Respond using one or more of the following approaches:
Ask a probing question, substantiated with additional background information, and evidence.
Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
Group B
Inferential Statistics- Based on probability; used to draw conclusions or make generalizations about a given population or problem.
Example: “What can I infer about 5-minute Apgar scores of premature babies (the population) after calculating a mean Apgar score of 7.5 in a sample of 300 premature babies?” (McGonigle & Mastrain, p. 376, 2017).
Sampling Distributions- A sampling distribution is the frequency distribution of a statistic over many random samples from a single population.
Sampling Distribution of the Mean – as an example we randomly draw test scores from 25 students out of a total group of 5,000. We then calculate the mean, then draw a new group and repeat; each mean will serve as one datum, or data point.
Hypothesis Testing- is the use of statistics to determine the probability that a given hypothesis is true.
Null Hypothesis- the hypothesis that there is no significant difference between specified populations; or differences can be attributed to sampling or experimental error
Type 1 Error- This error occurs when we reject the null hypothesis when we should have retained it.
Type 2 Error- This error occurs when we fail to reject the null hypothesis. In other words, we believe that there isn’t a genuine effect when actually there is one.
Parametric statistics – A class of statistical tests that involve assumptions about the distribution of the variables and the estimation of a parameter.
Nonparametic statistics – A class of statistical tests that do not involve stringent assumptions about the distribution of variables. Between-subject design – A research design in which separate groups of people are compared (e.g. smokers and nonsmokers; intervention and control group subjects). Within-subject design – A research design in which a single group of participants is compared under different conditions or different points in time (e.g. before and after surgery).
Two classes of Statistical Tests:
Parametric tests – tests involving an estimation of a parameter, the use of interval or ratio-level data, and the assumption of normally distributed variables. Include t-tests and ANOVA.
Nonparametric tests – used when the data are nominal or ordinal or when a normal distribution cannot be assumed. Include the Mann-Whitney U test, Wilcoxon signed – rank test, and Kruskal – Wallis test.
Statistical Tests
T-test parametric procedure identifying mean differences for two independent groups, like experiment versus control or dependent groups, like pretreatment and post-treatment scores.
One – way ANOVA – tests the relationship between one categorical independent variable, such as different interventions, and a continuous dependent variable.
Independent t-test – used to compare mean values of a single group to a hypothesized value.
Two- way ANOVA – tests multiple hypotheses with two independent variables
Paired t -test – Obtaining two measurements from the same people or from a paired set of participants. This measures the difference between two related groups. Used when the means for two sets of scores are not independent.
Repeated – measures ANOVA – tests the same group using three or more measures of the same dependent variable.
ANOVA – parametric procedure for testing differences between means when there are more than three groups.
Chi-Square test – used to test hypothesis about group differences in proportions. It is computed by comparing observed frequencies and expected frequencies, in which there was no relationship between variables.
One-tailed test – A statistical test in which only values in one tail of distribution are considered in determining significance. A one-tailed test allots all of your alpha to testing the statistical significance in the one direction of interest.
Two-tailed test – Statistical tests in which both ends of the sampling distribution are used to determine improbable values. A two-tailed test allots half of your alpha to testing the statistical significance in one direction and half of your alpha to testing statistical significance in the other direction.
There are different types of statistical methodologies, inferential statistics are based on probability. Ali and Bhaskar (2016) define probability as “the likelihood that an event will occur” (para. 21). According to Hyatt, Powell, Johnson, and Caldwell (2017) a working knowledge of inferential statistics is needed to understand, interpret, and critically evaluate research studies. The basic premise of inferential statistics is to generate data from random samples and use it to describe or make inferences about an entire population (Ali & Bhaskar, 2016). A basic understanding of inferential tests will help nurses implement research into evidence-based pracitce.
While there are various inferential tests, it is important to understand that they all use probability to infer meaning; that meaning is subsequently applied mathematically to a larger population. For example, Polit and Beck (2017) report that the T-tests is a hypothesis testing tool which compares two groups of data sets to find the difference between them. In nursing research, this test can be utilized to determine if there is causality or any relationship between data sets. Analysis of variance (ANOVA) involves mathematically analyzing data. This test is useful in comparative analysis. For example, the efficacy of interventions, such as different ambulation protocols can be compared with through ANOVA. Inferential statistics also facilitate comparisons of proportions; this is achieved with the Chai Square test. This test is often used to compare differences between the interventional and the control groups (Polit, Beck 2017). While it is unlikely that non-researchers will retain knowledge of the various statistical tests, being able to identify the statistical methodology will help them to better interpret research results.
