Comm 215 Case Section E FALL 2015: Description of Case and Questions to be Addressed. A financial institution is collecting data to better understand the profiles of its current employees. Such information would be essential for 1) an evaluation of the current hiring practice; 2) understanding the mechanism of determining salary; 3) looking into possible discrimination against certain gender and or age groups in order to reflect socially acceptable values with respect to equity in the work place. Also, the company is particularly aware that while market factor efficiencies may support wage structures that some employees may be inclined to exploit the laws to their advantage. Thus in order to protect itself from hazard related to future lawsuits, the company wishes to gather data that would provide information that would enable it to test and analyze the fairness of its practices or otherwise. In particular, management wants to determine and report on whether any differences observed in salary between gender categories and or age groupings are due to factors that might not be socially acceptable; as opposed to relative comparative factor efficiency in the market. Management, over the history of the organization had collected and recorded data on the following variables below. NSAL: Salary at the time of study SSAL: Salary at the time of hiring SEX: 0 = male; 1 = female SENIOR: Number of months with the company AGE (in months) at time of hire EXP: Months of work experience EDU: 1 = high school graduate; 2 = some college; 3 = college graduate Data on the above variables are obtained for 111 employees (See data on the "data" worksheet on Moodle: W2015 Case Data). A preliminary study based on the data by students on a stage from the Mathematics Department at the local University was quite ambiguous as to whether the company was in compliance with the laws and social norms of the society. Management wanted to have a second opinion and contracted you (Your group) to conduct a review of the study. PART I First, your group is asked to do a literature review of the literature available on similar studies and determine whether the variables used by the Mathematics stagiaires are appropriate and broad enough in coverage to effectively determine whether its employment practices, its organizational structure, market strategies and administration practices make it a leading company in fair employment practices. The company is also aware that there are many issues related to data collection (See Text, Groebner, pages 12-13) that can lead to biases and errors in the accuracy of the data with significant negative impact on the conclusion reached. In particular, the company wishes to you/group to determine whether the methods used to collect the data meet the requirements for external and internal validity. While the company realizes that an extensive analysis of how to measure the magnitude of bias and how to reduce bias and other data collection problems may be beyond the scope of your research group, it would like you to point out any flaws in the data collected by the Mathematic Stagiaires, and pose questions about the potential for bias and determine what steps, based on the topics and concepts taught in this course, can be taken to reduce biased effects. To assist your review read Section 1.2 of your text (Groebner pages 7-9) selectively: indicate what data collection methods have been used by the research team of stagiaires and comment on the appropriateness. What kind of study is this, an experimental design study or observational? Part II: Data Summary and Analysis 1) Use appropriate descriptive statistics to summarize the following data and comment on their underlying distributions. For qualitative data, your answer should at least include supporting relative frequencies tables, and or graphics. Your presentations should entail test for outliers and a written analysis of the changes in the distribution when adjustments are made for outliers: comment on the location, shape and skewness of the distribution before and after making adjustment for outliers. Show the results and state the implications of any changes for the outcome of your analysis 2) Using the most appropriate statistical methods, compare the distributions for the salaries of men and women at the time of the study, before and after any adjustments are made in the data. 3) Does your analysis support the belief that there is a relationship between the age at the time of hiring and the salary at the time of hiring, age and sex discrimination. Support you answer with appropriate analytical, graphic tools and/or descriptive measures. What are the implications of your conclusions for the findings of the study? 