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1. QUESTION

Title:     Quantitative Reasoning and Analysis for Psychology

Paper Details

I do not know how to send the Afrobarometer dataset from the SPSS software but you all were able to complete another assignment for me using someone else’s access – I hope you can do the same this time!

Please see attached instructions (with links embedded for some of the resources) and a copy of skill builders for reference.  The variables that I used in previous assignments were:  Region of Africa, Participant Age and Country By Region

Subject Pages Style Psychology 3 APA

Introduction to Qualitative Analysis: Confidence Intervals

Confidence Interval

A confidence interval is a statistic that shows a margin of error of a given variable. It shows how confident the researcher is on using the stated mean or proportion lies within the true value of the population.

This assignment uses data from Afro-barometer Dataset to calculate the confidence interval of a number of variables namely, Region of Africa, Participant Age, and Country by Region.  Using SPSS, the data set is opened and the confidence interval for the stated variables computed at 95% Confidence interval.

The results of the analysis show that participants’ age confidence interval is (40.70, 41.78). This shows that there is a good chance, that is to say 95% of the times in the long run and with many samples that the parameter (Participants age) is in the interval. Additionally, the results of the analysis show that West Africa’s confidence interval is (0.33, 0.34). This shows that there is a good chance, that is to say 95% of the times in the long run and when many samples are used in the computation of the proportion that parameter (Participants from West Africa) is in the interval. The results of the analysis also show that East Africa’s confidence interval is (0.15, 0.16) as shown in Table 1. This shows that there is a good chance, 95% of the times that the parameter (Participants from East Africa) is in the interval when the computation is repeated with many samples (Bland, 2015; Farnsworth, 2016)

The results of the analysis also show that Southern Africa’s confidence interval is (0.33, 0.34). This shows that there is a good chance, 95% of the times in the long run and with many samples that the parameter (Participants from Southern Africa) is in the interval. In addition, the results of the analysis show that North Africa’s confidence interval is (0.112, 0.114) This shows that 95% of the times in the long run and with many samples that the parameter of the population proportion (Participants from North Africa) is in the interval (Field, 2013; Bonett and Wright, 2015). The results of the analysis also show that Central Africa’s confidence interval is (0.06, 0.07) (Table 1). This shows that there is a good chance, 95% of the times in the long run and with many samples that the parameter (Participants from Central Africa) is in the interval.

Table 1: Confidence Intervals Participant Age and Country by Region

 t df Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Difference Lower Upper COUNTRY.BY.REGION = West Africa 164.289 53934 .000 .334 .33 .34 COUNTRY.BY.REGION = East Africa 99.627 53934 .000 .155 .15 .16 COUNTRY.BY.REGION = Southern Africa 164.289 53934 .000 .334 .33 .34 COUNTRY.BY.REGION = North Africa 82.148 53934 .000 .111 .11 .11 COUNTRY.BY.REGION = Central Africa 61.886 53934 .000 .066 .06 .07 Participants Age 150.130 53934 .000 41.246 40.71 41.78

Source: Computation from the Afro-barometer data

Implications for Social Change

Over time, there are changes observed in patterns of behavior and cultural values and norms. Thus, every research is known to have a profound social change if data collected is intended to capture differences in the behavioral and cultural variables. Data from Afrobarometer covers the African region. The results in the table above imply that the age of the participants in the afro-barometer studies focusses on the population that is in its prime age of about forty years who have an essential role to play in society as key decision makers and thus able to make important social changes. In addition, the data shows that West Africa and Southern Africa had the highest participants, thus this data will possibly have a greater application in the two regions and other regions with similar demographics. Central Africa had the lowest number of participants in the whole data set.

### References

 Bland, M. (2015). An introduction to medical statistics. Oxford University Press (UK). Farnsworth, D. L. (2016). Confidence intervals instead of hypothesis tests. Mathematics and Computer Education, 50(2), 130. Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage. Bonett, D. G., & Wright, T. A. (2015). Cronbach’s alpha reliability: Interval estimation,     hypothesis testing, and sample size planning. Journal of Organizational Behavior, 36(1),     3-15.