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ANOVA Test Application Analysis Research Paper

Geographical location

ANOVA analysis was undertaken to determine if there was any statistically significant difference between the selected geographical locations. It was assumed that a geographical location and the quality standards accepted within a specific environment may determine the engagement rates among the company’s staff. In other words, the living standards adopted for a certain region may defile the employees’ involvement with the organization and its success, thus, determining the staff member’s performance.

 Table 1. Descriptives Employment measure N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum Lower Bound Upper Bound A 9 .554444 .0777996 .0259332 .494642 .614247 .4300 .6800 B 11 .591818 .1560012 .0470361 .487015 .696621 .3200 .8300 C 10 .576000 .2889906 .0913868 .369269 .782731 .0000 1.0000 D 10 .604000 .1609141 .0508855 .488889 .719111 .2900 .8600 E 10 .696000 .1827688 .0577966 .565255 .826745 .4400 1.0000 F 10 .693000 .1922412 .0607920 .555479 .830521 .3300 1.0000 Total 60 .619833 .1882164 .0242986 .571212 .668455 .0000 1.0000

As Table 1 shows, the difference between the geographical locations in question is, in fact, rather small. The insignificant differences in the value of the standard deviation show rather graphically that the respondents’ assessments of employee engagement based on geographical location were not polarized. Instead, the estimation of the link between the geographical location and the enthusiasm of the staff was rather even in most cases. Hence, it can be assumed that geographical location does not seem to play a significant role in the rates of employees’ engagement. As the confidence interval for the mean peaks at 95%, the results of the assessment can be considered credible, since most of the samples hold value to the population parameter. Therefore, the geographical location can be viewed as slightly insignificant for determining employee engagement.

 Table 2. ANOVA Employment measure Sum of Squares df Mean Square F Sig. Between Groups .180 5 .036 1.020 .415 Within Groups 1.910 54 .035 Total 2.090 59

The above results indicate that the p-value is greater than 0.05 and this implies that the null hypothesis cannot be rejected at 0.05 level of significance. In this case, the null hypothesis is that there is no mean variation of employment engagement between the 6 geographical locations selected. In other words, statistically, the comparatively low score of the p-value allows for proving the statement provided above, i.e., the insignificance of geographic location as the factor contributing to the level of employee engagement in the working process. The lack of difference in the mean square of the values between and within groups also indicates that most of the respondents were positively certain about the lack of importance of the geographical location when it came to their work. The null hypothesis, hence, cannot be rejected, which means that the commitment of the staff does not depend on the geographical location thereof.

Gender

Independent sample t-test was undertaken to determine if there is a statistically significant difference between the males and females selected. The issue of gender differences in the workplace is, perhaps, one of the most controversial aspects of the test, as there are a range of problems in the field under analysis from social and cultural perspectives. Due to the lack of equity among the male and female employees, there may be a drastic difference in the engagement rates between the two groups specified.

 Table 3. Group Statistics Gender N Mean Std. Deviation Std. Error Mean Employment measure 2 Male 10 .6030 .07861 .02486 Female 10 .5510 .10038 .03174

As expected, the mean of employee engagement is somewhat lower among the women that have been sampled from the target population than it is among men; while the difference is comparatively small, reaching 0.520, it should still be deemed as significant and, therefore, explored in a more detailed manner. The difference in standard deviation rates among the target denizens of the Saudi Arabian population (0.02177) also indicates that the responses of the female participants were more homogenous than the ones of the male interviewees. The specified detail indicates that the rates of staff satisfaction and engagement in the working process depend significantly on gender.

 Table 4. Independent Samples Test Levene’s Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Employment measure 2 Equal variances assumed .782 .388 1.290 18 .213 .05200 .04032 -.03271 .13671 Equal variances not assumed 1.290 17.021 .214 .05200 .04032 -.03306 .13706

Based on the above results, it is observed that the p-value (0.23) is less than 0.05 is greater than 0.05. This means that the null hypothesis cannot be rejected at 0.05 level of significance. The null hypothesis is that there is no statistically significant difference in means of the mean employment engagement measure between males and females selected.

