Tag: variables

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Variables that influence an employee’s decision to leave or stay at an organization

Respond to the following in a minimum of 175 words: 
What are the variables that influence an employee’s decision to leave or stay at an organization (Hint: It’s not just money.)
Please include sources/references to support your perspective.

Part 2

Assess your Leadership Skills
Review the questions in Appendix 3: Glossary. (2007). Guide to Organisation Design, 302–315, page 5, under the heading ‘Gallup Q12’. Ask yourself these 12 questions to measure employment engagement and contemplate why these questions are practical. 
Respond to the following in a minimum of 175 words:
Do you consider yourself an engaged employee? 
Did these questions make you think of anything that can be done at your organization to increase employee engagement and performance? 
Would you add any questions to the list? 
How can managers in the healthcare industry utilize these questions?

Part 3

Exam Content
As a human resources manager in a healthcare organization, you will be asked to develop varying types of strategies and management techniques that improve the performance of your workforce. You need to know how to keep abreast of such strategies through research, as well as analyze how such strategies and techniques can be applied in your organization. In this assessment, you will apply these skills.
Select a healthcare organization and specific division within it with which you work or are familiar.
Assume you are the human resources director for your selected organization.
In a recent meeting, executive management determined it would like to improve healthcare workforce performance levels within a specific division of your organization.
Management has asked you to research and identify 3 diverse strategies that use innovative management techniques, operational practices, or technology that could be applied to improve workforce performance within the selected division at your healthcare organization.
Create a 1,050- to 1,400-word summary of 3 diverse strategies to improve workforce performance that includes the following:
Identification of 3 key strategies to improve workforce performance for your organization and division
An analysis of how each strategy could be deployed within your division and organization to improve workforce performance
A recommendation for the application of the best key strategy
An analysis of how your recommended strategy affects workforce needs for service delivery for your organization
SMART goal(s), objective(s), and tasks to implement your recommended strategy
A description of how goal achievement will be measured
Expenses for recommendation implementation
Cite 3 reputable references to support your assignment (e.g., trade or industry publications, government or agency websites, scholarly works, or other sources of similar quality).
Instructors Note:  Please carefully read and closely follow the assignment instructions and the content of the grading rubric. It is strongly suggested that you use subheadings for each assignment component. This will ensure that you are addressing each section of the assignment.

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Identifying dependent and independent variables and simple linear regression

Variables
This is a two-part assignment that will be submitted as one document. You
do not need to include the introduction or conclusion sections. Be sure that
you read the instructions here very carefully before you begin.
Part I. To complete the first part of this assignment, follow these instructions
to locate information that will help you practice ic. With this information,
you will explain assumptions and interpret statistics (F- and R-square).
Steps:
▪ Go to the US Department of Education: College Scoreboard. Then
select Search Field of Study.
▪ In the search bar, type in Public Administration, and then press enter.
▪ Select only Bachelor’s Degree and leave the Location field blank.
(You will have a list of approximately 200 public and private colleges
and universities. From the list of schools, select a minimum of 12
public colleges and universities. Ignore all private colleges and
universities).
▪ Select the Public Administration link under Bachelor’s Degree. (You
will see the Graduation Rate, Average Annual Costs, and Salary After
Completing Field of Study).
▪ Build a table from the information you collected. Ignore any public
college or university that does not provide all three data categories.
Utilizing the software of your choice, use this information to create a
table from the information you collected.
▪ create scatter plots, and
▪ conduct simple linear and multiple least squares regression
analysis.
Once you have completed the above steps, you will:
▪ Report on the simple linear regression scatter plot:
▪ Import the simple linear regression scatter plot into a word
document in APA Style and format.
▪ Import the simple linear regression analysis results in a word
document, in APA style and format.
▪ Explain if any assumptions of simple linear regression were
violated.
▪ Interpret the F-statistic, the R-square statistic, the significance
of the coefficient, t-test, and the significant coefficients.
▪
▪ Report on the multiple regression scatter plot.
▪ Import the multiple regression scatter plot into a word document
in APA style and format.
▪ Import the multiple regression analysis into a word document in
APA style and format.
▪ Explain if any assumptions of multiple-linear regression were
violated.
▪ Interpret the F-statistic, the R-square statistic, the significance
of the coefficient, t-test, and the significant coefficients.
Part II. As in previous units, revisions to the hypothesis and research
questions are necessary. If you feel revisions are needed, go ahead and
make them. If no revisions are needed, justify your decision. Keep in mind
you will be developing a quantitative research proposal.
Your final submitted document must be at least three pages in length. The
title and reference do not apply to the page count You may use the
textbook as one resource and two resources should be from the CSU
Online Library Research Databases.
Adhere to APA Style when constructing this assignment, including in-text
citations and references for all sources that are used. Please note that no
abstract is needed.
Do not do Part II or worry about the page count

