Questions
DEHS Data Set for Assessment Projects INTD 5064 Applied Statistics for Health Care Practitioners CI Subjects...

DEHS Data Set for Assessment Projects
INTD 5064 Applied Statistics for Health Care Practitioners
CI Subjects
Subject ID Group Gender Mode of Communication ESP-Pre TL-Pre AC-Pre EC-Pre ESP Post CLS-Post RLI-Post ELI-Post LCI-Post LSI-Post GF-Post
C01 1 1 1 1 86 89 95 3 95 96 99 90 88 101
C02 1 2 1 1 82 85 85 3 85 89 87 83 78 89
C03 1 1 1 1 85 78 80 3 90 92 88 88 84 85
C04 1 1 1 2 81 81 82 2 80 88 84 79 76 105
C05 1 2 1 1 92 95 100 4 100 100 95 98 104 82
C06 1 1 1 1 79 80 72 4 92 94 90 92 82 90
C07 1 1 1 1 78 80 74 3 84 88 79 86 80 80
C08 1 2 1 1 111 115 102 3 120 122 112 109 110 102
C09 1 1 1 2 87 89 79 4 88 92 87 87 82 82
C10 1 2 1 2 99 98 89 4 100 98 90 104 106 95
C11 1 1 1 1 67 69 68 3 79 84 82 70 78 77
C12 1 2 2 1 102 100 98 2 95 98 93 96 90 82
C13 1 1 2 1 74 74 70 2 70 72 70 71 68 74
C14 1 2 2 1 68 65 70 1 67 69 66 65 68 70
C15 1 1 2 1 95 90 101 2 90 92 88 85 95 87
C16 1 1 2 1 75 77 76 2 72 75 70 74 68 69
Non CI Subjects
Subject ID Group Gender Mode of Communication ESP-Pre TL-Pre AC-Pre EC-Pre ESP Post CLS-Post RLI-Post ELI-Post LCI-Post LSI-Post GF-Post
S01 2 2 2 1 95 89 100 2 93 89 85 100 92 82
S02 2 1 2 1 87 85 95 1 80 83 82 80 78 70
S03 2 2 2 2 76 78 80 1 78 72 70 77 80 65
S04 2 1 2 1 75 73 72 2 73 71 72 75 72 68
S05 2 1 2 1 79 78 80 1 80 70 72 85 81 63
S06 2 1 2 1 77 78 74 1 75 77 68 85 70 71
S07 2 1 2 1 78 80 72 2 72 75 70 72 69 60
S08 2 2 2 1 77 81 75 1 80 89 73 75 78 65
S09 2 1 2 1 87 88 84 1 80 84 80 75 80 68
S10 2 1 2 1 89 98 82 3 90 100 85 85 85 78
S11 2 2 2 1 90 94 92 1 85 90 82 79 87 72
S12 2 1 2 1 73 78 72 1 70 74 67 79 68 66
S13 2 2 2 1 74 74 75 1 70 72 69 67 75 67
S14 2 2 2 1 68 65 68 2 62 60 61 67 60 55
S15 2 1 2 1 75 74 72 1 71 77 67 75 71 70
S16 2 1 2 1 74 77 73 1 77 74 68 80 72 65

7. Trautwein and Ammerman are curious how the CI group compares to the norm on CLS at the end of the study.

a. What inferential test should the researchers use? Why?

b. What are the independent and dependent variables?

           

c. Using the A-B-C-D format used in class, answer Drs. Trautwein and Ammerman’s research question.

In: Statistics and Probability

11. Drs. Trautwein and Ammerman are curious if receptive language changed in the non-CI group (from...

11. Drs. Trautwein and Ammerman are curious if receptive language changed in the non-CI group (from the beginning to the end of the study).

What type of inferential test should be used to test the hypothesis? Why?

If they found significance, what would their conclusions be?

