¶ … Cluster Analysis
By using two different data sets, this paper aims at improving two analyses conducted relating to leadership effectiveness and community policing studies. In addition, in the paper, reliability tests and factor analyses on some of the six scales of importance used in the Community Policing study are looked at in-depth. Besides, the analysis conducted by Dr. Eveland is re-evaluated in this paper.
Leadership Effectiveness
From the report conducted by Dr. Eveland, several multiple regression analyses were initiated to help determine the existence of any relationship among the nine scales to the dependable variable, Q75; overall satisfaction with the manager as a leader. When plotted in a graph, the variable moderately skewed toward higher values.
Additionally, a simple multiple regression of all the predictors showed a statistically significant relationship between predictors and variables (F = 19.33, df = 9, 462, p< 0.001, R2 = 0.27). Nevertheless, beta coefficients for individual predictors for most variables were not significant; it is only Communication which is a significant predictor with a beta of 0.33. Since the varying means and variances among the predictors, a stepwise regression was used to correct the results (Eveland, 2008). The regression analysis produced a significant result with three predictors (F = 56.0, df = 3, 468, p < 0.001, R2 = 0.26). Outlined below are the significant predictors and their coefficients.
Unstandardized Coefficients
Standardized Coefficients
t
Significance
Model
B
Standard Error
Beta
(Constant)
1.28
6.05
0.00
Communication
0.46
0.07
0.33
6.56
0.00
Planning/Execution
For communication, the variable Q8, genuinely listens to people had 0.23, Q17; shares information readily peaked at 0.24 while Q53, encourage and accept feedback from others was 0.20. Besides, Q61 asks questions to ensure effective two-way communication had a meager 0.16.
Planning/Execution variables Q2, spends quality time on planning and Q63; consistently follows-through on his/her commitments recorded means of 0.15 and 0.63 respectively.
Finally Teamwork's Q5, demonstrates a personal commitment to teamwork was 0.19, Q14, effectively leads teams to achieve business results became 0.26 and Q50, appreciates diverse viewpoints (those that differ from his/her own) recorded at 0.25.
In this regard, a final analysis repeating the stepwise regression was conducted separately for each of the four reporting groups. According to the table below, the analyses shown are appropriate given the significant differences between the means of overall satisfaction by groups.
f df p
R2
Significant Predictors and Betas
Self
49.05
1,58
transforms correlations among a set of observed variables into smaller number of factors, containing essential information about the linear inter-relationships among the original test scores (Kriegel, Kroger, Sander, & Zimek, 2011). Factor analysis is used in behavioral sciences, social sciences, and other applied sciences dealing with large quantities of data. In addition, factor analysis is subdivided into two major groups; exploratory and confirmatory. Cluster analysis on the other hand
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