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Objects or variables are clustered into homogeneous groups that are similar to each other and dissimilar to other groups.

one using RStudio Programming programm.

Cluster Analysis
(hierarchical & non-hierarchical)
• Grouping/clustering similar objects/cases (or also variables) into groups.
• Homogeneous/heterogeneous groups? • Segments? – Segmentation
• Profiles?
• Grouping variables?
[see also: N. K. Malhotra & D. F. Birks, 2007, Marketing Research: An Applied Approach (Chapter 23:
Cluster Analysis), 3rd European Edition, Prentice Hall, Inc., Pearson Education Limited, Essex, England.] Modul University Vienna
Aim
• Objects or variables are clustered into homogeneous groups that are similar to each other and dissimilar to other groups.
• Group/cluster membership is not known in advance. There is no a priori information. A data-driven grouping solution is produced.
• Number of clusters not fixed in advance when using hierarchical clustering but is selected subsequent to the procedure. Using nonhierarchical clustering the number of clusters has to be pre-specified. Different solutions should be compared.
• Optimum result for k clusters is not necessarily the same as hierarchical result for the kth step
• Result may heavily depend on the procedure chosen!
You will always get some cluster solution, also if there are no reasonable clusters!
Importing data in R: .csv-files
Locate the file and enter the path and file name to import the dataset

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Scatterplot
How many cultural and sporty activities would you plan for a one month trip?
Optional: Standardization
If variables used for cluster analysis are measured on different scales, they have to be standardized in the forefront (Z scores most frequently used). Otherwise measurement scale differences may have an influence on the result!
Standardization:
[Mean value deducted from every observation and divided by the standard deviation.]
Modul University Vienna
Hierarchical clustering procedure
Clustering procedure for hierarchical clustering can be
• agglomerative – every object starts in a separate cluster which are grouped into bigger and bigger clusters until all objects are in one cluster
• or divisive – a single cluster with all objects is split up until all objects are in separate clusters (also see Dendrogram) Linkage methods:
• Single linkage = nearest neighbour
• Complete linkage = farthest neighbour
• Average linkage = average distance between all pairs
• Centroid method = distance between cluster centroids
• Variance methods (minimize within-cluster variance) Ward‘s method – most frequently used! – combines clusters with smallest increase in overall sum of squared distance to the cluster means
Hierarchical clustering
Distance measure
• Similarity is determined by the distance between groups
• Default: Squared Euclidean distance – most often used – interval scale;
(v=number of variables, X and Y are the objects to be compared) various alternative distance measures available for interval, counts or binary data: e.g. City-Block or Manhattan-distance (sum of absolute distances), for binary data: -distance
Depending on the chosen distance measure results may change!
Modul University Vienna
Perform cluster analysis

Agglomeration schedule
• X1 and X2: If the values are negative, the two observations were merged at this stage (singleton agglomerations). If it is positive, it was merged at a former stage of the algorithm (non-singleton observations).
• cluster height: the criterion usedfor the agglomeration procedure (here the squared Euclidean distance).
• One can observe a dramatic increase in step 37. Further collapsing the 3 to two clusters will be problematic.
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Dendrogram
• Vertical lines represent distances between clusters that are put together.
• Coefficients are rescaled, here 0-50.
How many clusters
• Distances of last two stages are very large.
• Decision on three clusters? Or two? Depends on objectives!
• …are relevant in terms of practical/managerial considerations?
• Theoretically based? Literature?
• Useful sizes?
• Meaningful interpretation of cluster characteristics possible?
• Distance between clusters?
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Dendrogram
• Distances of last two stages are very large.
• Decision on three clusters? Or two? Depends on objectives!