4) The Mathematics Stagiaires recognize the disparities in the salaries between males and females working for the company. But in their report they supported a management report which stated that female salaries were catching up to males and that at the time of the study no more than 50 percent of the female employees had incomes below the average NSAL for the company as a whole. Test the validity of the claim and comment on the statement that female salaries are catching up to males. What are the research implications for your conclusions? Part III: Final Report As stated in the project description, management is concern about the legal and social implications of the existence issues related to gender equity or economic exploitation based on age differences. Does your group's analysis and revised review support the conclusions of the math stagiaires that management should be concerned about being at risk of legal action and social sanctions. Comment and please support your conclusions by the appropriate statistical analysis and scatter plots. What recommendations would you make in public relations strategy, human resource management and data gathering, presentation and analysis to address some of the concerns expressed by management. SEE FILE \"CASE STUDY INSTRUCTIONS,FALL 2015 MOODLE A financial institution is collecting data to better understand the profiles of its current employees. Such information would be essential for 1) an evaluation of the current hiring practice; 2)understanding the mechanism of determining salary; 3)looking into possible discrimination against certain gender or age groups in order to avoid future lawsuits. The measurements involve the variables below. It would be useful to use descriptive statistics, both graphical and numerical, to describe these variables, and to help meeting the objectives of the current study as indicated above. NSAL: Salary at the time of study SSAL: Salary at the time of hiring SEX: 0 = male; 1 = female SENIOR: Number of months with the company AGE (in months) at time of hire EXP: Months of work experience EDU: 1 = high school graduate; 2 = some college; 3 = college graduate Data on the above variables are obtained for 111 employees (data on the "data" worksheet) Employee 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 NSAL 9000 12480 11760 13920 13020 9240 8340 8160 13320 14460 7860 12600 13560 15120 11760 8880 12120 14220 9060 14280 9360 13260 10980 10920 7860 10560 13416 10440 13020 11100 11100 9240 9060 11940 8700 11340 11760 13560 9180 13800 11040 8160 8280 11400 11520 9300 11400 8520 8640 9360 10200 11940 10860 11280 10680 11160 11160 14640 15420 9840 12660 11220 9660 9960 9780 9180 11520 7260 11700 12240 12120 12660 8940 SSAL 5100 6300 5700 6600 5400 4380 4500 4500 6000 5700 4380 7500 6300 6600 6300 6600 6600 5340 4500 6900 4500 6600 5880 4500 4500 4200 6300 4620 7200 6600 7800 4500 4500 6300 4500 6000 6600 6600 4200 4860 6000 4500 4500 4500 7200 5700 4200 4500 4800 5400 4800 6300 6600 5100 4620 4980 5400 7200 6600 5400 6300 6000 4620 4500 4980 5580 5580 4380 4620 4980 6300 5700 4500 SEX 1 0 1 0 1 1 1 1 1 0 1 1 0 0 0 1 1 1 1 1 1 0 0 1 1 1 0 1 1 0 1 1 1 0 1 0 1 0 1 1 0 1 1 1 0 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 0 1 SENIOR 65 67 63 94 90 81 69 69 90 96 81 90 94 90 70 71 98 88 81 85 80 83 70 81 80 93 66 74 78 79 82 81 69 82 65 72 86 64 93 77 87 66 69 80 65 95 92 77 69 64 81 70 67 81 81 69 73 71 90 78 92 71 93 81 69 73 72 80 93 69 68 65 80 AGE 298 345 301 432 345 294 285 281 534 356 303 740 365 394 322 299 527 332 298 384 300 397 334 297 294 310 329 288 342 364 705 289 281 361 276 338 340 383 311 292 378 283 284 301 492 352 306 296 279 546 295 349 369 326 295 290 328 361 365 326 390 322 337 301 289 307 328 300 322 284 344 307 292 EXP 24 46 9 93 22 0 0 0 3 83 11 204.5 78 60 