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- 1. Assignment Grading Rubric Course: MT460 Unit: 9 Points: 45 _________________________________________________ Unit 9: Leadership, Policy, and Culture Case Study Analysis Paper: Prepare a case study analysis of Case 9, Defender Direct, Inc.: A Business of Growing Leaders found in the Cases section of your digital book. Closely follow the Case Study Analysis Template by clicking on the hyperlink. Please utilize this template format for this Assignment. Use titles and subtitles per the format for readability purposes. Focus upon the idea of the company’s strategy-culture relationship and which of the four strategy- culture situations should it implement in order to help move Defender Direct forward. Please include the SWOT Analysis with the four quadrants in the appendix of your paper (after the References page). You can find the SWOT analysis template in Doc Sharing. Assignment Checklist: • Conduct a SWOT Analysis on the case study company’s current strategy-culture relationship. • Create a case study analysis focusing on which of the four strategy-culture situations it should implement in order to help move the company forward.
- 2. Format The case analysis should be 2--3 written pages in length (not including the formal title page and References page), double-spaced. Ensure that you use correct spelling, grammar, punctuation, mechanics, and usage. The citing of sources (text and list references) should use the current APA format and style. http://extmedia.kaplan.edu/business/MT460/MT460_1403C/MT 460_Case_Study_Analysis_Format_and_Style_Template.docx For assistance with APA format and citation style visit the Kaplan Writing Center. Directions for Submitting Your Project • Before you submit your project, you should save your work on your computer in a location and with a name that you will remember. • Make sure your Assignment is in the correct file format (Microsoft Word .doc or .docx). • Submit y your completed document to the Unit 9 Assignment Dropbox. Need help with the Dropbox? Click on the Dropbox Guide link under Academic Tools tab.
- 3. MT460 Unit 9 Assignment Grading Rubric Maximum Percent Criteria Maximum Points 50% Content 22 Answer provides correct and complete information demonstrating critical thinking: • Conduct a SWOT Analysis on the case study company’s current strategy-culture relationship.
- 4. • Create a case study analysis focusing on which of the four strategy-culture situations it should implement in order to help move the company forward. 30% Analysis and Critical Thinking • Synopsis of situation • Key issues • Problem definition • Alternative solutions • Select a solution • Implementation • Recommendations 14 15% Writing Style, Grammar 6 5% APA Format and Citation Style 3 100% Total 45 Assignment Grading RubricCourse: MT460 Unit: 9 Points: 45_________________________________________________ Introduction
- 5. We want to check how the age and different levels of music affects the musical tastes or liking to the music. For this we have two categories of age that is less than 40 years and more than 40 years and three categories of different music that are Fugazi, Abba and Barf Grooks. Basically we want to check whether these variables affect the liking of music and if yes then how they are going to affect the liking of music. Three Hypotheses can be tested simultaneously with two way analysis of variance. Statistical Assumption of the test: 1. The data should be collected by random sampling. 2. The sample should be independent from each other. 3. The data should be continuous or we can say that the data should be either interval level or ratio level for t test. Using the data set you have selected, select independent and dependent variables. Here we have Independent Variables: Age, Music Dependent Variable: Liking Develop the null and the alternative hypotheses. First hypothesis: Null Hypothesis (Ho1): All the age groups have equal music liking on the average or we can say that there is no significant difference in liking music due to age factor. Alternative Hypothesis (Ha1): All the age groups are not equal music liking on the average or we can say that there is a significant difference in liking music due to age factor. Mathematically; Null Hypothesis (Ho1): µ1 = µ2 Alternative Hypothesis (Ha1): µ1 ≠ µ2 Where µ1 = Mean of the liking music for first category of age of less than 40 years. µ2 = Mean of the liking music for second category of age of
- 6. more than 40 years. Second hypothesis: Null Hypothesis (Ho2): All the music groups have equal music liking on the average or we can say that there is no significant difference in liking music due to music factor. Alternative Hypothesis (Ha2): All the music groups are not equal music liking on the average or we can say that there is a significant difference in liking music due to music factor. Mathematically; Null Hypothesis (Ho2): µ1 = µ2 = µ3 Alternative Hypothesis (Ha2): µi ≠ µj; for some i not equal to j Where µ1 = Mean of the liking music for first category of music that is Fugazi µ2 = Mean of the liking music for second category of music that is Abba. µ3 = Mean of the liking music for third category of music that is Barf Grooks. Third hypothesis: Null Hypothesis (Ho3): There is no significant interaction between two main factors that is age and music. Alternative Hypothesis (Ha3): There is a significant interaction between two main factors that is age and music. .Level of Significance = .05 The below syntax is used to calculate the Two Way ANOVA test for the above mentioned data. UNIANOVA liking BY music age /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /POSTHOC=music(BONFERRONI) /PLOT=PROFILE(music age) /EMMEANS=TABLES(music) /EMMEANS=TABLES(age) /EMMEANS=TABLES(music*age)
- 7. /PRINT=OPOWER ETASQ HOMOGENEITY DESCRIPTIVE /CRITERIA=ALPHA(.05) /DESIGN=music age music*age. SPSS Output is given below: Univariate Analysis of Variance Between-Subjects Factors Value Label N Music 1.00 Fugazi 30 2.00 Abba 30 3.00 Barf Grooks 30 Age Group 1.00 40+ 45
