Importance of Statistical Package for Social Sciences and Data Analysis - Report Example

The Purpose of This Report This report intends to show the use of the statistics software- SPSS (Statistical Package for Social Sciences) during research. SPSS is a software package, mainly used in the social sciences, to assist researchers who lack skills in quantitative analysis methods (Armstrong & Everett 1990). The data being utilized, in this report, is obtained by a survey. The survey investigates the ethical decision-making in human resource management. The survey was distributed among individuals in service organizations, semi-government authorities, and private organisations. The total number of questionnaires distributed was 175 and out of these 100 were returned. Manning and Munro (2007) will be utilized as a guide, for the analysis, throughout the report. Therefore, this report will cover eight assessment items in the study guide by using SPSS. Assessment Item 2.1 2.1.1 Scale Measurement Scale Measurement for Variable, ID: This variable is used as an identification number for each of the 100 questionnaires. Scale Measurement for Variable, Gender: Nominal scale is used to indicate a male and female answer in this case. Scale Measurement for Variable, Age: Ordinal scale is used to answer a single response and it also rank-orders the categories in meaningful way. Scale Measurement for Variable, Job in HR: Ordinal scale is used to elicit a single response and it also rank-orders the categories in meaningful way. Scale Measurement for Variable, Time in Job: Ordinal scale is used to elicit a single response and it also rank-orders the categories in meaningful way. Scale Measurement for Variable, Salary: Ordinal scale is used to elicit a single response and it also rank-orders the categories in meaningful way. Scale Measurement for Variable, Orgtype: Nominal scale is used for three items to elicit a single response in this case. Scale Measurement for Variable, Ethical 1, 2 and 3: Internal scale is used with seven-point scale. 2.1.2 Data File Please see the file attached as Appendix ‘A’. Assessment Item 2.2 2.2 Descriptive Statistics for Survey Data 2.2.1 Descriptive Statistics for Frequencies Descriptive statistics help in understanding the dimensions of the data under review (Sternstein 1996). The two major techniques used are frequencies, and the standard deviation and the mean. A total of 100 participants were surveyed among whom three failed to indicate their gender. A total of 37 percent participants were male while 60% were female. Please refer Table 1 in Appendix ‘B’ attached to this report. Among 100 participants, 15% were between 21 and 30 years, 26% between 31 to 40 years, 41% between 41 and 50 years, 16% were between 51 to 60 years, while rest two participants were over 60 years of age. Please refer Table 2 in Appendix ‘B’ attached to this report. For time in Human Resource, 9% were working in the HR field for less than 1 year, 6% were working in the HR field between 1 to 2 years, 14% were working in the HR field between 3 to 5 years, 27% were working in the HR field between 6 to 10 years, 44% were working in the HR field for more than 10 years. Please refer Table 3 in Appendix ‘B’ attached to this report. For Time in Job, 27% were working in the present job for less than 1 year, 30% were working in the present job between 1 to 2 years, 27% were working in the present job between 3 to 5 years, 10% were working in the present job between 6 to 10 years, 6% were working in the present job for more than 10 years. Please refer Table 4 in Appendix ‘B’ attached to this report. Survey analysis for salary indicated that 10% had their current salary between $31,000 and $40,000 pa, 31% had their current salary between $41,000 and $55,000 pa, 40% had their current salary between $56,000 and $70,000 pa, 18% had their current salary between $76,000 and $100,000 pa. 1% had their current salary over $100,000 per annum. Please refer Table 5 in Appendix ‘B’ attached to this report. 57% indicated that their organization type was part of the public service, 26% organization type was a semi-government authority, and 14% organization type was private sector, while 3% failed to identify the type of their organization. Please refer Table 6 in Appendix ‘B’ attached to this report. 2.2.2 Descriptive Statistics for Mean and Standard Deviation Mean measures the average of all the values while the standard deviation measures the level of deviation, of values, from the computed mean. The mean for Loyalty to Org is 3.07 with standard deviation of 2.212 and variance 4.894. The median is 3.0 and standard deviation of the difference between the estimated values and the true values is 0.241 (standard error). The mean for Ethical 1 is 3.50 with standard deviation of 1.403 and variance 1.970. The median is 3.0 and standard error is 0.241. The mean for Ethical 2 is 3.52 with standard deviation of 1.396 and variance 1.949. The median is 4.0 and standard error is 0.241. The mean for Ethical 3 is 3.54 with standard deviation of 1.321 and variance 1.746. The median is 4.0 and standard error is 0.241. Please refer Table 1 in Appendix ‘C’ attached to this report for mean and standard deviation. 