Qnt 351 Quantitative Analysis for Business - Ballard Integrated Managed Services, Inc

Ballard Integrated Managed Services, Inc

QNT/351 Quantitative Analysis For Business

October 14, 2012

Data collection is the acquiring of valuable information to decipher areas of problem and make scientific decisions based on certainty without being biased. It is extremely crucial to make sure that the data being used is valid, purposeful, and applicable to the problem being addressed or questioned. In order to administer an effective statistical analysis, an integrated means of research must be utilized. In this paper, Team B will review the problems that are confronting Ballard Integrated Managed Services, Inc. Team B will address the research questions, hypotheses, data collection methods, data integrity, and their findings. Additionally Team B will make recommendations on whether the actions of the survey administered by BIMS produces a characteristic sample of its employees for a healthy outcome to the problems they face.

Barbara Tucker of Ballard Intergraded Managed Service (BIMS) provides housekeeping, plant maintenance, cleaning, and food service management for patients and staff at Douglas Medical Center. Barbara is concerned, as staff morale has declined over the last several months. Typically, there is a high rate of turnover of 55%-60% (University of Phoenix, 2012). However, in the last four months the turnover rate has climbed to 64% (University of Phoenix, 2012). Staff sick time, lack of time management, and poor work has increased. Exit interviews are not shedding any light on the situation. Barbara has enlisted Debbie Horner from Human Resources to concentrate on employee motivation. Debbie thinks the employees are disenchanted with his or her company or work situation. Barbara wants to know why employee motivation is down and turnover rate is high. Debbie is going to ask 449 employees to express his or her view of the current hours, work conditions, training, compensation, treatment, internal communication, and job security via an anonymous survey using ordinal scale of measurement, (University of Phoenix, 2012). The ordinal scale shows series or rank order (McClave, 2011). As written below the ordinal scale of measurement on this survey uses numbers one through five with one being very negative and five expressing very positive. This will provide BIMS with a general idea of why there is high turnover and morale is down. Some demographic information will also be collected. The data will be organized by division (University of Phoenix, 2012). Debbie will use the data to compute techniques and research correlations by description and frequency (University of Phoenix, 2012).

The survey included 14 questions for the employees to grade on a scale from 1-5, 5 being positive. Debbie coded the survey as follows

No. Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 A B C D

1 3 4 1 5 1 3 3 2 3 37 2 2

2 5 5 5 5 5 3 5 5 2 5 1 12 1 2

3 1 2 1 5 5 1 1 1 1 1 2 76 1 2

4 2 5 3 3 2 4 5 1 3 4 2 3 2 1

5 4 4 5 1 4 1 3 3 2 4 2 16 1 2

6 5 2 5 4 3 3 2 1 2 1 1 52 1 2

7 1 4 5 3 2 5 4 2 1 1 8 2 2

8 1 3 2 2 5 2 4 5 3 2 2 28 2

9 3 3 1 4 4 2 2 2 2 4 3 15 2 1

10 5 1 3 2 2 2 1 4 1 1 1 83 2 2

Debbie Horner, the HR manager at this site, created her survey using a quantitative and qualitative approach to collect data. Quantitative data deals with numbers as data can be measured. For example collecting data related to height, weight, members, or age. Surveys are an ideal method used, as it requires individuals to input a response that can be calculated. This method can be distributed via email, phone, and in this case placed in the employees payroll checks.

The qualitative approach deals with descriptions and observations however, and cannot be measured. For example collecting data related to colors, smells, tastes or textures. Qualitative data is normally broken down into charts, graphs and percentages. This method is collected by, facilitating focus groups, observations, and, personal interviews for the use of research.

Within the study, several variables exist and with each variable different levels of measurement also apply. Lind, Marchal, and Wathen (2011) stated, "The level of measurement of the data dictates the calculations that can be done to summarize and present the data. It will also determine the statistical tests that should be performed" (p. 9). In the BIMS survey, levels of measurement include nominal, ratio, and interval. For example, the nominal level of measurement pertains to the variable concerning the survey participant's gender, level of employment, and job division because it categorizes with no natural order. Additionally, the ratio level of measurement features consist of the distance between two numbers, a meaningful 0 point, and measures items like money, weight, distance, time, etc., so said level of measurement applies to the variable regarding the length of time employed with BIMS (Lind, et al, 2011, p. 12). Whereas the