Therefore, the supposition concerning the gender issues, which may be the key impediment to employee engagement rates among the Saudi Arabian population can be considered proven wrong. While the group statistics data indicated that there could have been a slight misbalance between male and female denizens of the Saudi Arabian population in terms of the engagement in the working process, the deviation is far too small to claim that it has a tangible effect on the outcomes of the test Moreover, the fact that the p-value is less than 0.5 indicates that the null hypothesis has a rather high veracity rate; therefore, the null hypothesis, which states that there is no major difference between the engagement rates of the Saudi Arabian employees depending on their gender.

Age

One way ANOVA was undertaken to determine if there is a statistically significant difference in the mean employment engagement measure between the age groups. It is quite obvious that age plays a major role in employee engagement rates, as the differences in the ability to process information and accomplish tasks.

 Table 5. Descriptive Employment measure 3 N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum Lower Bound Upper Bound A 10 .5230 .12579 .03978 .4330 .6130 .29 .67 B 10 .5700 .08907 .02817 .5063 .6337 .41 .69 C 10 .6230 .07439 .02353 .5698 .6762 .48 .74 D 10 .6680 .09931 .03140 .5970 .7390 .47 .81 E 10 .7000 .28382 .08975 .4970 .9030 .25 1.00 Total 50 .6168 .16182 .02288 .5708 .6628 .25 1.00

The descriptive analysis of the data provided has shown that there is a minor difference between the results shown by different age groups. The mean ranging from.5230 to.7000, there are solid reasons to assume that engagement rates among the staff depend slightly on the age of an employee. More importantly, the minimum and the maximum indices also vary to a considerable extent, the lowest data reaching.25, whereas the highest marks landing at 1.00. In other words, there could be an indication that the Saudi Arabian employees belonging to different age groups display different rates of engagement in the working process. The specified phenomenon can be explained with the help of the shift in values that occurs as the staff members get older and gain more experience. The reassessment of their key priorities leads to them outing a stronger emphasis on family and the relationships with their family members. Consequently, the significance of excelling in the workplace performance, as well as the rats of engagement in the professional routine, becomes increasingly low.

 Table 6. ANOVA Employment measure 3 Sum of Squares df Mean Square F Sig. Between Groups .206 4 .051 2.148 .090 Within Groups 1.077 45 .024 Total 1.283 49

It is observed in the above results that the p-value (0.09) is greater than 0.05. Therefore, the null hypothesis cannot be rejected at the 0.05 level of significance and conclude that there is no statistically significant difference or variation between the age groups considered in the study. In this case, the null hypothesis is that there is no statistically significant variation or difference in the mean employment engagement measure between the age groups considered in the study. Therefore, it can be assumed that the supposition concerning the alterations in the staff’s perception of their duties, as well as the rates of their engagement in their work, do not depend on their age for the most part. The specified conclusion, therefore, allows assuming that the strategies for enhancing employee engagement in most Saudi Arabian entrepreneurship may be carried out without taking the age factor into account. Instead, other variables should be viewed as the area of interest and thus reinforced. Specifically, the influence of position on the rates of employee engagement deserves to be analyzed.

Position

One way that ANOVA was carried out was to determine if there is a statistically significant difference or variation in the mean employment engagement measure between the employment positions. The factor in question presumably has a major significance in defining the rates of engagement among the staff. Indeed, the above-mentioned parameter defines the arrangement of incentives, which the company may provide for the staff; therefore, it can be assumed that the factor may contribute to the increase in engagement rates considerably.

 Table 7. Descriptives Employment measure 4 N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum Lower Bound Upper Bound A 10 .4510 .17654 .05583 .3247 .5773 .17 .67 B 10 .6340 .24757 .07829 .4569 .8111 .33 1.00 C 10 .5750 .23717 .07500 .4053 .7447 .25 1.00 D 10 .3650 .19069 .06030 .2286 .5014 .13 .63 5.00 10 .5850 .09168 .02899 .5194 .6506 .43 .69 E 10 .6400 .07542 .02385 .5860 .6940 .50 .77 F 10 .6000 .09989 .03159 .5285 .6715 .44 .74 Total 70 .5500 .19102 .02283 .5045 .5955 .13 1.00

A closer look at the descriptive will reveal that the standard deviation among the respondents is rather low; the standard error, in its turn, is quite high. Thus, it can be assumed that the responses provided by the interviewed were homogenous for the most part.