Cluster membership and information
• Cluster membership variable of the 3 cluster solution is produced.

• The 1st group has 15 observations, the 2nd and 3rd have 12.

• The 1st group is neither interested in culture nor sports. The 2nd group is interested in culture but not in sports. The 3rd group is interested in sports but not in culture.
Modul University Vienna
Non-hierarchical clustering: k-means
• Disadvantage: Number of clusters has to be a priori fixed!!!
• Advantage: computationally less burdensome compared with hierarchical cluster analysis if many observations are contained in the dataset
• Optimising partitioning: Objects are reassigned iteratively between clusters and do not necessarily stay within one cluster once assigned to it (contrary to hierarchical clustering)
• Iteration:
1. Each objects is assigned to the cluster with thenearest cluster center (least squared Euclidean distance)
2. Recalculation of cluster centers
3. Loop: Continue with step 1
Distance measure
• Similarity (between preferably interval scaled variables) is determined by the squared Euclidean distance
• Notation: n=number of observations i=1,…,n
x and y are the objects to be compared
• The variance (squared Euclidean distances between all clustering variables and the centroid of each cluster), or socalled within cluster variation, is minimized.

Modul University Vienna
Number of clusters, iteration and random starts
• The number of clusters must be specified a priori!!!
• k-means uses an iterative algorithm to determine the cluster centers (1. objects are assigned to nearest cluster center, 2. calculation of cluster center, 3. continues with step 1). iter.max sets the maximum number of iterations. During classification the algorithm will continue iterating until iter.max iterations have been conducted or the convergence criterion is reached.
• Hint: A high iter.max value is recommended (e.g. 1,000) to allow for a high number of iteration steps and the algorithm to converge.
• As the final result depends on the starting values, k-means clustering should be run with several random starting values, here 25. The one with the lowest within-cluster variation will automatically be selected.
Random starts
• The a priori selected number of clusters must be specified!!!
• k-means uses an iterative algorithm to determine the cluster centers. iter.max sets the maximum number of iterations. During classification the algorithm will continue iterating until iter.max iterations have been done or the convergence criterion is fulfilled.
• If convergence criteria is not achieved the number of maximum iterations has to be increased until enough iteration steps (1. objects are assigned to nearest cluster center, 2. calculation of cluster center, 3. continues with step 1) are processed.
• Hint: A high max_iter value is recommended (e.g. 1,000) to allow for a high number of iteration steps and the algorithm to converge.
Modul University Vienna
Perform k-means clustering

• The number of cases in each cluster shows the size of each cluster in the dataset.
• Cluster means are the means of variables within clusters.
• Cluster vector = cluster membership
Cluster membership
• The cluster membership shows the case number in the rownames
(values 1 to 39) and the cluster number in the kcluster.cluster column.
• Case number 1 belongs to cluster 3, case number 13 belongs to cluster 1…
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Print k-means solution and cluster center
• Final Cluster Centers are the means of variables within clusters.

Cluster comparison
• Attention!
Judgement of differences between clusters for variables used in the algorithm via t-test or ANOVA?
No hypothesis test in the usual meaning, just descriptive!
Just an indicator which variables are relevent for clustering.
= Proper validation only by means of an external criterion not involved in cluster analysis!
= Profiling
Modul University Vienna
Profiling
• First, groups are described on the basis of the variables used for k-means clustering.
• Second, profiling describes clusters by means of other relevant variables not used during the clustering procedure (e.g. demographic, psychographic, geographic… characteristics).

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What Ethic Variables Are Most Important Doing Business

For this article assignment, read Ethics Capsule 1- “What Ethic Variables Are Most Important Doing Business” page 7 in your text

– the student will summarize the article in accordance with the required template. (See Below).

– the assignment will not exceed three pages in length. (The requirement of three pages is because in business, time is money. It is important that the student include all of the pertinent information of this article within these three pages. When compiling all of this data into three pages, it requires critiqued writing).

– it is important that the student summarizes the article, but equally important is the inclusion of their opinion based on the data and the student’s additional research.

– the final paper will be a cover page, three pages, and a reference page.