2.2.3 Descriptive Statistics Crosstabulations There were total of 37 males in the survey, of which 5 males (13.5%) were between 21 to 30 years of age, 8 males (21.6%) in age between 31 to 40 years, 15 (40.5%) males in age between 41 to 50 years, 8 males (21.6%) in age between 51 to 60 years, and 1 male (2.7%) was over 60 years of age. There were 60 females in the survey, of which 10 females (16.7%) were between 21 to 30 years of age, 15 females (25.0%) in age between 31 to 40 years, 26 females (43.3%) in age between 41 to 50 years, 8 females (13.3%) in age between 51 to 60 years, and 1 female (1.7%) was over 60 years of age. Please refer Table 1 in Appendix ‘D’. 2 (5.4%) male and 6 (10.0%) females indicated they were working in HR field for less than 1 year. 2 (5.4%) males and 4 (6.7%) females indicated they were working in HR field between 1 to 2 years. 2 (5.4%) males and 11 (18.3%) females indicated they were working in HR field between 3 to 5 years. 13 (35.1%) males and 13 (21.7%) females indicated they were working in HR field between 6 to 10 years. 18 (48.6%) males and 26 (43.3%) females indicated they were working in HR field between 6 to 10 years. Please refer Table 2 in Appendix ‘D’. 10 (27.0%) males and 16 (26.7%) females indicated they were working in the present job for a period of less than 1 year. 12 (32.4%) males and 18 (30.0%) females indicated they were working in the present job between 1 to 2 years. 7 (18.9%) males and 20 (33.3%) females indicated they were working in the present job between 3 to 5 years. 4 (10.8%) males and 5 (8.3%) females indicated they were working in the present job between 6 to 10 years. 4 (10.8%) males and 1 (1.7%) females indicated they were working in the present job for more than 10 years. Please refer Table 3 in Appendix ‘D’. 1 (2.7%) male and 8 (13.3%) females indicated that their current salary was between $31,000 and $40,000 pa. 9 (24.3%) males and 21 (35.0%) females indicated that their current salary was between $41,000 and $55,000 pa. 17 (45.9%) males and 22 (36.7%) females indicated that their current salary was between $56,000 and $70,000 pa. 10 (27.0%) males and 8 (13.3%) females indicated that their current salary was between $71,000 and $100,000 pa. There was none male and only one (1.7%) female who indicated that her current salary was over $100,000 per annum. Please refer Table 4 in Appendix ‘D’. 19 (52.8%) males and 35 (60.3%) females indicated that their organization type was part of the public service. 10 (27.8%) males and 16 (27.6%) females indicated that their organization type was a semi-government authority. 7 (19.4%) males and 7 (12.1%) females indicated their organization type to be a private sector. Please refer Table 5 in Appendix ‘D’. Assessment Item 2.3 2.3 Create a Composite Variable Composite variables are created in order to represent the characteristics of certain variables. The composite can be obtained through either taking the mean of responses or by taking a sum of all the variables. For the study, the composite variable was derived after taking the mean of the variables 8, 9 and 10. Please refer to Appendix ‘E’ for values of composite variable. Pearson correlation measures the degree to which all the variables are able to explain similar phenomenon (Murphy 1994). Any value which is less than 0.50 shows that there is a little correlation between the survey questions. For internal consistency of the composite variables by examining correlations, please refer Appendix ‘F’. The composite variable displays correlations with each individual variable greater than 0.50 for ethical 1, 2 and 3. Inter-item correlations between ethical 1, 2 and 3 are all greater than 0.30. Therefore, ethical 1, 2 and 3 all seemed to display adequate homogeneity. Principal Component Analysis is a statistical technique that shows the correlation between variables for large amounts of data (Joliffe 2002). PCA helps when the amount of data, being observed, is large. It aims to discover the trends that are unknown. The Eigenvalues measures the amount of variability accounted for by a particular variable. For internal consistency of the composite variable using principal components analysis, please see Appendix ‘F’. The criteria that only one Eigenvalue must be greater than 1 assures whether our data explains a common phenomenon is. Using this criterion three factors will be extracted (1, 2 and 3) (Kaiser 1960). In this case, only one component was extracted (with an eigenvalue = 2.974) and so by this criterion, it is assumed that items are homogenous (Manning & Munro 2007). Ethical 1 represents the concept in the most appropriate manner while Ethical 3 is on other side. The reliabilities of the composite variable, in this case, α = 0.870 represents a good level of reliability as explained by Cronbach’s alpha (Manning & Munro 2007). From the information shown above, it was found that all items were homogenous, and Chronbach’s alpha was acceptable. Process