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# Descriptive Stats Analysis

Submitted By mkeller26050
Words 1631
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Barbara Tucker who oversees Ballard Integrated Managed Services, Inc for the Douglas Medical Center location decided to conduct a survey in regards to the research question asking, why the turnover rate jumped from averaging 55-60% to 64%. A survey was given to each employee of BIMS that support the Douglas Medical Center and of the 5,300 employees only 78 participated in the survey leaving a very low response rate or 17.3%. This immediately tells the observers that the morale of the employees is not very high and one can only hope that the information provided by the 78 employees helps to point to why they are feeling this way. The following information will show how the responses were computed using descriptive statistics in the form of tables, charts, measures of central tendency, and variability.
Charts
In regards to the charts created from the responses to the survey, some inferences can be made and some conclusions can be drawn. One such inference could be that since more than half of the employees participating in the survey replied that they do not enjoy working for BIMS, this could also be a realistic ratio for the whole staff as many did not feel that it was important enough to respond to the survey. Another inference could be that the managers and supervisors are not reacting to the scheduling needs of their employees from the beginning of their employment. This could be concluded because 51 of 78 responses were negative in regards to, if the employees felt their request for their desired shift was fulfilled. A staggering revelation from the charts and what may be the most compelling as to why the companies has such a high turnover rate is in reference to the question regarding if the employees feel they are paid fairly for their work. There were 50 responses that were of the two most negative response options in the survey, and not one employee chose the highest option of very positive. From the information provided in the charts an observer can conclude that due to the lack of manger and supervisor support of the needs of the employees, and lack of fair pay, the employees simply do not enjoy working for BIMS and will leave as soon as they get an opportunity to, through new employment.
Measures of Central Tendency
After careful scrutiny, our team has revised our initial assessment of the nature of the BIMS survey data and has come to the conclusion that the survey is, in fact, qualitative in nature. Questions 1-10 are ordinal, because the categories assigned can be ordered or ranked; questions A, C, and D, are demographic in nature, and, thus, nominal, because the categories do not have an intrinsic order (in addition, questions C and D are dichotomous). We have also calculated the measures of central tendency (mean, median, and mode) for the survey data and are able to reach some interesting conclusions. First of all, we stand by our original assessment that the data retrieved BIMS was not enough to reach any definitive conclusions about what the majority population of the BIMS employees feel, but, in the absence of returned surveys, we ‘crunched’ the numbers, so to speak, and came up with the following:
• The value that was most used by respondents was number two, which has been identified as “Somewhat Negative,” with value one, “Very Negative,” second. To give these numbers some sort of contextual reference, more responses were number two, the frequency of which is higher than possible responses four and five, the more positive responses, combined. See histogram A. Histogram A
• We have calculated that the central tendency (mean, median and mode) for each of the ordinal questions (Question 1-10) and see that, again, the tendency is for the numbers to fall under the value of three—which has been identified as “Neither Positive nor Negative.” The best measure of central tendency for ordinal data, the median, show that for Questions 1,3,5,and 7, the median value is three; for Questions 2,and 4, the median is two point five; for Questions 6,8,9, and 10, the median is two. Again, we must note that numbers do not lie; the central tendency is for the respondents to be either neutral or less than positive about their employment at BIMS. Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10
MEAN 2.807692 2.730769 2.807692 2.769231 2.884615 2.064103 2.871795 2.653846 2.217949 2.653846
MEDIAN 3 2.5 3 2.5 3 2 3 2 2 2
MODE 2 2 2 2 2 2 2 2 2 2

Tables
In using the Ballard Integrated Managed services inc.,Members of the BIMS were asked to answers each question from 1-10, with rating from very negative to very positive with one be the same as rating of one to five. Colum’s one on the data represents the 78 members and column 2 represent the question 1-10. We also recorded zero when some members did not answers the questions and also recorded 6. The first table is a table of numerical questions in the BIMS data. Team B, focus on three top most important questions such as do you enjoy working for BIMS, if you are paid fairly and do you fear your job.
When asked for Question 1, “How well do you enjoy working for BIMS?” On the negative side 1 employees did not answers, About 15 of the employees rate very negative , About 21% rate negative , 12% rate neutral , which that shows more employees are very unsatisfied about working for BIMS. Only 2 employees rate positive to that question.
When asked for question 6, you are paid fairly for the work you do? , about 3 employees did not answer, 20 employee rate very negative, 30 employee rate negative , 19 employees was neutral about it , 6 employees rate positive and nobody rate positive. Again only 6 employees rate positive and very positive means nobody believe they get paid fairly. It is important to know how satisfied the employees feel about their pay.
When as for question 10, Do you fear that you will lose your job?, 2 did not rate , 17 rate very negative, 22 rate negative, 12 rate neutral, 15 rate positive and 9 Rate very positive. As for that question, not a lot fear for their job.
When ask questions from A, in which division do you work? The answers were between (1) Food, (2) Housekeeping (3) Maintenance, we had to count as code, 1 or 2 or 3. About 32 employees work for Food services, 36 employees work for housekeeping and 9 employees work for Maintenance. For question B, asked how long you have working for BIMS? For example B, there were different complete answers to pick from months and years because it ranges from 1 month to 328 months. For the fourth table C, what is your gender? Was from either female or Male and the table shows there was 27 female and 38 male. The last table which is D, Are you a manager or supervisor, the answers was either yes for manager and no for supervisor. There were a total of 12 managers and 63 supervisors. BIMS EMPLOYEE SURVEY
NA Very Negative Negative Neutral Positive Very positive
(0) (1) (2) (3) (4) (5) (6)
Question 1-10
Q1 1 15 21 12 12 1 1
Q2 2 14 22 13 14 11 1
Q3 1 15 21 15 13 13 0
Q4 3 15 21 12 12 12 2
Q5 1 13 22 14 14 14 0
Q6 3 20 30 19 6 0 0
Q7 0 15 21 15 13 14 0
Q8 4 15 22 12 13 10 1
Q9 0 17 32 24 5 0 0
Q10 2 17 22 12 15 9 1

QUESTIONS 1-10
N0. Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10
0 1 2 1 3 1 3 0 4 0 2
1 15 14 15 15 13 20 15 15 17 17
2 21` 22 21 21 22 30 21 22 32 22
3 12 13 15 12 14 19 15 12 24 12
4 12 14 13 12 14 6 13 13 5 15
5 1 11 13 12 14 0 14 10 0 9
6 1 1 0 2 0 0 0 1 0 1

Division FOOD SERVICES Housekeeping Maintenance 32 36 9

Answers for C Gender Female 1 Male
2
27 38

Answers for D Job Title Manager / Supervisors = Yes Non- Manager / Supervisors = No
Yes 12
NO 63

Variability
If and even there is a huge adequate sample size, there will still need to be more information to arrive at a conclusion. A measure of variability is what is needed. Typically, if you hand out 449 surveys employees you expect to get all 449 surveys back. Will everyone return the surveys back who work in housekeeping, food or maintenance? Male or Female? Understanding how the data is spread will show us how efficient the survey is. If each person in housekeeping returns their survey, then it will be obvious the survey has had a positive outcome, however, when workers contain a broad variability with the percentage of the returns (most likely they will), the image will then become a bit fuzzy. A proper conclusion can only be made if the mean and variability has been calculated. In his case, if the survey returns are large and there is little variability, then we would receive a p-value (probability-value) that is small. According to Merriam-Webster probability-value is the probability of an event or outcome in a statistical experiment (Merriam-Webster, 2014).

References

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