– in addition to the article, the student will use two additional outside source

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account several cultural variables

In the decision-making process, you must take into account several cultural variables. Describe one of the variables associated with risk tolerance and one of the variables associated with internal/external locus of control. Why are these important factors to consider? Your response must be at least 300 words in length.

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Describe one of the variables associated with risk tolerance and one of the variables associated with internal/external locus of control

In the decision-making process, you must take into account several cultural variables. Describe one of the variables associated with risk tolerance and one of the variables associated with internal/external locus of control. Why are these important factors to consider? Your response must be at least 300 words in length.

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What are the variables? What are the null and alternative hypotheses?

 Describe a study you might design that could use multiple regression. What are the variables? What are the null and alternative hypotheses? Why would multiple regression be appropriate for this design? What would multiple regression indicate in relation to your research question? What would it not indicate? Be specific and use your sample study to illustrate your answers. This response does not need to be supported with external research. 400 – 500 words 

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Look at the distribution of the continuous variables in the data set using PROC UNIVARIATE, including producing histograms and insets with means, standard deviations and sample size

1. Performing a One-Sample t-Test

The data in STAT1.NormTemp come from an article in the Journal of Statistics Education by Dr. Allen L. Shoemaker from the Psychology Department at Calvin College. The data are based on an article in a 1992 edition of JAMA (Journal of the American Medical Association), which questions the notion that the true mean body temperature is 98.6. There are 65 males and 65 females. There is also some question about whether mean body temperatures for women are the same as for men. The variables in the data set are as follows:

ID Identification number

BodyTemp Body temperature (degrees Fahrenheit)

Gender Coded (Male, Female)

HeartRate Heart rate (beats per minute)

a. Look at the distribution of the continuous variables in the data set using PROC UNIVARIATE, including producing histograms and insets with means, standard deviations and sample size.

b. Perform a one-sample t-test to determine whether the mean of body temperatures (the variable BodyTemp in STAT1.NormTemp) is 98.6. Produce a confidence interval plot of BodyTemp with the value 98.6 used as a reference.

1) What is the value of the t statistic and the corresponding p-value?

2) Do you reject or fail to reject the null hypothesis at the 0.05 level that the average temperature

2. Using PROC TTEST for Comparing Groups

Elli Sagerman, a Masters of Education candidate in German Education at the University of North Carolina at Chapel Hill in 2000, collected data for a study. She looked at the effectiveness of a new type of foreign language teaching technique on grammar skills. She selected 30 students to receive tutoring; 15 received the new type of training during the tutorials and 15 received standard tutoring. Two students moved away from the district before completing the study. Scores on a standardized German grammar test were recorded immediately before the 12-week tutorials and then again 12 weeks later at the end of the trial. Sagerman wanted to see the effect of the new technique on grammar skills. The data are in the STAT1.GERMAN data set.

Change Change in grammar test scores

Group The assigned treatment, coded Treatment and Control

Analyze the data using PROC TTEST. Assess whether the treatment group improved more than the control group.

a. Do the two groups appear to be approximately normally distributed?

b. Do the two groups have approximately equal variances?

c. Does the new teaching technique seem to result in significantly different change scores compared with the standard technique?

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A researcher is interested in the relationships between the following four variables: On-line game addiction, narcissistic personality traits, self-control, and aggression. Data are collected from a sample of 226 individuals. The data can be found in the assessment SPSS spreadsheet assessment.sav’. For each variable, higher values indicate greater levels of the variable. Analyse the data using SPSS and report the results using standard APA conventions. (20 marks)? The focus is clearly on the relationships between

On-line game
addiction, narcissistic personality traits, self-control, and aggression.

On-line game
addiction, narcissistic personality traits, self-control, and aggression.