thus stops at Step 6. The composite variable is an average of the three research items that measure the ethical climate. The value was obtained after averaging the sum of the responses for items 8, 9 and 10. Items 8, 9 and 10, in the survey, measure the personal views of the respondent. The questions measure the individual’s Ethical barometer. Looking at reliability and validity, we find that rather than being distinct, they actually form a continuum (Trochim 2006). Assessment Item 2.4 2.4 Histograms and Box Plots This histogram for ethics shows that most of the data was around mean value 3.52 on a scale ranging from 0 to 6. Further, histogram is almost normal. Please refer Appendix ‘G’. The box plot for ethics provides summary in a graphical way. Here, median is represented by the horizontal line through the box in the bottom. Please refer Appendix ‘G’. Histogram for Loyalty shows that the measure scale is between 0 and 12. Most of respondents were score on 3, followed 2, and then 0 and 1. Furthermore, the histograms is positively skewness, therefore, it means that “mean is greater than median” and most respondents feel that loyalty is more oriented toward the employee. Please refer Appendix ‘G’. Box plot for Loyalty helps to examine and compare the central tendency and variability of one or more distributions and to identify any outliers. The location of the median, the height of the rectangular box, and length of the whiskers gives an overview of characteristics of variable Loyalty. Please refer Appendix ‘G’. Outliers are data observations that deviate from the other observations, which may give reasons to believe that they where produced through a separate mechanisms (Hawkins 1980). Cases with standardized scores with an absolute value in excess of 3.29 (p < 0.01) are identified as potential outliers (Manning & Munro 2007). In this case no value for ZEthics and Zloyalty was found in excess of 3.29. For values of ZEthics and ZLoyalty, please refer Appendix ‘H’. Tabachnick and Fidell (1997) described techniques to conduct a multivariate test. Using the data from the set of 10 variables, the Mahalanobis distance was estimated for each case. Any individual with a Mahalanobia distance score greater than 13.816 (D.F. =2, X2 = 13.816) would be a multivariate outlier. From data contained in MAH_1, it was found that the maximum score was 11.59823. Thus no Mahalanobis score greater than 13.816 was found; therefore, “no” multivariate outlier was identified (Manning & Munro 2007). Please refer Appendix ‘H’ for values of variable MAH_1. Assessment Item 2.5 2.5 Normality 2.5.1 Normality in Loyalty The distribution is positively skewed with a value of 0.744 and error of skew 0.241. Thus, the ratio of skewness to standard error of skewness is 0.744/0.241 = 3.087. Since the sample is less than 300; therefore, absolute value is 2.58. In this case the sample size was 100; the ratio of skew to standard error of skew is 3.087 greater than 2.58. Thus, loyalty variable “have significant level of skew” (Manning & Munro 2007). Please refer Appendix ‘I’. To further verify, Minitab 15.1 was used for normality test of variable Loyalty. The plot of the shows that the points do not fall close to the reference line, indicating that the data does not follow a normal distribution. The p-value for the Anderson-Darling normality test (bottom right) of the data is less than 0.005. This value is far less than the chosen a-level of 0.10, thus we will not reject H0 that there is enough evidence to suggest that the data do not follow a normal distribution. Please refer Appendix ‘I’ for more details. Based on above information, the scores were transformed. In this case, a square-root transformation was applied to produce a new variable (LoyaltySQRT). Following the same general procedures, ratio obtained by dividing the skewness to standard error of skewness is -2.6 (-0.627 / 0.241) smaller than 2.58, and value for both skew (-0.627, P > 0.001) and kurtosis (0.043, P > 0.001) of the transformed scores were “not significantly” different to those of a normal distribution. This transformed variable was used in all subsequent analysis to represent the concept of loyalty (Manning & Munro 2007). Please refer Appendix ‘I’ for more details. 2.5.2 Normality in Ethics The distribution is slightly negatively skewed with a value of -0.074. The error of skew is 0.241. Thus, -0.074/0.241 = -0.307. Again here the sample is less than 300 which represents that the absolute value is 2.58. In this case the sample size was 100; the ratio of skew to standard error of skew is -0.307, which is far smaller than 2.58 and so variable Ethics does not “have significant level of skew” (Manning & Munro 2007). Assessment Item 2.6 2.6.1 ANOVA in Ethics and Gender Linear Regression was conducted to ascertain the prediction of ethics outcomes by gender. Gender includes R= 0.13, R-Square= 0.000. The value for Finc is 0.017 with degrees of freedom 1 and 96 which is not significant at P > 0.05 (p=0.897). Therefore, males will not rate their own ability to achieve ethical outcomes more highly than will females do (Manning 2006). Please refer Appendix ‘J’ for details. 