References
Ali, Z., & Bhaskar, S. B. (2016). Basic statistical tools in research and data analysis. Indian journal of anaesthesia, 60(9), 662–669. doi:10.4103/0019-5049.190623
Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for Nursing practice (10th Ed.). Philadelphia, PA: Wolters Kluwer.Chapter 17, “Inferential Statistics”
Hayat, M. J., Powell, A., Johnson, T., & Cadwell, B. L. (2017). Statistical methods used in the public health literature and implications for training of public health professionals. PloS one, 12(6), e0179032. doi:10.1371/journal.pone.0179032
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"
Greek Cuban And Hindu Health Care System
/in Uncategorized /by developer1. Greek and Hindu heritage are base on the oriental culture and the Cuban heritage in occidental. Please discuss the beliefs of these three cultures and how they influence the delivery of health care.
2. Compare these three culture and how disease and prevention it is influence by the cultural practices.
APA word Arial 12 font attached to
A maximun of 500 words are required.
A minimum of 2 evidence based references are required.
please include header ++ cover page
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"
Group B Post
/in Uncategorized /by developerRespond using one or more of the following approaches:
Ask a probing question, substantiated with additional background information, and evidence.
Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
Group B
Inferential Statistics- Based on probability; used to draw conclusions or make generalizations about a given population or problem.
Example: “What can I infer about 5-minute Apgar scores of premature babies (the population) after calculating a mean Apgar score of 7.5 in a sample of 300 premature babies?” (McGonigle & Mastrain, p. 376, 2017).
Sampling Distributions- A sampling distribution is the frequency distribution of a statistic over many random samples from a single population.
Sampling Distribution of the Mean – as an example we randomly draw test scores from 25 students out of a total group of 5,000. We then calculate the mean, then draw a new group and repeat; each mean will serve as one datum, or data point.
Hypothesis Testing- is the use of statistics to determine the probability that a given hypothesis is true.
Null Hypothesis- the hypothesis that there is no significant difference between specified populations; or differences can be attributed to sampling or experimental error
Type 1 Error- This error occurs when we reject the null hypothesis when we should have retained it.
Type 2 Error- This error occurs when we fail to reject the null hypothesis. In other words, we believe that there isn’t a genuine effect when actually there is one.
Parametric statistics – A class of statistical tests that involve assumptions about the distribution of the variables and the estimation of a parameter.
Nonparametic statistics – A class of statistical tests that do not involve stringent assumptions about the distribution of variables. Between-subject design – A research design in which separate groups of people are compared (e.g. smokers and nonsmokers; intervention and control group subjects). Within-subject design – A research design in which a single group of participants is compared under different conditions or different points in time (e.g. before and after surgery).
Two classes of Statistical Tests:
Parametric tests – tests involving an estimation of a parameter, the use of interval or ratio-level data, and the assumption of normally distributed variables. Include t-tests and ANOVA.
Nonparametric tests – used when the data are nominal or ordinal or when a normal distribution cannot be assumed. Include the Mann-Whitney U test, Wilcoxon signed – rank test, and Kruskal – Wallis test.
Statistical Tests
T-test parametric procedure identifying mean differences for two independent groups, like experiment versus control or dependent groups, like pretreatment and post-treatment scores.
One – way ANOVA – tests the relationship between one categorical independent variable, such as different interventions, and a continuous dependent variable.
Independent t-test – used to compare mean values of a single group to a hypothesized value.
Two- way ANOVA – tests multiple hypotheses with two independent variables
Paired t -test – Obtaining two measurements from the same people or from a paired set of participants. This measures the difference between two related groups. Used when the means for two sets of scores are not independent.
Repeated – measures ANOVA – tests the same group using three or more measures of the same dependent variable.
ANOVA – parametric procedure for testing differences between means when there are more than three groups.
Chi-Square test – used to test hypothesis about group differences in proportions. It is computed by comparing observed frequencies and expected frequencies, in which there was no relationship between variables.