DEHS Data Set for Assessment Projects
INTD 5064 Applied Statistics for Health Care Practitioners
CI Subjects
Subject ID Group Gender Mode of Communication ESP-Pre TL-Pre AC-Pre EC-Pre ESP Post CLS-Post RLI-Post ELI-Post LCI-Post LSI-Post GF-Post
C01 1 1 1 1 86 89 95 3 95 96 99 90 88 101
C02 1 2 1 1 82 85 85 3 85 89 87 83 78 89
C03 1 1 1 1 85 78 80 3 90 92 88 88 84 85
C04 1 1 1 2 81 81 82 2 80 88 84 79 76 105
C05 1 2 1 1 92 95 100 4 100 100 95 98 104 82
C06 1 1 1 1 79 80 72 4 92 94 90 92 82 90
C07 1 1 1 1 78 80 74 3 84 88 79 86 80 80
C08 1 2 1 1 111 115 102 3 120 122 112 109 110 102
C09 1 1 1 2 87 89 79 4 88 92 87 87 82 82
C10 1 2 1 2 99 98 89 4 100 98 90 104 106 95
C11 1 1 1 1 67 69 68 3 79 84 82 70 78 77
C12 1 2 2 1 102 100 98 2 95 98 93 96 90 82
C13 1 1 2 1 74 74 70 2 70 72 70 71 68 74
C14 1 2 2 1 68 65 70 1 67 69 66 65 68 70
C15 1 1 2 1 95 90 101 2 90 92 88 85 95 87
C16 1 1 2 1 75 77 76 2 72 75 70 74 68 69
Non CI Subjects
Subject ID Group Gender Mode of Communication ESP-Pre TL-Pre AC-Pre EC-Pre ESP Post CLS-Post RLI-Post ELI-Post LCI-Post LSI-Post GF-Post
S01 2 2 2 1 95 89 100 2 93 89 85 100 92 82
S02 2 1 2 1 87 85 95 1 80 83 82 80 78 70
S03 2 2 2 2 76 78 80 1 78 72 70 77 80 65
S04 2 1 2 1 75 73 72 2 73 71 72 75 72 68
S05 2 1 2 1 79 78 80 1 80 70 72 85 81 63
S06 2 1 2 1 77 78 74 1 75 77 68 85 70 71
S07 2 1 2 1 78 80 72 2 72 75 70 72 69 60
S08 2 2 2 1 77 81 75 1 80 89 73 75 78 65
S09 2 1 2 1 87 88 84 1 80 84 80 75 80 68
S10 2 1 2 1 89 98 82 3 90 100 85 85 85 78
S11 2 2 2 1 90 94 92 1 85 90 82 79 87 72
S12 2 1 2 1 73 78 72 1 70 74 67 79 68 66
S13 2 2 2 1 74 74 75 1 70 72 69 67 75 67
S14 2 2 2 1 68 65 68 2 62 60 61 67 60 55
S15 2 1 2 1 75 74 72 1 71 77 67 75 71 70
S16 2 1 2 1 74 77 73 1 77 74 68 80 72 65

In: Statistics and Probability

4. Trautwein and Ammerman hypothesize that mode of communication is related to speech perception after the...

4. Trautwein and Ammerman hypothesize that mode of communication is related to speech perception after the study.

a. What inferential test would they use to complete the analysis? Why? b.

Complete parts B and D of the analysis, using an obtained value of 8.1. You may round speech perception scores.

