Assessment Details and Submission Guidelines Unit Code CHM103 Year/Term XXXXXXXXXX Unit Title Business Statistics Assessment Type Group Assignment & Presentation Due Date Friday in Week 11 by 11.55 PM...

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Assessment Details and Submission Guidelines Unit Code CHM103 Year/Term 2021 -2 Unit Title Business Statistics Assessment Type Group Assignment & Presentation Due Date Friday in Week 11 by 11.55 PM Assessment Title 2 – 4 members each group Unit Learning Outcomes covered in this assessment a. Explain and present business data for informed interpretation, including comparison b. Demonstrate techniques for the collection and presentation of data c. Compare probability approaches for the measurement of business uncertainty d. Draw conclusions about populations based on sample information e. Originate reliable forecasts based on particular variables of interest f. Analyse data and solve business problems by applying statistical techniques including regression analysis g. Explain and interpret Index numbers Weight 40 Marks Total Marks 100 Marks (this will be scaled down to 40%) Word limit NA Submission Guidelines • All work must be submitted on Moodle by the due date along with a completed Assignment Cover Page. • The assignment must be in MS Word format, 1.5 spacing, 11-pt Calibri (Body) font and 2 cm margins on all four sides of your page with appropriate section headings. • Reference sources must be cited in the text of the report, and listed appropriately at the end in a reference list using APA Assignment Description • Students are required to produce the group assignment using data provided. • As this is a group assignment, students will be required to contribute overall and prepare sections individually which can be then amalgamated. • Students are all required to present their findings in week 11 in the group presentation. • You need to use Business Statistics tools, techniques and terminology that you have learnt to analyse the data and to write up the assignment. Page 2 of 5 Data set [Job Satisfaction] is from a global corporation. The variables include: 1. ID 2. “Gender” –1= male or 2=female 3. Marital status (Married, single) 4. Age 5. Years of experience 6. City that they come from (areas coded from 1 to 5) 7. Region they come from (east, west, south, north) 8. Departments (1=IT, 2=Marketing, 3= Sales, 4= HR, 5= Finance 6=Innovation) 9. Salary (in thousands) 10. Job satisfaction score before training (1= extremely dissatisfied; 5=extremely satisfied) 11. Job satisfaction score after training (1= extremely dissatisfied; 5=extremely satisfied) 12. Life happiness score (1= extremely unhappy; 10=extremely happy) 13. Promoted (yes, No) Page 3 of 5 Assignment instructions: Three hundred employees of the company globally have been surveyed regards their job satisfaction in the company. The main challenge in the business is deterioration in job satisfaction among the employees. For this reason, the company HR has decided to conduct a survey and identify satisfaction level of the employees. They measure employee’s satisfaction in two periods of before and after training. Using analytics and application of the material we have covered in class, address the following questions/sections (as guide only). You can come up with any rational question to answer, as long as you can provide your reasoning and assumptions behind that. As guide - answer these main research questions within the following sections: 1. Variance/Standard deviation: Compare variance and standard deviation between ‘job satisfaction score before training’ and ‘job satisfaction score after training’. Is there a meaningful difference between them? How far below or above the average each of them are? 2. Covariance: Find out covariance between ‘job satisfaction score before training’ and ‘life happiness score’. Do they change in the same direction? 3. Independent sample T-test: Is there statistically significant difference in ‘life happiness score’ between two groups of male and female staff? 4. Z-score: How many standard deviations above or under average ‘Salary’ and ‘Age’ are? Are there any outliers? 5. Chi-square test: Is there any relationship between ‘marital status’ and ‘promotion? 