Running head: PART 2: ANALYSIS O SOFTWARE SPSS (PASW) 1
PART 2: ANALYSIS O SOFTWARE SPSS (PASW) 8
PART 2 OF SPSS (PASW) SOFTWARE ANALYSIS
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PART 2 OF SPSS (PASW) SOFTWARE ANALYSIS
Introduction
Few areas have been affected by technological advancement more dramatically than the methods for the display of results of experimentation and inquiry for tables, maps, drawings, graphs, charts and photographs. The changes have significantly increased the flexibility authors take for effective presentation of results.
Using figures and tables, enables authors to show a large amount of information competently and to make their data more inclusive. Tables are used to show numerical values or textual information. A figure can be a chart, a photograph, a drawing, a chart or any other illustration arranged in different manners. Tables are usually characterized by rows and columns structure, while a figure is any other type that is not a table.
Proper ways of data displays serve for effective communication of what the author intends to communicate. Consequently, it is vital for scientific articles’ authors to master the process of figures and tables preparation
Figures and tables presentation
For clear communication of a large dataset without the need to read the text that explains a figure of a table, all figures or tables presented in any authored material need to be understandable and self-explanatory.
When dealing with categorical data distribution need to be arranged as per the occurrence of a variety of the results. Tables are ideal to present a descriptive statistic of a given dataset as the frequencies provide a basic understanding of data under analysis as table 1 below indicate where different numerical values statistics are presented by the available dataset. Furthermore, distribution frequency of numerical variables can be presented in forma histogram chart, a frequency polygon chart or a table.
Table 1:
Occupational safety’s descriptive statistics for at a given work place
N
Range
Mean
Std. Deviation
Variance
NumEmps
51
40.000
24.01961
7.495306
56.180
Hours Worked
51
83200.000
49960.78431
15590.235899
243055455.373
PerSafeBeh
51
.577
.86582
.138945
.019
Injury rate
51
76.923
15.17570
17.474677
305.364
Safety climate
51
4.300
4.69706
1.034973
1.071
Risk
51
6.000
4.58824
2.011730
4.047
Experienced coded
51
2.000
1.96078
.823669
.678
If one is representing complex experimental design, the table can be summarized in compact tables, making the entire structure of the of the table display clear without the need for a lengthy textual description. The key features of the samples can be briefly summarized in a table as table 1 above shows.
Figure 1: Line graph showing correlation between climate safety and rate of injury for occupation safety of selected site
Table 2
ANOVA: Analysis of linear regression for the rate of injury against climate safety
Model
Amount of Squares
Df
Mean Square
F
Sig.
Regression
2.453
1
2.453
.008
.930b
Residual
15265.765
49
311.546
When point estimates are included in a table, for instance correlation or regression slopes, where possible, include the confidence intervals. It can be reported either by use of brackets or as text or giving lower and upper limit in a separate columns. In text state the confidence interval for instance the tables prepared are based on 95% confidence interval.
The generated linear analysis of the regression p=0.930 F=0.08 shows that the safety of the climate, shown in the prediction in rate of injury, is insignificant because p>0.05. The graph on figure 1 is used to affirmed the data using the above line, where it is apparently visible that modest alignment (or correlation) between the injury rate and climate safety. Furthermore, a high degree of variation is shown in Figure 1 indicating signifying difficulty in predicting mean rate of injury at all times. It is essential to note that the high rate of standard deviation for climate safety score as a proportion of all the 7 points scale.
Figure 2: Pie chart showing the site’s number of hours
There are many different types of figures to present a given data set, key in the preparation of the information value of the figure in the paper or presentation context in the appearance of the figure. In the case the figure adds no value to the thoughtful of the paper or duplicates other rudiments of the paper, it needs not to be included. Additionally, if the figure is only the best way to communicate specific information, then it needs to be précised. For instance, figure two above shows the hours worked by each site. The figure communicates the hours worked for each site of the samples.
Conclusion
In generally, each table analyzed need to be easy to understand, standardization of values presented having cells with the similar decimal places, a title should be indicated what is being described and when the data was collected. It should give more information on heading, when needed. It should be put to the article when mentioned in the text.
Similarly graphs need to contain below the figure, a title with appropriate information referring to the figures in the text, the source providing the data is quoted, then demonstrate the used scale being used and be self-explanatory.
References
Allen, P. J., & Bennett, K. (2010). PASW statistics by SPSS: A practical guide: Version 18.0. South Melbourne: Cengage Learning.
Miner, G. (2012). Practical text mining and statistical analysis for non-structured text data applications. Academic Press.
Pallant, J. (2013). SPSS survival manual. McGraw-Hill Education (UK).
George, D. (2011). SPSS for windows step by step: A simple study guide and reference, 17.0 update, 10/e. Pearson Education India.
Hox, J. J., Moerbeek, M., & van de Schoot, R. (2010). Multilevel analysis: Techniques and applications. Routledge.
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