DEHS Data Set for Assessment Projects
INTD 5064 Applied Statistics for Health Care Practitioners
CI Subjects
Subject ID Group Gender Mode of Communication ESP-Pre TL-Pre AC-Pre EC-Pre ESP Post CLS-Post RLI-Post ELI-Post LCI-Post LSI-Post GF-Post
C01 1 1 1 1 86 89 95 3 95 96 99 90 88 101
C02 1 2 1 1 82 85 85 3 85 89 87 83 78 89
C03 1 1 1 1 85 78 80 3 90 92 88 88 84 85
C04 1 1 1 2 81 81 82 2 80 88 84 79 76 105
C05 1 2 1 1 92 95 100 4 100 100 95 98 104 82
C06 1 1 1 1 79 80 72 4 92 94 90 92 82 90
C07 1 1 1 1 78 80 74 3 84 88 79 86 80 80
C08 1 2 1 1 111 115 102 3 120 122 112 109 110 102
C09 1 1 1 2 87 89 79 4 88 92 87 87 82 82
C10 1 2 1 2 99 98 89 4 100 98 90 104 106 95
C11 1 1 1 1 67 69 68 3 79 84 82 70 78 77
C12 1 2 2 1 102 100 98 2 95 98 93 96 90 82
C13 1 1 2 1 74 74 70 2 70 72 70 71 68 74
C14 1 2 2 1 68 65 70 1 67 69 66 65 68 70
C15 1 1 2 1 95 90 101 2 90 92 88 85 95 87
C16 1 1 2 1 75 77 76 2 72 75 70 74 68 69
Non CI Subjects
Subject ID Group Gender Mode of Communication ESP-Pre TL-Pre AC-Pre EC-Pre ESP Post CLS-Post RLI-Post ELI-Post LCI-Post LSI-Post GF-Post
S01 2 2 2 1 95 89 100 2 93 89 85 100 92 82
S02 2 1 2 1 87 85 95 1 80 83 82 80 78 70
S03 2 2 2 2 76 78 80 1 78 72 70 77 80 65
S04 2 1 2 1 75 73 72 2 73 71 72 75 72 68
S05 2 1 2 1 79 78 80 1 80 70 72 85 81 63
S06 2 1 2 1 77 78 74 1 75 77 68 85 70 71
S07 2 1 2 1 78 80 72 2 72 75 70 72 69 60
S08 2 2 2 1 77 81 75 1 80 89 73 75 78 65
S09 2 1 2 1 87 88 84 1 80 84 80 75 80 68
S10 2 1 2 1 89 98 82 3 90 100 85 85 85 78
S11 2 2 2 1 90 94 92 1 85 90 82 79 87 72
S12 2 1 2 1 73 78 72 1 70 74 67 79 68 66
S13 2 2 2 1 74 74 75 1 70 72 69 67 75 67
S14 2 2 2 1 68 65 68 2 62 60 61 67 60 55
S15 2 1 2 1 75 74 72 1 71 77 67 75 71 70
S16 2 1 2 1 74 77 73 1 77 74 68 80 72 65

In: Statistics and Probability

The assumption that a system will operate in a stable environment without risk is not realistic...

The assumption that a system will operate in a stable environment without risk is not realistic (Sales et al., 2018). Risk is widely classified into disruption and operational risks (Kleindorfer & Saad, 2005; Tang, 2006). Extreme uncertainty and the absence of synchronization between supply and demand are linked to operational risks while circumstances such as labor strikes, terrorist attacks, and natural calamities are related to disruption risks (Lockamy & McCormack, 2010). The probability of human injury or even death is high in disruptions such as multi-casualty disasters which brings about the challenge of increased pressure on healthcare. Healthcare institutions are required to become capable of understanding and adapting to environmental changes to mitigate such unexpected changes. These unexpected changes can affect the competitiveness, responsiveness and operating procedures of a firm significantly (Huang, Yen, & Liu, 2014), and for healthcare institutions, the economic well-being and reputation of the nation as well.

There is a growing need for healthcare institutions to develop responsiveness (Tolf, Nyström, Tishelman, Brommels, & Hansson, 2015; Vissers, Bertrand, & De Vries, 2001). However, the responsiveness of healthcare systems remains a complex, distinct and still not adequately investigated concept (Brinkerhoff & Bossert, 2013; Cleary, Molyneux, & Gilson, 2013; Gilson, Palmer, & Schneider, 2005; Siddiqi et al., 2009). Responsive healthcare systems anticipate and adjust to meet evolving requirements, exploiting opportunities to enhance access to effective interventions and to enhance health services (Hanefeld, Powell-Jackson, & Balabanova, 2017; Lodenstein, Dieleman, Gerretsen, & Broerse, 2013), ultimately resulting in improvements in outcomes of healthcare (Allotey, Davey, & Reidpath, 2014; Smith, Mossialos, Papanicolas, & Leatherman, 2009). A better understanding of healthcare responsiveness is particularly important for many nations with low and medium incomes such as Ghana, where economic and social development is rapidly advancing.