 Table 8. ANOVA Employment measure 4 Sum of Squares df Mean Square F Sig. Between Groups .635 6 .106 3.544 .004 Within Groups 1.882 63 .030 Total 2.518 69

The above analysis results show that the p-value is less than 0.05 and this means that the null hypothesis is to be rejected at 0.05 level of significance. It can, therefore, be concluded that there is a variation between the age groups, but this analysis cannot indicate which groups exhibit the variation since we have more than two groups. Therefore post hoc test was undertaken as indicated in the next section. The post hoc results indicate that there is statistically significant variation between the groups that include A and D; B and C; D and E as well as between D and F.

 Table 9. Multiple Comparisons Dependent Variable: Employment measure 4 Turkey HSD (I) Position (J) Position Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound A B -.18300 .07730 .230 -.4184 .0524 C -.12400 .07730 .680 -.3594 .1114 D .08600 .07730 .922 -.1494 .3214 5.00 -.13400 .07730 .597 -.3694 .1014 E -.18900 .07730 .198 -.4244 .0464 F -.14900 .07730 .470 -.3844 .0864 B A .18300 .07730 .230 -.0524 .4184 C .05900 .07730 .988 -.1764 .2944 D .26900* .07730 .015 .0336 .5044 5.00 .04900 .07730 .995 -.1864 .2844 E -.00600 .07730 1.000 -.2414 .2294 F .03400 .07730 .999 -.2014 .2694 C A .12400 .07730 .680 -.1114 .3594 B -.05900 .07730 .988 -.2944 .1764 D .21000 .07730 .111 -.0254 .4454 5.00 -.01000 .07730 1.000 -.2454 .2254 E -.06500 .07730 .980 -.3004 .1704 F -.02500 .07730 1.000 -.2604 .2104 D A -.08600 .07730 .922 -.3214 .1494 B -.26900* .07730 .015 -.5044 -.0336 C -.21000 .07730 .111 -.4454 .0254 5.00 -.22000 .07730 .082 -.4554 .0154 E -.27500* .07730 .012 -.5104 -.0396 F -.23500 .07730 .051 -.4704 .0004 5.00 A .13400 .07730 .597 -.1014 .3694 B -.04900 .07730 .995 -.2844 .1864 C .01000 .07730 1.000 -.2254 .2454 D .22000 .07730 .082 -.0154 .4554 E -.05500 .07730 .991 -.2904 .1804 F -.01500 .07730 1.000 -.2504 .2204 E A .18900 .07730 .198 -.0464 .4244 B .00600 .07730 1.000 -.2294 .2414 C .06500 .07730 .980 -.1704 .3004 D .27500* .07730 .012 .0396 .5104 5.00 .05500 .07730 .991 -.1804 .2904 F .04000 .07730 .999 -.1954 .2754 F A .14900 .07730 .470 -.0864 .3844 B -.03400 .07730 .999 -.2694 .2014 C .02500 .07730 1.000 -.2104 .2604 D .23500 .07730 .051 -.0004 .4704 5.00 .01500 .07730 1.000 -.2204 .2504 E -.04000 .07730 .999 -.2754 .1954 *. The mean difference is significant at the 0.05 level.

The multiple comparisons of the data provided in Table 9 show that there are very few factors that contribute to the alterations in the employee engagement level. Specifically, the age, the gender, and the geographical location of the staff members do not seem to impact the engagement rates of the latter in the slightest. The specified phenomenon can be explained by the fact that the Saudi Arabian employees value their jobs too high to change their performance based on the environmental or personal factors that they are exposed to. The fact that the staff’s engagement appears to be dependent on the position that they occupy, in its turn, is also rather logical, as the position often defines the staff’s salary and, thus, is considered one of the key reasons for delivering excellent performance in the organizational setting.

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"ANOVA Test Application Analysis." IvyPanda, 12 July 2020, ivypanda.com/essays/anova-test-application-analysis/.

1. IvyPanda. "ANOVA Test Application Analysis." July 12, 2020. https://ivypanda.com/essays/anova-test-application-analysis/.

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IvyPanda. "ANOVA Test Application Analysis." July 12, 2020. https://ivypanda.com/essays/anova-test-application-analysis/.

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IvyPanda. 2020. "ANOVA Test Application Analysis." July 12, 2020. https://ivypanda.com/essays/anova-test-application-analysis/.

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IvyPanda. (2020) 'ANOVA Test Application Analysis'. 12 July.