Sample Essay on Relationship between Purpose of Study and Data Analysis Techniques

The data will be analyzed using the following inferential statistics: One Sample Hypothesis test, confidence interval, Chi Square Statistics, T-test, Pearson correlation, and Multi-variant Regression. Multi-variant regression will assess the responses of the participants of the program before and after undergoing the tests. Similarly, the multi-variant regression will be used to study if the program had on aspects such as anger and self-esteem of the participants involve (Bailey & Gatrell, 2005). A confidence interval of 95 % will be used in all the inferential statistics calculation involving the data presented. Chi Square statistic will assess whether the age of the women had any effect on their responses to the program (Mantel & Haenszel, 2009). T-tests will be used to compare the scores of emotional changes amongst women aged 30-35 and those aged 40-46. Additionally, all the measures of central tendencies will be included in final report of the calculation of inferential statistics.

Each type of inferential statistic is significant in making statistical conclusion regarding the data. The multi-variant regression will indicate whether the program improved the lives of the women by equipping them with sufficient social skills. The confidence level chosen will to determine the level of accuracy of all the statistical conclusions made. Chi-square will reveal the women’s age groups that is most acted by social problems and how they respond to them. T-test will give the age bracket of women that are most affected by the social problems studied. The measures of central tendencies will reveal the most prevalent social problem affecting the women (Strauss & Corbin, 2010). When all these conclusions have been made, a social worker can the focus one problem. For instance, the social worker can choose the address the social problem affecting women of certain age bracket.

 

References

Bailey, T. C., & Gatrell, A. C. (2005). Interactive spatial data analysis (Vol. 413). Essex:

Longman Scientific & Technical.

Mantel, N., & Haenszel, W. (2009). Statistical aspects of the analysis of data from retrospective

studies. J Natl Cancer Inst. 22(4), 719-748.

Strauss, A., & Corbin, J. (2010). Basics of qualitative research (Vol. 15). Newbury Park, CA:

Sage.