Nevertheless, responsiveness always implies that a flexible central system exists (More & Babu, 2008). Flexibility is required to respond quickly to the rapidly changing unique patient needs and demands (Aronsson, Abrahamsson, & Spens, 2011; Peltokorpi, Torkki, & Lillrank, 2011). Flexibility remains an expensive and challenging capability to develop and incorporate in any system completely. Identifying the right flexibility capabilities to develop can efficiently improve responsiveness to meet changing needs and demands of healthcare patients (Aronsson et al., 2011; Peltokorpi et al., 2011). Moreover, flexible scheduling and resources can help healthcare institutions respond more effectively to their patients by better matching the variable demand for care with the supply of physical resources such as beds, pharmaceutical, people and space required (Chen, Zhou, Ma, & Pham, 2011; Laker, Froehle, Lindsell, & Ward, 2014). Researchers have asserted that flexibility can be proactively employed as well to create a competitive advantage for a business (Chang, Yang, Cheng, & Sheu, 2003; Ettlie & Penner-Hahn, 2008; D. M. Upton, 2008). Profitable flexibility applications have been demonstrated in various ways: by the National Bicycle Industrial Company (Moffat, 1990), and by the General Motors ' Lordstown factory experiment (Kasarda and Rondinelli, 1998). Flexibility is clearly of the utmost significance (J. H. M. Manders, Caniëls, & Ghijsen, 2017) to the responsiveness of healthcare institutions, the economy, patient satisfaction and yet significant amount of existing literature focuses on the manufacturing sector (Chang, Chen, Lin, Tien, & Sheu, 2006; Jack & Raturi, 2002; Koste, Malhotra, & Sharma, 2004), with little or no attention to the service sector..

However, understanding the impact of specific flexibility capabilities and their application is critical to organizations as flexibility is expensive to implement; hence any investment in flexibility based on wrongly considered competences might be (Gerwin, 2008; Narasimhan, Talluri, & Das, 2004). There is also a paucity of studies concerning flexibility capabilities relating to operations of healthcare institutions. The quality of care and satisfaction with health facilities have been seen in most research as the perfect measure of assessing health systems performance. However, the WHO suggests responsiveness as a better measure of the performance of health systems (NB Valentine et al., 2003). Healthcare institutions are challenged by many sources of uncertainty in the supply chain and at an operational level. Though supply chain and operations flexibilities have the potential to promote the resilience and responsiveness of healthcare institutions, the scarcity of the literature in this respect makes this study worthwhile. As a result of limited literature at present, little knowledge exists on the extent to which supply chain and operations flexibilities individually promote responsiveness, or impact customer satisfaction, particularly within the service sector in Ghana.

Required:

  1. Propose an appropriate research title whch will adequately capture the research gaps and issues discussed.                                                                                                                                 
  2. Propose FOUR (4) research objectives which will reflect the research issues discussed.  
  3. Propose FOUR (4) research questions which will satisfy the research issues discussed.    

In: Operations Management

The assumption that a system will operate in a stable environment without risk is not realistic...

The assumption that a system will operate in a stable environment without risk is not realistic (Sales et al., 2018). Risk is widely classified into disruption and operational risks (Kleindorfer & Saad, 2005; Tang, 2006). Extreme uncertainty and the absence of synchronization between supply and demand are linked to operational risks while circumstances such as labor strikes, terrorist attacks, and natural calamities are related to disruption risks (Lockamy & McCormack, 2010). The probability of human injury or even death is high in disruptions such as multi-casualty disasters which brings about the challenge of increased pressure on healthcare. Healthcare institutions are required to become capable of understanding and adapting to environmental changes to mitigate such unexpected changes. These unexpected changes can affect the competitiveness, responsiveness and operating procedures of a firm significantly (Huang, Yen, & Liu, 2014), and for healthcare institutions, the economic well-being and reputation of the nation as well.

There is a growing need for healthcare institutions to develop responsiveness (Tolf, Nyström, Tishelman, Brommels, & Hansson, 2015; Vissers, Bertrand, & De Vries, 2001). However, the responsiveness of healthcare systems remains a complex, distinct and still not adequately investigated concept (Brinkerhoff & Bossert, 2013; Cleary, Molyneux, & Gilson, 2013; Gilson, Palmer, & Schneider, 2005; Siddiqi et al., 2009). Responsive healthcare systems anticipate and adjust to meet evolving requirements, exploiting opportunities to enhance access to effective interventions and to enhance health services (Hanefeld, Powell-Jackson, & Balabanova, 2017; Lodenstein, Dieleman, Gerretsen, & Broerse, 2013), ultimately resulting in improvements in outcomes of healthcare (Allotey, Davey, & Reidpath, 2014; Smith, Mossialos, Papanicolas, & Leatherman, 2009). A better understanding of healthcare responsiveness is particularly important for many nations with low and medium incomes such as Ghana, where economic and social development is rapidly advancing.