6. Correlation analysis: Is there statistically significant relationship between ‘years of experience’ and ‘salary’? 7. Regression analysis: Does ‘Salary’ determine ‘life happiness score’? Note: This is only a guide and there are no right and wrong answers when it comes to statistical analysis. You must know and demonstrate your knowledge of this. Page 4 of 5 Assignment structure: • Introduction – Describe the analysis to be conducted. • Problem definition and business intelligence required • Defining problem of the company and what they are trying to achieve by the analysis. This includes your possible assumptions and the logic behind them • Variance/ Standard deviation • Is there a meaningful difference between two variables? • Covariance • How two variables vary? In the same direction or otherwise? • Independent sample T-test: • statistically significant difference between two groups. • Z-score: • Where are the variables in terms of their standard location? (choose any numerical variable) • Chi-square test: • Any relationship between two categorical variables? • Correlation analysis: • Significant relationship between two numerical variables? • Regression analysis: • Does a variable influence other variable? • Results and Recommendations • Based on the analyses what conclusions/suggestions you can have for decision makers? Assignment formatting: Font size 12 Times New roman, double spacing. Note. The word count does not include headings, tables, graphs/figures or the reference list. Page 5 of 5 Marking Guide (40 Marks) Criteria Possible Marks% Marks Allocated  Introduction • Describe the analysis to be conducted. 5  Problem definition and business intelligence required • Defining problem of the company and what they are trying to achieve by the analysis (or what are you going to achieve by the analysis) • Methods used for the analysis and the reason for choosing them 10  Variance/ Standard deviation • Is there a meaningful difference between two variables? 5  Covariance • How two variables vary? In the same direction or otherwise? 5  Independent sample T-test: • Statistically significant difference between two groups. 10  Z-score: • Where are the variables in terms of their standard location? 5  Chi-square test: • Any relationship between two categorical variables? 20  Correlation analysis: • Significant relationship between two numerical variables? 15  Regression analysis: • Does a variable influence other variable? 15  Results and Recommendations • Based on the analyses what conclusions/suggestions you can have for decision makers? 10 100% Total paper result: 30% Presentation: 10% Overall Comments: 40% Sheet1 ID numberGenderMarital StatusAgeZ-ageZ-age_probYears of experienceCity AreaRegionDepartmentsSalary(000)Z-salaryZ-salary probJob Satisfaction Score before training(1-5)Job Satisfaction Score after training(1-5)Life Happiness Score (1-10)PromotedPromoted-c 2952Married20-2.14954464630.015795625523East2581.59281437130.9443990799228Yes1 2961Married20-2.14954464630.015795625511East144-0.5029940120.3074842411229Yes1 2972Married20-2.14954464630.015795625523North137-1.55089820360.0604630405326Yes1 2981Married20-2.14954464630.015795625532East1520.69461077840.7563503722133No0 2991Married20-2.14954464630.015795625525East247-0.05389221560.4785105194355No0 3001Married20-2.14954464630.015795625512South4500.39520958080.6536558887354Yes1 2892Single22-1.95305976090.025406257222South137-1.55089820360.0604630405139No0 2902Married22-1.95305976090.025406257231East6520.69461077840.7563503722335No0 2912Married22-1.95305976090.025406257223West147-0.05389221560.4785105194131Yes1 2922Married22-1.95305976090.025406257211East2500.39520958080.6536558887253Yes1 2931Married22-1.95305976090.025406257254West146-0.20359281440.4193358544132Yes1 2942Married22-1.95305976090.025406257231West547-0.05389221560.4785105194135No0 2862Married24-1.75657487550.039495149333West2561.29341317370.9020659019258Yes1 2872Single24-1.75657487550.039495149321West5561.29341317370.9020659019348Yes1 2882Married24-1.75657487550.039495149312South145-0.35329341320.3619342415436No0 2711Married28-1.36360510470.086345942384North2520.69461077840.7563503722132Yes1 2722Married28-1.36360510470.086345942352East547-0.05389221560.4785105194154No0 2732Single28-1.36360510470.086345942344South1500.39520958080.6536558887235Yes1 