QUESTION 1
A researcher is interested in the relationships between the following four variables: On-line game
addiction, narcissistic personality traits, self-control, and aggression. Data are collected from a
sample of 226 individuals. The data can be found in the assessment SPSS spreadsheet
‘assessment.sav’. For each variable, higher values indicate greater levels of the variable. Analyse
the data using SPSS and report the results using standard APA conventions. (20 marks)
? The focus is clearly on the relationships between

  • On-line game addiction
  • Narcissistic personality traits
  • Self-control
  • Aggression
    ? State what you are going to do to investigate this
  • Descriptives
  • Scatterplots
    ? Pearson Correlations Produce a table of descriptive statistics
  • Mean
  • Standard Deviation
  • Skew
  • Kurtosis
  • N
    ? Comment on any observed deviations in skew or kurtosis (Z-scores that are greater
    than +/- 1.96) but indicate that no transformations will be performed. Indeed, there are
    few options for kurtosis and it is not generally seen as a big problem anyway.
    ? Present scatter plots between all pairs of variables with lines of best fit added.
  • Could be individually or in a matrix.
  • Comment on what the relationships look like.
  • Do there seem to be any outliers, and if so, do they look like they are going to make an unacceptable impact on the relationship observed?
    ? Present correlations matrix.
  • Comment on the strength, significance and direction of the correlations.
    QUESTION 2
    Following the initial analysis conducted in Q1 the researcher goes on to look at which of the
    variables (On-line game addiction, narcissistic personality traits, and self-control) are the best
    predictors of aggression. Analyse the data using SPSS and report the results using standard APA
    conventions. (30 marks)
    ? All needs to be referenced according to APA style.
    ? It requires multiple regression
    ? Briefly indicate whether the variables would be expected to be good predictors based on correlations reported in question 1
    ? R Squared
    ? Anova – significance and what it means
    ? Individual Predictors
    o Beta coefficients and confidence intervals
    o T-tests for the beta coefficients § Part correlations (compare to zero order)
    o Collinearity
    ? Indicate which appears to be best predictor, second, third.
    ? State the regression equation
    QUESTION 3
    The researcher also thinks that it is possible that there are sex differences for these variables. You
    will also find codes for males and females in the data set. Analyse the data using SPSS to investigate
    this, and report the results using standard APA conventions. (20 marks)
    ? All needs to be referenced according to APA style.
    ? State that you performed Independent Sample t-tests to identify if sex differences exist.
    ? Table of descriptive statistics
  • Mean, SD, N
    ? Report each t-test separately:
    EXAMPLE:
    The 31 participants in the rosemary condition (M = 15.90, SD = 2.45) performed significantly better on time based prospective memory than the 34 participants in the no aroma condition (M = 14.41, SD = 2.451), t(63) = – 2.59, p = .012. Calculation of Cohen’s d indicated the presence of a medium effect size, d = .64, 95% CI [.14, 1.14].
    ? Draw an overall conclusion. Are there sex differences? Which variables? How big? Consistently in the same direction?
    QUESTION 4
    As I further investigation, the researcher wants to see if playing a violent video game increases
    levels of aggression. She runs a study in which aggression levels are measured in 40 participants
    before and after playing a violent video game. Use SPSS to compare the variables Aggro_pre and
    Aggro_post in order to answer this question. (10 marks)
    ? All needs to be referenced according to APA style.
    ? State that you performed a Paired samples t-test to see if aggression after playing the game is greater than before.
    ? Table of descriptive statistics
    o Means, SD, N
    o Report t-test.
    EXAMPLE:
    The results from the time based prospective memory test (M = 15.12, SD = 2.42) and the event based prospective memory test (M = 15.75, SD = 1.64) revealed significantly better performance for event based prospective memory, t(64) = -2.11, p = .039. Calculation of Cohen’s d indicated the presence of a small effect size, d =.26, 95%CI [.01, .50].
    ? Draw a conclusion. Is the effect potentially important?
    QUESTION 5 (Needs bibliography review)
    Explain the advantage of reporting effect sizes in addition to significance levels. (20 marks)
    ? What is statistical significance?
    ? What is effect size?
    ? The distinction between statistical significance and scientific (or practical)
    importance.
    ? Give an example.
    ? Factors that affect significance
    ? Problem with effect sizes eg many different types
    ? Value of effect size in addition to statistical significance
    ? Overall summary/conclusion
    ? All needs to be referenced according to APA style

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Two variables in Jamovi: one nominal and one ordinal or continuous

Create two variables in Jamovi: one nominal and one ordinal or continuous

Name the variables and, if appropriate, label the levels.

Take a screenshot of each variable showing the name and levels (if appropriate for the variable).

Organize this in a Word document and upload this document to Canvas to submit your assignment.