Nevertheless, responsiveness always implies that a flexible central system exists (More & Babu, 2008). Flexibility is required to respond quickly to the rapidly changing unique patient needs and demands (Aronsson, Abrahamsson, & Spens, 2011; Peltokorpi, Torkki, & Lillrank, 2011). Flexibility remains an expensive and challenging capability to develop and incorporate in any system completely. Identifying the right flexibility capabilities to develop can efficiently improve responsiveness to meet changing needs and demands of healthcare patients (Aronsson et al., 2011; Peltokorpi et al., 2011). Moreover, flexible scheduling and resources can help healthcare institutions respond more effectively to their patients by better matching the variable demand for care with the supply of physical resources such as beds, pharmaceutical, people and space required (Chen, Zhou, Ma, & Pham, 2011; Laker, Froehle, Lindsell, & Ward, 2014). Researchers have asserted that flexibility can be proactively employed as well to create a competitive advantage for a business (Chang, Yang, Cheng, & Sheu, 2003; Ettlie & Penner-Hahn, 2008; D. M. Upton, 2008). Profitable flexibility applications have been demonstrated in various ways: by the National Bicycle Industrial Company (Moffat, 1990), and by the General Motors ' Lordstown factory experiment (Kasarda and Rondinelli, 1998). Flexibility is clearly of the utmost significance (J. H. M. Manders, Caniëls, & Ghijsen, 2017) to the responsiveness of healthcare institutions, the economy, patient satisfaction and yet significant amount of existing literature focuses on the manufacturing sector (Chang, Chen, Lin, Tien, & Sheu, 2006; Jack & Raturi, 2002; Koste, Malhotra, & Sharma, 2004), with little or no attention to the service sector..

However, understanding the impact of specific flexibility capabilities and their application is critical to organizations as flexibility is expensive to implement; hence any investment in flexibility based on wrongly considered competences might be (Gerwin, 2008; Narasimhan, Talluri, & Das, 2004). There is also a paucity of studies concerning flexibility capabilities relating to operations of healthcare institutions. The quality of care and satisfaction with health facilities have been seen in most research as the perfect measure of assessing health systems performance. However, the WHO suggests responsiveness as a better measure of the performance of health systems (NB Valentine et al., 2003). Healthcare institutions are challenged by many sources of uncertainty in the supply chain and at an operational level. Though supply chain and operations flexibilities have the potential to promote the resilience and responsiveness of healthcare institutions, the scarcity of the literature in this respect makes this study worthwhile. As a result of limited literature at present, little knowledge exists on the extent to which supply chain and operations flexibilities individually promote responsiveness, or impact customer satisfaction, particularly within the service sector in Ghana.

Required:

  1. Propose an appropriate research title whch will adequately capture the research gaps and issues discussed.                                                                                                                                 
  2. Propose FOUR (4) research objectives which will reflect the research issues discussed.  
  3. Propose FOUR (4) research questions which will satisfy the research issues discussed.    

In: Economics

The assumption that a system will operate in a stable environment without risk is not realistic...