One-tailed test – A statistical test in which only values in one tail of distribution are considered in determining significance. A one-tailed test allots all of your alpha to testing the statistical significance in the one direction of interest.
Two-tailed test – Statistical tests in which both ends of the sampling distribution are used to determine improbable values. A two-tailed test allots half of your alpha to testing the statistical significance in one direction and half of your alpha to testing statistical significance in the other direction.
There are different types of statistical methodologies, inferential statistics are based on probability. Ali and Bhaskar (2016) define probability as “the likelihood that an event will occur” (para. 21). According to Hyatt, Powell, Johnson, and Caldwell (2017) a working knowledge of inferential statistics is needed to understand, interpret, and critically evaluate research studies. The basic premise of inferential statistics is to generate data from random samples and use it to describe or make inferences about an entire population (Ali & Bhaskar, 2016). A basic understanding of inferential tests will help nurses implement research into evidence-based pracitce.
While there are various inferential tests, it is important to understand that they all use probability to infer meaning; that meaning is subsequently applied mathematically to a larger population. For example, Polit and Beck (2017) report that the T-tests is a hypothesis testing tool which compares two groups of data sets to find the difference between them. In nursing research, this test can be utilized to determine if there is causality or any relationship between data sets. Analysis of variance (ANOVA) involves mathematically analyzing data. This test is useful in comparative analysis. For example, the efficacy of interventions, such as different ambulation protocols can be compared with through ANOVA. Inferential statistics also facilitate comparisons of proportions; this is achieved with the Chai Square test. This test is often used to compare differences between the interventional and the control groups (Polit, Beck 2017). While it is unlikely that non-researchers will retain knowledge of the various statistical tests, being able to identify the statistical methodology will help them to better interpret research results.
References
Ali, Z., & Bhaskar, S. B. (2016). Basic statistical tools in research and data analysis. Indian journal of anaesthesia, 60(9), 662–669. doi:10.4103/0019-5049.190623
Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for Nursing practice (10th Ed.). Philadelphia, PA: Wolters Kluwer.Chapter 17, “Inferential Statistics”
Hayat, M. J., Powell, A., Johnson, T., & Cadwell, B. L. (2017). Statistical methods used in the public health literature and implications for training of public health professionals. PloS one, 12(6), e0179032. doi:10.1371/journal.pone.0179032
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"
Group Management For Just Culture
/in Uncategorized /by developerDiscu
Discussion: Making the Case for Capital
Discussion: Group Management for Just Culture
This Discussion examines the opportunities of managers in working with groups to promote change that facilitates the delivery of safe, high–quality care.
To Prepare
By Day 3
Post a description of an adverse event in your organization and your analysis of the issue using the Regulatory Decision Pathway. Explain how role conflict or ambiguity might have influenced this situation. Apply the principles of just culture as you explain how you, as the group’s manager, would handle the situation.
Read a selection of your colleagues’ responses.
By Day 6
Respond to at least two of your colleagues on two different days using one or more of the following approaches:
Reference
Pepe, J., & Cataldo, P. J. (2011). Manage risk, build a just culture. Health Progress. Retrieved from http://www.outcome–eng.com/wp–content/uploads/2012/01/manage–risk.pdf
Russell, K. A. & Radtke, B. K. (2014). An evidence–based tool for regulatory decision–making: regulatory decision pathway. Journal of Nursing Regulation, 5(2), 5–9.
Marquis & Huston, Leadership roles and management functions in nursing, 2015
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"
Group Powerpoint
/in Uncategorized /by developerIn a 5- to 10-slide PowerPoint presentation, address the following:Provide an overview of the article you selected, including answers to the following questions:What type of group was discussed?Who were the participants in the group? Why were they selected?What was the setting of the group?How often did the group meet?What was the duration of the group therapy?What curative factors might be important for this group and why?What “exclusion criteria” did the authors mention?Explain the findings/outcomes of the study in the article. Include whether this will translate into practice with your own client groups. If so, how? If not, why?Explain whether the limitations of the study might impact your ability to use the findings/outcomes presented in the article.
Here is the article
Yildiran, H., & Holt, R. R. (2015). Thematic analysis of the effectiveness of an inpatient mindfulness group for adults with intellectual disabilities. British Journal of Learning Disabilities, 43(1), 49–54. doi:10.1111/bld.12085Note: Retrieved from Walden Library databases.