2.6.2 ANOVA in Ethics and OrgType Similarly, Linear Regression was again employed to establish the prediction of ethics outcomes by organization type which includes R= 0.307, R-Sqaure= 0.094. The value for Finc is 9.9 with degrees of freedom 1 and 96 which is significant at P < 0.05 (p=0.002). Therefore, people who are working in the public service will rate their own ability to achieve ethical outcomes more highly than will either those working in semi-government authorities or in the private sector (Manning 2006). Please refer Appendix ‘K’ for details. Assessment Item 2.7 2.7 The researcher believes there will be a negative correlation between the respondents’ rating of the degree to which the respondent feels that within their organization, loyalty to the organization is emphasized over loyalty to employees (Loyalty) and their perceived ability to achieve ethical outcomes (ethics) (Manning and Munro 2007). H1: Ethics (interval scale) affects employee perception of organization loyalty (interval) Here both Ethics and Employee perception of organization are measured on interval scales. A linear regression could be used, but this would result in a relationship equation between the two variables (Manning & Munro 2007). However, significant relationship between the two variables is the main concern; therefore, a correlation analysis is likely to serve the purpose (Manning & Munro 2007). Pearson r is a good measure for this purpose but it requires the distribution of both variables to be normal (Manning & Munro 2007). If either is not normal then Spearman rank order correlation would serve the purpose (Manning & Munro 2007). H2: Loyalty SQRT (interval scale) affects employee perception of organization loyalty (interval) Here both Loyalty SQRT and Employee perception of organization are measured on interval scales. A linear regression could be used, but this would result in a relationship equation between the two variables (Manning & Munro 2007). However, significant relationship between the two variables is the main concern; therefore, a correlation analysis is likely to serve the purpose (Manning & Munro 2007). Pearson r is a good measure for this purpose but it requires the distribution of both variables to be normal (Manning & Munro 2007). If either is not normal then Spearman rank order correlation would serve the purpose (Manning & Munro 2007). H3: Employee perception of organization loyalty (interval) affects Ethical outcome (ratio scale) Here the Employee perception of organization is on an interval scale and Ethical Outcome is measured on a ratio scale. A linear regression could be used, but this would result in a relationship equation between the two variables (Manning & Munro 2007). However, significant relationship between the two variables is the main concern; therefore, a correlation analysis is likely to serve the purpose (Manning & Munro 2007). Pearson r is a good measure for this purpose but it requires the distribution of both variables to be normal (Manning & Munro 2007). If either is not normal then Spearman rank order correlation would serve the purpose (Manning & Munro 2007). Assessment Item 2.8 2.8 Contingency Table Analysis The researcher believes that there will be a significant relationship between gender and organization type. Specifically that female will be more likely to work in public service HR, and males will be more likely to work in HR in private organizations (Manning & Munro 2007). Following hypotheses were designed to supplement this analysis Ho: There is a relationship that females will be more likely to work in HR in public service, and males will be more likely to work in HR in private organizations Hα: There is no relationship that females will be more likely to work in HR in public service, and males will be more likely to work in HR in private organizations There are 37 males and 60 females in this survey. 19 (52.8%) males and 35 (60.3%) females indicated their organization type to be part of the public service. 10 (27.8%) males and 16 (27.6%) females indicated that their organization type is a semi-government authority. 7 (19.4%) males and 7 (12.1%) females belonged to organization type which is private sector. Furthermore, as Chi-square test result shows that ( = 0.05) < (P-value = 0.579). Thus H0 at  = 0.05 is not rejected. Therefore, females will be more likely to work in HR in public service, and males will be more likely to work in HR in private organizations (Manning 2006). Conclusion This report has analyzed the eight assessment items described in the study guide by using applications in SPSS software. The SPSS technique were used in order to answer the problems of descriptive statistics, bivariate and multivariate statistics, histograms, box plots, normality tests, linear regression, ANOVA, Chi-Square hypothesis testing, and the prediction for identifying groups in factor analysis and discriminant. In this report, Harvard referencing style was followed to communicate in a clear, concise and persuasive manner. Read More