The assumption that a system will operate in a stable environment without risk is not realistic (Sales et al., 2018). Risk is widely classified into disruption and operational risks (Kleindorfer & Saad, 2005; Tang, 2006). Extreme uncertainty and the absence of synchronization between supply and demand are linked to operational risks while circumstances such as labor strikes, terrorist attacks, and natural calamities are related to disruption risks (Lockamy & McCormack, 2010). The probability of human injury or even death is high in disruptions such as multi-casualty disasters which brings about the challenge of increased pressure on healthcare. Healthcare institutions are required to become capable of understanding and adapting to environmental changes to mitigate such unexpected changes. These unexpected changes can affect the competitiveness, responsiveness and operating procedures of a firm significantly (Huang, Yen, & Liu, 2014), and for healthcare institutions, the economic well-being and reputation of the nation as well.
There is a growing need for healthcare institutions to develop responsiveness (Tolf, Nyström, Tishelman, Brommels, & Hansson, 2015; Vissers, Bertrand, & De Vries, 2001). However, the responsiveness of healthcare systems remains a complex, distinct and still not adequately investigated concept (Brinkerhoff & Bossert, 2013; Cleary, Molyneux, & Gilson, 2013; Gilson, Palmer, & Schneider, 2005; Siddiqi et al., 2009). Responsive healthcare systems anticipate and adjust to meet evolving requirements, exploiting opportunities to enhance access to effective interventions and to enhance health services (Hanefeld, Powell-Jackson, & Balabanova, 2017; Lodenstein, Dieleman, Gerretsen, & Broerse, 2013), ultimately resulting in improvements in outcomes of healthcare (Allotey, Davey, & Reidpath, 2014; Smith, Mossialos, Papanicolas, & Leatherman, 2009). A better understanding of healthcare responsiveness is particularly important for many nations with low and medium incomes such as Ghana, where economic and social development is rapidly advancing.
Nevertheless, responsiveness always implies that a flexible central system exists (More & Babu, 2008). Flexibility is required to respond quickly to the rapidly changing unique patient needs and demands (Aronsson, Abrahamsson, & Spens, 2011; Peltokorpi, Torkki, & Lillrank, 2011). Flexibility remains an expensive and challenging capability to develop and incorporate in any system completely. Identifying the right flexibility capabilities to develop can efficiently improve responsiveness to meet changing needs and demands of healthcare patients (Aronsson et al., 2011; Peltokorpi et al., 2011). Moreover, flexible scheduling and resources can help healthcare institutions respond more effectively to their patients by better matching the variable demand for care with the supply of physical resources such as beds, pharmaceutical, people and space required (Chen, Zhou, Ma, & Pham, 2011; Laker, Froehle, Lindsell, & Ward, 2014). Researchers have asserted that flexibility can be proactively employed as well to create a competitive advantage for a business (Chang, Yang, Cheng, & Sheu, 2003; Ettlie & Penner-Hahn, 2008; D. M. Upton, 2008). Profitable flexibility applications have been demonstrated in various ways: by the National Bicycle Industrial Company (Moffat, 1990), and by the General Motors ' Lordstown factory experiment (Kasarda and Rondinelli, 1998). Flexibility is clearly of the utmost significance (J. H. M. Manders, Caniëls, & Ghijsen, 2017) to the responsiveness of healthcare institutions, the economy, patient satisfaction and yet significant amount of existing literature focuses on the manufacturing sector (Chang, Chen, Lin, Tien, & Sheu, 2006; Jack & Raturi, 2002; Koste, Malhotra, & Sharma, 2004), with little or no attention to the service sector..
However, understanding the impact of specific flexibility capabilities and their application is critical to organizations as flexibility is expensive to implement; hence any investment in flexibility based on wrongly considered competences might be (Gerwin, 2008; Narasimhan, Talluri, & Das, 2004). There is also a paucity of studies concerning flexibility capabilities relating to operations of healthcare institutions. The quality of care and satisfaction with health facilities have been seen in most research as the perfect measure of assessing health systems performance. However, the WHO suggests responsiveness as a better measure of the performance of health systems (NB Valentine et al., 2003). Healthcare institutions are challenged by many sources of uncertainty in the supply chain and at an operational level. Though supply chain and operations flexibilities have the potential to promote the resilience and responsiveness of healthcare institutions, the scarcity of the literature in this respect makes this study worthwhile. As a result of limited literature at present, little knowledge exists on the extent to which supply chain and operations flexibilities individually promote responsiveness, or impact customer satisfaction, particularly within the service sector in Ghana.
Required:

a) Propose an appropriate research title whch will adequately capture the research gaps and issues discussed.
b) Propose FOUR (4) research objectives which will reflect the research issues discussed.   

c) Propose FOUR (4) research questions which will satisfy the research issues discussed.

In: Statistics and Probability

1)In lieu of the movement control orders (MCO), many restaurants are not able to cater to...

1)In lieu of the movement control orders (MCO), many restaurants are not able to cater to dine-in method. Instead, customers are allowed order in their food and collection of the food is channelled in three methods.

i)In recording the use case of Food Collection, several scenarios are possible. Define scenario.

ii)List THREE (3) possible scenarios for the use case of Food Collection.

2)What is the purpose of using digital signatures? Detail out the steps of conducting a digital signature.

3)Detail out the THREE (3) main elements that affect a scrum project.

In: Computer Science

Discuss the concept of cost transformation and how management accountants can contribute towards the cost transformation...

Discuss the concept of cost transformation and how management accountants can contribute towards the cost transformation of an organisation.

In: Accounting

What factors contribute to the demographic profile of north korea (fertility rate, family size, immigration, aging

What factors contribute to the demographic profile of north korea (fertility rate, family size, immigration, aging

In: Economics

What professional attributes should a coder/biller have to contribute to the overall health of the medical...

What professional attributes should a coder/biller have to contribute to the overall health of the medical office or hospital?

In: Nursing