- 8. 2.00 0-40 45 Descriptive Statistics Dependent Variable:Liking Rating Music Age Group Mean Std. Deviation N Fugazi dimension2 40+ -75.8667 14.37193 15 0-40 66.2000 19.90406 15
- 10. Total 1.4000 77.40783 30 Total dimension2 40+ 19.4444 70.93164 45 0-40 19.6222 68.06257 45 Total 19.5333 69.12035 90 Levene's Test of Equality of Error Variancesa Dependent Variable:Liking Rating F df1 df2
- 11. Sig. 1.189 5 84 .322 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a. Design: Intercept + music + age + music * age Estimated Marginal Means 1. Music Dependent Variable:Liking Rating Music Mean Std. Error 95% Confidence Interval
- 12. Lower Bound Upper Bound Fugazi -4.833 3.594 -11.981 2.314 Abba 62.033 3.594 54.886 69.181 Barf Grooks 1.400 3.594 -5.747 8.547 2. Age Group Dependent Variable:Liking Rating Age Group Mean Std. Error
- 13. 95% Confidence Interval Lower Bound Upper Bound dimension1 40+ 19.444 2.935 13.609 25.280 0-40 19.622 2.935 13.786 25.458 3. Music * Age Group Dependent Variable:Liking Rating
- 14. Music Age Group Mean Std. Error 95% Confidence Interval Lower Bound Upper Bound Fugazi dimension2 40+ -75.867 5.083 -85.975 -65.759 0-40 66.200 5.083 56.092 76.308 Abba dimension2
- 15. 40+ 59.933 5.083 49.825 70.041 0-40 64.133 5.083 54.025 74.241 Barf Grooks dimension2 40+ 74.267 5.083 64.159 84.375 0-40 -71.467 5.083 -81.575 -61.359 Post Hoc Tests Music Multiple Comparisons
- 16. Liking Rating Bonferroni (I) Music (J) Music Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound Fugazi Abba -66.8667* 5.08292 .000 -79.2836 -54.4498 Barf Grooks -6.2333
- 17. 5.08292 .671 -18.6502 6.1836 Abba Fugazi 66.8667* 5.08292 .000 54.4498 79.2836 Barf Grooks 60.6333* 5.08292 .000 48.2164 73.0502 Barf Grooks Fugazi 6.2333 5.08292 .671 -6.1836 18.6502 Abba -60.6333* 5.08292 .000 -73.0502 -48.2164 Based on observed means. The error term is Mean Square(Error) = 387.541.
- 18. *. The mean difference is significant at the .05 level. Profile Plots From the above analysis and results we can conclude that the assumptions of the models are satisfied because the Levene's Test of Equality of Error Variances has P-value 0.322 which is more than the level of significance, so we can say that the population variances are equal. Also the data is normally distributed and sample is randomly drawn. So we can conclude that 1) All the age groups have equal music liking on the average or we can say that there is no significant difference in liking music due to age factor because P-value corresponding to this variable is 0.966 which is very high. 2) All the music groups are not equal music liking on the average or we can say that there is a significant difference in liking music due to music factor because the P-value corresponding to this is 0.000. 3) There is a significant interaction between two main factors
- 19. that is age and music because the P-value corresponding to this is 0.000. Partial η2 (Partial eta-squared): Partial eta-squared describes the "proportion of total variation attributable to the factor, partialling out (excluding) other factors from the total nonerror variation" Here the value of R-Square is .923 which means that 92.3% of the variation is explained by these factors. So it means we have obtained the power more than 80% for this analysis. Also, the post hoc test shows that Fugazi and Abba has a significant difference on the liking of music and also the Abba and Barf Brooks has a significant difference on the liking of music at 5% level of significance. The profile plots show that Abba has a high liking of music as compare to other two. Also, the most important results are that the Abba is liked by all age groups does not matter whether they are less than or equal to 40 years or whether they are more than 40 years. Reference: Bailey, R. A. (2008). The design of Comparative Experiments. Cambridge University Press. ISBN 978-0-521-68357-9. Pre- publication chapters are available on-line. Belle, Gerald van (2008). Statistical rules of thumb (2nd ed.).
- 20. Hoboken, N.J: Wiley. ISBN 978-0-470-14448-0. Cochran, William G.; Cox, Gertrude M. (1992). Experimental designs (2nd ed.). New York: Wiley. ISBN 978-0-471-54567-5. Cohen, Jacob (1988). Statistical power analysis for the behavior sciences (2nd ed.). Routledge ISBN 978-0-8058-0283-2 Cohen, Jacob (1992). "Statistics a power primer". Psychology Bulletin 112 (1): 155–159. doi:10.1037/0033-2909.112.1.155. PMID 19565683. Cox, David R. (1958). Planning of experiments. Reprinted as ISBN 978-0-471-57429-3 Cox, D. R. (2006). Principles of statistical inference. Cambridge New York: Cambridge University Press. ISBN 978-0-521- 68567-2. Freedman, David A.(2005). Statistical Models: Theory and Practice, Cambridge University Press. ISBN 978-0-521-67105-7 SA Glantz and BK Slinker, Primer of Applied Regression and Analysis of Variance, McGraw-Hill, second edition, 2000. SE Maxwell and HD Delaney. Designing Experiments and Analyzing Data, second edition. Laurence Erlbaum, 2004. Running head: <INSERT NAME OF CASE> 1 <INSERT NAME OF CASE> 2 Unit <Number> <insert name of case> Case Study Analysis Kaplan University School of Business MT460 Management Policy and Strategy Author: <insert your name>
- 21. Professor: Dr. <professor’s name> Date: <month> <date>, <year> Name of Case Study Company Name: <Insert company name here from the case.> Topic of the Week: <Insert the topic of the week to focus upon in the analysis.> Synopsis of the Situation <Start here and indent 5-7 spaces; then one inch margins all around; enter content; should have two to three paragraphs>. Alternative Solution s <Create at least three alternative solutions that are original and not from the case study itself.> 1. <Begin here with at least two sentences.> 2. <Begin here with at least two sentences.> 3. <Begin here with at least two sentences.> Selected