Among 100 participants, 15% were between 21 and 30 years, 26% between 31 to 40 years, 41% between 41 and 50 years, 16% were between 51 to 60 years, while rest two participants were over 60 years of age. Please refer Table 2 in Appendix ‘B’ attached to this report. For time in Human Resource, 9% were working in the HR field for less than 1 year, 6% were working in the HR field between 1 to 2 years, 14% were working in the HR field between 3 to 5 years, 27% were working in the HR field between 6 to 10 years, 44% were working in the HR field for more than 10 years.

Please refer Table 3 in Appendix ‘B’ attached to this report. For Time in Job, 27% were working in the present job for less than 1 year, 30% were working in the present job between 1 to 2 years, 27% were working in the present job between 3 to 5 years, 10% were working in the present job between 6 to 10 years, 6% were working in the present job for more than 10 years. Please refer Table 4 in Appendix ‘B’ attached to this report. Survey analysis for salary indicated that 10% had their current salary between $31,000 and $40,000 pa, 31% had their current salary between $41,000 and $55,000 pa, 40% had their current salary between $56,000 and $70,000 pa, 18% had their current salary between $76,000 and $100,000 pa.

1% had their current salary over $100,000 per annum. Please refer Table 5 in Appendix ‘B’ attached to this report. 57% indicated that their organization type was part of the public service, 26% organization type was a semi-government authority, and 14% organization type was private sector, while 3% failed to identify the type of their organization. Please refer Table 6 in Appendix ‘B’ attached to this report. 2.2.2 Descriptive Statistics for Mean and Standard Deviation Mean measures the average of all the values while the standard deviation measures the level of deviation, of values, from the computed mean.

The mean for Loyalty to Org is 3.07 with standard deviation of 2.212 and variance 4.894. The median is 3.0 and standard deviation of the difference between the estimated values and the true values is 0.241 (standard error). The mean for Ethical 1 is 3.50 with standard deviation of 1.403 and variance 1.970. The median is 3.0 and standard error is 0.241. The mean for Ethical 2 is 3.52 with standard deviation of 1.396 and variance 1.949. The median is 4.0 and standard error is 0.241. The mean for Ethical 3 is 3.

54 with standard deviation of 1.321 and variance 1.746. The median is 4.0 and standard error is 0.241. Please refer Table 1 in Appendix ‘C’ attached to this report for mean and standard deviation. 2.2.3 Descriptive Statistics Crosstabulations There were total of 37 males in the survey, of which 5 males (13.5%) were between 21 to 30 years of age, 8 males (21.6%) in age between 31 to 40 years, 15 (40.5%) males in age between 41 to 50 years, 8 males (21.6%) in age between 51 to 60 years, and 1 male (2.7%) was over 60 years of age.

There were 60 females in the survey, of which 10 females (16.7%) were between 21 to 30 years of age, 15 females (25.0%) in age between 31 to 40 years, 26 females (43.3%) in age between 41 to 50 years, 8 females (13.3%) in age between 51 to 60 years, and 1 female (1.7%) was over 60 years of age. Please refer Table 1 in Appendix ‘D’. 2 (5.4%) male and 6 (10.0%) females indicated they were working in HR field for less than 1 year. 2 (5.4%) males and 4 (6.7%) females indicated they were working in HR field between 1 to 2 years. 2 (5.4%) males and 11 (18.3%) females indicated they were working in HR field between 3 to 5 years. 13 (35.1%) males and 13 (21.7%) females indicated they were working in HR field between 6 to 10 years. 18 (48.6%) males and 26 (43.3%) females indicated they were working in HR field between 6 to 10 years.

Please refer Table 2 in Appendix ‘D’. 10 (27.0%) males and 16 (26.7%) females indicated they were working in the present job for a period of less than 1 year. 12 (32.

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