2742Married28-1.36360510470.086345942355West146-0.20359281440.4193358544256Yes1 2751Married28-1.36360510470.086345942383West247-0.05389221560.4785105194152Yes1 2762Married28-1.36360510470.086345942355West1581.59281437130.9443990799241No0 2772Married28-1.36360510470.086345942364South244-0.5029940120.3074842411335No0 2782Married28-1.36360510470.086345942393South1510.54491017960.7070923527231Yes1 2791Married28-1.36360510470.086345942384West1520.69461077840.75635037221510Yes1 2802Married28-1.36360510470.086345942352South1480.09580838320.5381636204149Yes1 2812Married28-1.36360510470.086345942351West6571.44311377250.9255057879335Yes1 2822Single28-1.36360510470.086345942382South1490.2455089820.5969688229151Yes1 2832Married28-1.36360510470.086345942353South245-0.35329341320.3619342415243No0 2842Married28-1.36360510470.086345942362South1510.54491017960.7070923527152No0 2851Married28-1.36360510470.086345942381West5490.2455089820.5969688229115Yes1 2471Married30-1.16712021930.1215809118125West129-2.7485029940.0029934044249Yes1 2482Married30-1.16712021930.1215809118121West1601.89221556890.9707688676436Yes1 2492Married30-1.16712021930.1215809118101West1490.2455089820.5969688229133Yes1 2502Married30-1.16712021930.121580911893North2490.2455089820.5969688229335No0 2511Married30-1.16712021930.121580911854South4480.09580838320.5381636204334Yes1 2522Married30-1.16712021930.121580911881North2510.54491017960.7070923527251Yes1 2532Single30-1.16712021930.121580911851East438-1.40119760480.0805774952238Yes1 2542Single30-1.16712021930.121580911842East2510.54491017960.7070923527339No0 2552Married30-1.16712021930.121580911855West3520.69461077840.7563503722226No0 2562Married30-1.16712021930.121580911881West2490.2455089820.5969688229123Yes1 2571Married30-1.16712021930.121580911853East2540.9940119760.8398914815125Yes1 2582Married30-1.16712021930.121580911863North345-0.35329341320.3619342415334Yes1 2592Married30-1.16712021930.121580911895South1510.54491017960.7070923527151Yes1 2602Single30-1.16712021930.121580911882East2520.69461077840.7563503722152Yes1 2612Married30-1.16712021930.121580911854East1480.09580838320.5381636204245No0 2622Single30-1.16712021930.121580911854West4571.44311377250.9255057879239No0 2632Married30-1.16712021930.121580911884South2490.2455089820.5969688229236Yes1 2642Single30-1.16712021930.121580911855South145-0.35329341320.3619342415135Yes1 2651Married30-1.16712021930.121580911862West2510.54491017960.7070923527326Yes1 2662Married30-1.16712021930.121580911881West2490.2455089820.5969688229231No0 2672Married30-1.16712021930.121580911854West2561.29341317370.9020659019133No0 2681Married30-1.16712021930.121580911883East234-20.0227501319458No0 2692Married30-1.16712021930.121580911895North145-0.35329341320.3619342415249Yes1 2701Married30-1.16712021930.121580911855East337-1.55089820360.06046304051310Yes1 2232Married32-0.97063533390.1658649521154East233-2.14970059880.0157894525236No0 2242Married32-0.97063533390.1658649521162West146-0.20359281440.4193358544135No0 2252Married32-0.97063533390.1658649521141West2510.54491017960.7070923527326Yes1 2262Married32-0.97063533390.1658649521122West2551.14371257490.8736285717231Yes1 2272Married32-0.97063533390.1658649521133South244-0.5029940120.3074842411133Yes1 2281Single32-0.97063533390.1658649521152West246-0.20359281440.4193358544258No0 2292Married32-0.97063533390.1658649521121West1490.2455089820.5969688229249Yes1 2302Married32-0.97063533390.1658649521153North3480.09580838320.53816362041310Yes1 2312Married32-0.97063533390.1658649521141North2591.74251497010.9592908129132Yes1 2322Married32-0.97063533390.1658649521152East546-0.20359281440.4193358544154No0 2332Married32-0.97063533390.1658649521132West1591.74251497010.9592908129235No0 2342Married32-0.97063533390.1658649521121North146-0.20359281440.4193358544456Yes1 2352Married32-0.97063533390.1658649521123East235-1.85029940120.0321352045152Yes1 2361Single32-0.97063533390.1658649521151West144-0.5029940120.3074842411241Yes1 2372Single32-0.97063533390.1658649521164West243-0.65269461080.2569765888335Yes1 2382Married32-0.97063533390.1658649521141West1540.9940119760.8398914815231Yes1 2391Married32-0.97063533390.1658649521123South141-0.95209580840.17052419731510No0 2402Married32-0.97063533390.1658649521131South1510.54491017960.7070923527149No0 2411Married32-0