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"
Group Process And Stages Of Formation
/in Uncategorized /by developerIn a 2- to 3-page paper, address the following:
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"
Group Processes And Stages Of Formation
/in Uncategorized /by developerGroup Processes and Stages of Formation
In a 2- to 3-page paper not including cover and reference page, address the following:
Explain the group’s processes and stage of formation.
Explain curative factors that occurred in the group. Include how these factors might impact client progress.
Explain intragroup conflict that occurred and recommend strategies for managing the conflict. Support your recommendations with evidence-based literature.
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"
Group Project 18994923
/in Uncategorized /by developerScenario: Health Systems: Daniel, a DNP prepared ED NP identified that patients seen in the ED for various reasons had undiagnosed HTN. He observed that the patient’s chief compliant was well addressed but the HTN was not. He has approached the hospital system about the problem and suggested an outpatient clinic adjacent to the ED to address the HTN and other coincidentally found problems. What AP roles, core competencies and support are needed to make this happen?
1- Discuss transformational leadership and how it applies to a RN in the outpatient clinic.
*Discuss applying all or some of the 7 core competencies.
*Most be 2-3 power point slides.
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"
Group Project 19411735
/in Uncategorized /by developerInstructions:
This week you will be assigned to a group and be given a domain to develop/discuss applying all or some of the 7 core competencies. Group members need to assume AP roles (clinical and non-clinical) either by volunteering or being assigned by the group leader. A group leader must be decided and may be a nurse manager/nurse administrator, CNS, NP (maybe more than one and from different specialties), NI, and NE.CNLs and RNs may be also be part of the group scenario. All members are expected to demonstrate leadership knowledge and skills, but also must be willing to follow.Each group will demonstrate the core competencies and principals of transformational leadership in the group work. (See rubric).To ensure understanding of leadership styles, each group member will discover their own professional leadership style by an individual self-assessment online.Assignments and responsibilities should be equally assumed by group members. The final evidence of the group work will be power point presentation that discusses the scenario addressing the assigned domain, the roles and the outcomes. Please note that although a group project, individual grading rubric will be used to determine individual grades.(See below).
The master’s prepared nurse demonstrates leadership in the four domains: the profession of nursing, clinical practice arena, health policy arena, and systems level. The impact could be found in health promotion, disease prevention/management, quality improvement and/or within management of a health system. In order to complete this assignment, each group member will complete anassessmentabout your leadership style and post to the group area their leadership style.
Cherry, K. (2016). What’s Your Leadership Style? Learn more about your strengths and weaknesses as a leader.
My leaderships style is Democratic leader, also known as participative leaders, accept input from one or more group members when making decisions and solving problems, but the leader retains the final say when choices are made. Group members tend to be encouraged and motivated by this style of leadership.
This style of leadership often leads to more effective and accurate decisions, since no leader can be an expert in all areas. Input from group members with specialized knowledge and expertise creates a more complete basis for decision-making.
Remember, good leaders utilize all three styles depending upon the situation. For example:
How to Become a Better Leader
In conclusive remarks, search and agree upon a quotation from a library article related to leadership in an advanced nursing role and include with how it applied to your clinical decision/management issue of your assigned domain. Leadership journals from SOU Library areThe Journal of Nursing Scholarship or Nursing Leadership Forum or the American Journal of Nursing, Journal of Nursing Administration, Nursing Administration Quarterly, Nursing Management or Health Care Management Review
Group Topic:
Health Systems: Daniel, a DNP prepared ED NP identified that patients seen in the ED for various reasons had undiagnosed HTN. He observed that the patient’s chief compliant was well addressed but the HTN was not. He has approached the hospital system about the problem and suggested an outpatient clinic adjacent to the ED to address the HTN and other coincidentally found problems. What AP roles, core competencies and support are needed to make this happen?
Submission Details:
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"
Group Project 19450385
/in Uncategorized /by developergroup project
please see the guide line I attach the guideline and the source of writing which is ”Education as Engine” file. please do it as soon as possible
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"
Group Project 19450391
/in Uncategorized /by developergroup project :
please see the guide line I attach the guideline and the source of writing which is ”Education as Engine” file. please do it as soon as possible
"Looking for a Similar Assignment? Get Expert Help at an Amazing Discount!"