# SPSS Output

SPSSOutput Summary

SPSSOutput Summary

Thereading and math tests results for the 86 employees of the companywill be quite crucial in showing the employees are well competent inhandling the various activities that they have been assigned. Theresults are also vital in establishing whether there is a significantdifference between the males and females in the company as it regardsto their reading and math capability.

Thestudy focuses on the following research questions

Dowomen and men have comparable reading skills?

Dowomen and men have comparable math skills?

Hypotheses

H0-Women and men do not have comparable reading skills.

H1-Women and men have comparable reading skills

H0-Women and men do not have comparable math skills?

H1-Women and men have comparable math skills?

Variables

Thetest was based on various variables. These were as follows

Theindependent variable was sex. It has a discrete attribute in that anindividual is either male or female. It is categorical in nature, andit has a nominal scale (Robinson, McCarthy, &amp Smyth, 2010). Thedependent variables were reading performance and math performance.Both of them have continuous attributes in that they vary in a givenlevel. They are quantitative in nature in that the performances aremeasured by given statistical values. The scale of measurement forthese variables is intervals.

Descriptivestatistics

Statisticsshow that the mean of the reading scores of all the people who tookpart in the test was 23.733 while the mean for the math score was23.419. This shows that the employees performed better in the readingtest compared to the math test. The results also indicate that themean for the females in the reading test is 24.209 with a standarddeviation of 6.0575 while that of the males was 23.256 with astandard deviation of 5.2739. This clearly shows that the femalesperform quite better in the reading test compared to men. The meanfor the math performance in the test among the females was 22.814with a standard deviation of 4.5 compared to that of males which was24.023 with a standard deviation of 4.728. These results show thatmales perform better in the math test compared to females.

Numberof individuals who participated in the study

Therewere 86 individuals who participated in the study.

Howthe measures of central tendency and variability provide us with anoverview of the characteristics and shape of the distribution of eachvariable

Thelevel of performance of the employees on the reading test was bettercompared to the math test, given that the mean for the reading testwas 23.733 while that of the math test was 23.419. However, themedium value of performance in the math score (24) was highercompared to that of the reading score (Robinson et al., 2010). Also,the mode for the math score (24) was much better compared to that ofthe reading score.

Whilethe mean performance (24.209) of the females in the reading testshowed that they were better compared to the males who had a meanperformance of 23.733, there median and mode performance also help toshow that they were better in that test compared to the males. Themedian was 23 compared to that of the males which was also 23.000while the mode was 23 compared to the mode of the males which was21.0 (Sukal, 2013). The Mean performance of the males in the mathtest was higher compared to that of the females at 22.814. The medianscores for the males were the same as that of the females which was24. The mode performance of the males was also the same as that ofthe females, which was 24. This point towards the fact that the malesperformed better in the math test compared to the females.

Anoverview of the results of the ANOVA

Theresults of the ANOVA test for achievement showed that the calculatedvalue (0.017) was less than the tabulated value (0.895)

Typeof ANOVA conducted

Thetype of ANOVA conducted is the one-way ANOVA because the test onlydealt with one independent variable (sex).

One-tailedor two-tailed test

Thisis a two-tailed test because it tests whether there is a differencebetween the males and females in the reading and math capability.This difference could either be in terms of the males having betterperformance or the females having a better performance.

Shoulda posthoc test have been conducted? Why or why not? If so, what werethe results of this test?

Thecalculated value is less than the tabulated value. Therefore, wereject the null hypothesis and state that there is a significantdifference between the males and females in the company as it regardsto their reading and math capability (Hair, 2009). There is,therefore, no need for a posthoc test because the desired outcome hasbeen achieved.

Howthe interaction can be interpreted

Theinteraction of the males and females based on the statistical resultsand interaction graph can be interpreted to be that males areperforming better compared to the females.Whatdo the results tell us about our hypotheses?

Theresults show that the null hypotheses can be rejected, and we adoptthe alternative hypotheses.Whatconclusions can we draw from these results? What conclusions can weNOT make using these results?

Oneof the conclusions that we can make from the results is that thegeneral performance in the reading test is better than theperformance in the math test. Another conclusion is that malesperform better than the females in the math tests and females performbetter in the reading test compared to the males (Robinson et al.,2010). There is, therefore, a significant difference between themales and females in the company as it regards to their reading andmath capability.

Whatissues regarding how the data was collected, either in relation toethics or research design, should be considered in the interpretationof the data?

Someof these issues include the need to safeguard the identity of theparticipants.

References

Hair,J. F. (2009). Multivariate data analysis.

Robinson,M. D., McCarthy, D. J., &amp Smyth, G. K. (2010). edgeR: aBioconductor package for differential expression analysis of digitalgene expression data.&nbspBioinformatics,&nbsp26(1),139-140.

Sukal,M. (2013). Research methods: Applying statistics in research. SanDiego, CA: Bridgepoint Education, Inc.