click Contrasts….

Type 1 in the Coefficients: box.

Click Add.

Type -1 in the Coefficients: box.

Click Add.

Type 0 in the Coefficients: box.

Click Add.

Click Continue.

Click the Post Hoc… button at the bottom-middle of the dialog box.

Click Tukey. 

Click Continue.

Click OK.

This produces a drop-down menu.

This also produces a drop-down menu.

This produces the One-Way ANOVA dialog box with Group highlighted. 

This moves Group into the Factor: box.

This highlights Urges.

This moves Urges into the Dependent List:  box.  

This produces the One-Way ANOVA: Optionsdialog box.  

This puts a P in the Descriptive box, telling SPSS to compute some descriptive statistics and include them in the output.

This returns you to the One-Way ANOVA dialog box.  You have finished telling SPSS what it needs to know to do the One-Way ANOVA.  Let’s now implement the planned comparisons analysis.  We will follow this with the Tukey post hoc analysis.

This produces the One-Way ANOVA: Contrasts dialog box.  The coefficients for doing planned comparisons are entered in this dialog box.  Since you are asked to do a planned comparison between the Acupuncture + Counseling group (Group 1, according to our assignment of grouping values in the Data Editor) and the Placebo + Counseling group (Group 2) the correct coefficients for this planned comparison are 1 -1 0.  Alternately, we could use -1 1 0. Let’s use 1 -1 0.

This moves the 1 into the large box below the Coefficients: box.

This moves the -1 into the large box below the Coefficients: box.

This moves the 0 into the large box below the Coefficients: box.  You have finished entering the planned comparison, 1 -1 0.

This returns you to the One-Way ANOVA dialog box.  You are now ready to implement doing the Tukey HSD post hoc test.

This produces the One-Way ANOVA: Post Hoc Multiple Comparisons dialog box. 

This puts a P in the Tukey box and tells SPSS to do the Tukey HSD test when you give it the OK.  

This returns you to the One-Way ANOVA dialog box.

SPSS analyzes the Stress data and outputs the results to the Viewer.  The output is shown below in Figure 15.2.2.

Figure 15.2.2.  Results of One-Way ANOVA analysis including planned and post hoc testing. 

The SPSS viewer shows six tables, the Descriptives table, the ANOVA table, the Contrasts Coefficients table, the Contrasts Tests table, the Multiple Comparisons table, and the Stress table.  The ANOVA table is the table we use to conclude about the overall effect of the independent variable.  This table shows that Fobt = 8.543 and the obtained probability is .003.  Since .003 < 0.05, your conclusion is to reject H0.  The three treatments are not equal in their effect on cocaine urges.  

The Contrasts Coefficients table and the Contrasts Tests table pertain to the planned comparisons.  There is only one planned comparison, the comparison between the Acupuncture + Counseling group and the Placebo + Counseling group (coefficients 1 -1 0).  The Contrasts Tests table gives the results of this planned comparison.  We are interested in the Assume equal variances part of the table.  For this planned comparison (contrast 1), tobt = -3.866 with an obtained probability of .0022 tailed.  Since .002 < 0.05, you reject H0.  It appears that Acupuncture + Counseling has a greater effect on reducing cocaine urges than Placebo + Counseling.  

The Multiple Comparisons table gives the results of the Tukey HSD post hoc test.  The comparison between Group 1 and Group 2 yielded an obtained probability value of .004; the comparison between Group 1 and Group 3 yielded an obtained probability value of .016; and the comparison between Group 2 and Group 3 yielded an obtained probability value of .786.  Thus, you can reject H0 using α = 0.05 for the Group 1 – Group 2 comparison, and the Group 1 – Group 3 comparison, but not for the comparison between Group 2 and Group 3.  Thus, Acupuncture + Counseling significantly reduced cocaine urges compared to both Placebo + Counseling and Relaxation Therapy + Counseling, but you can’t affirm that Relaxation Therapy + Counseling does better than Placebo + Counseling.  Again the planned comparison probability is lower than the post hoc comparison probability (.002 verses .004).

 

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