15 7 143 31.5 0 19 18 69 40.5 5 5 0 47 2 6 55 265 13 2 85 0 48 24 106 9.5 4 75 0 1.5 3.5 210 46 6 0 0 197.5 11 48 78 18.5 18 0 32 12 0 47 64 14.5 0 0 12 21.5 18 0 11 4.5 55 9.5 5 EDU 1 2 1 2 2 1 1 1 1 1 1 1 2 2 2 1 3 2 1 3 1 2 1 1 1 1 1 1 2 2 2 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 1 1 1 3 3 1 2 2 2 1 1 2 1 1 2 1 2 2 1 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 10200 9600 10080 9360 9120 13020 9900 9300 13140 13800 10980 12108 9720 12540 14820 8340 8040 9780 13200 15960 32000 9120 8820 10620 16800 17364 10800 11040 13560 11664 10560 11760 9540 15660 9000 10140 8580 9660 4800 4500 5580 4500 4500 5700 4380 6300 7800 6900 6300 6300 4380 4440 7200 5400 4500 4800 7200 6300 6300 4500 4380 6000 6000 6300 6000 4560 6600 6000 5400 6120 5100 6300 6600 6300 5100 5400 1 1 1 1 1 0 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 1 1 0 0 0 0 1 0 1 1 1 1 0 0 0 1 1 76 83 64 80 69 96 79 82 64 80 91 66 80 67 75 67 92 79 75 91 82 68 81 81 96 76 94 93 79 76 94 72 69 63 70 70 63 69 315 310 349 292 284 364 296 350 322 362 381 344 301 325 345 618 315 292 351 364 354 281 299 368 386 331 401 307 368 327 354 309 293 327 534 341 680 309 7 16 56.5 0 0 43 4.5 4 20 2.5 48 80 7.5 47 5 181 24 7.5 26 59 34 1.5 8.5 52 68 12 119.5 5.5 94 22 3 30 19.5 85 216 55.5 139 7 2 1 2 1 1 2 1 3 3 3 2 1 1 2 2 1 1 1 3 2 2 1 1 2 2 2 1 1 1 1 2 1 1 1 1 2 1 2 Employee 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 NSAL 9000 12480 11760 13920 13020 9240 8340 8160 13320 14460 7860 12600 13560 15120 11760 8880 12120 14220 9060 14280 9360 13260 10980 10920 7860 10560 13416 10440 13020 11100 11100 9240 9060 11940 8700 11340 11760 13560 9180 13800 11040 8160 8280 11400 11520 9300 11400 8520 8640 9360 10200 11940 10860 11280 10680 11160 11160 14640 15420 9840 12660 11220 9660 9960 9780 9180 11520 7260 11700 12240 12120 12660 8940 10200 9600 10080 9360 9120 13020 SSAL 5100 6300 5700 6600 5400 4380 4500 4500 6000 5700 4380 7500 6300 6600 6300 6600 6600 5340 4500 6900 4500 6600 5880 4500 4500 4200 6300 4620 7200 6600 7800 4500 4500 6300 4500 6000 6600 6600 4200 4860 6000 4500 4500 4500 7200 5700 4200 4500 4800 5400 4800 6300 6600 5100 4620 4980 5400 7200 6600 5400 6300 6000 4620 4500 4980 5580 5580 4380 4620 4980 6300 5700 4500 4800 4500 5580 4500 4500 5700 SEX 1 0 1 0 1 1 1 1 1 0 1 1 0 0 0 1 1 1 1 1 1 0 0 1 1 1 0 1 1 0 1 1 1 0 1 0 1 0 1 1 0 1 1 1 0 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 0 SENIOR 65 67 63 94 90 81 69 69 90 96 81 90 94 90 70 71 98 88 81 85 80 83 70 81 80 93 66 74 78 79 82 81 69 82 65 72 86 64 93 77 87 66 69 80 65 95 92 77 69 64 81 70 67 81 81 69 73 71 90 78 92 71 93 81 69 73 72 80 93 69 68 65 80 76 83 64 80 69 96 AGE 298 345 301 432 345 294 285 281 534 356 303 740 365 394 322 299 527 332 298 384 300 397 334 297 294 310 329 288 342 364 705 289 281 361 276 338 340 383 311 292 378 283 284 301 492 352 306 296 279 546 295 349 369 326 295 290 328 361 365 326 390 322 337 301 289 307 328 300 322 284 344 307 292 315 310 349 292 284 364 EXP 24 46 9 93 22 0 0 0 3 83 11 204.5 78 60 15 7 143 31.5 0 19 18 69 40.5 5 5 0 47 2 6 55 265 13 2 85 0 48 24 106 9.5 4 75 0 1.5 3.5 210 46 6 0 0 197.5 11 48 78 18.5 18 0 32 12 0 47 64 14.5 0 0 12 21.5 18 0 11 4.5 55 9.5 5 7 16 56.5 0 0 43 EDU 1 2 1 2 2 1 1 1 1 1 1 1 2 2 2 1 3 2 1 3 1 2 1 1 1 1 1 1 2 2 2 1 1 1 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 1 1 1 3 3 1 2 2 2 1 1 2 1 1 2 1 2 2 1 2 1 2 1 1 2 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 9900 9300 13140 13800 10980 12108 9720 12540 14820 8340 8040 9780 13200 15960 32000 9120 8820 10620 16800 17364 10800 11040 13560 11664 10560 11760 9540 15660 9000 10140 8580 9660 4380 6300 7800 6900 6300 6300 4380 4440 7200 5400 4500 4800 7200 6300 6300 4500 4380 6000 6000 6300 6000 4560 6600 6000 5400 6120 5100 6300 6600 6300 5100 5400 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 1 1 0 0 0 0 1 0 1 1 1 1 0 0 0 1 1 79 82 64 80 91 66 80 67 75 67 92 79 75 91 82 68 81 81 96 76 94 93 79 76 94 72 69 63 70 70 63 69 296 350 322 362 381 344 301 325 345 618 315 292 351 364 354 281 299 368 386 331 401 307 368 327 354 309 293 327 534 341 680 309 4.5 4 20 2.5 48 80 7.5 47 5 181 24 7.5 26 59 34 1.5 8.5 52 68 12 119.5 5.5 94 22 3 30 19.5 85 216 55.5 139 7 1 3 3 3 2 1 1 2 2 1 1 1 3 2 2 1 1 2 2 2 1 1 1 1 2 1 1 1 1 2 1 2