The Responses of People Based on Whether They Are in Favor or against Britain Having Nuclear Weapon - Research Paper Example

 Quantitative Report Introduction Being in favor or against Britain having its own nuclear weapons topic has been a topic of interest in different aspect (Jacques, 2000). There is a lot of division regarding public opinion on nuclear weapons as well as choices based on replacement of Trident (Chatham House, 2010). Since the year 2005, it can be noted that at least 20 opinion polls have been undertaken at the moment Trident replacement debate had picked up (Chatham House, 2010).The main objective of the survey or study is to explore the responses of people based on whether they are in favor or against Britain having its own nuclear weapons. In this case, Chi squared was used to analyze the data, ‘British Social Attitudes (BSA) survey series’ which was collected by National Centre for Social Research (Park et al., 2014; Stafford and Thomson, 2006). It was designed to generate attitude movement measures (Park et al., 2014; Jowell et al., 1992) .The dependent variable considered in this case is “are you in favor or against Britain having its own nuclear weapons?” .The independent variable considered is sex or gender. In this case different people respond differently and it was critical to know if gender is relatively associated with opinion on having the nuclear weapons. Therefore, there were 2 nominal variables that include gender and opinion on nuclear possession. In the survey, the options of response for most questions are on the scale of 5 point (use of five point Likert scale) (DeVellis, 2003; Spector, 1992), that is, from strongly in favor to strongly against, this also include ‘I don’t know’ Frequency Tables and Confidence Tables The table below includes the frequency table for the question responses whether people are in favor or against Britain having its own nuclear weapons. Somewhat in favor is observed to be the largest group with 8.2 percent but it is seen not to be much higher when compared with the next group of strongly against with 7.6 percent. I don’t know group has the smallest percentage of 1 while strongly in favor and neither in favor or against both have 5.8 percent. When the categories are collapsed to in favor and against, the percentage is 14 percent and 12.1 percent respectively. The confidence interval is 3.14 ± 0.31 Statistics Are you in favour or against Britain having its own nuclear weapons? :Q445 N Valid 2879 Missing 5872 Are you in favour or against Britain having its own nuclear weapons? :Q445 Frequency Percent Valid Percent Cumulative Percent Valid Strongly in favour 509 5.8 17.7 17.7 Somewhat in favour 720 8.2 25.0 42.7 Neither in favour nor against 510 5.8 17.7 60.4 Somewhat against 391 4.5 13.6 74.0 Strongly against 662 7.6 23.0 97.0 Don't know 87 1.0 3.0 100.0 Total 2879 32.9 100.0 Missing version off route 5872 67.1 Total 8751 100.0 Analysis The crosstabulation table below enables us to understand that majority of females are strongly against nuclear possession while males are strongly in favor. The Crosstabulation Table Person 1 SEX :Q54 * Are you in favour or against Britain having its own nuclear weapons? :Q445 Crosstabulation Are you in favour or against Britain having its own nuclear weapons? :Q445 Total Strongly in favour Somewhat in favour Neither in favour nor against Somewhat against Strongly against Don't know Person 1 SEX :Q54 Male Count 366 366 187 152 238 30 1339 % within Person 1 SEX :Q54 27.3% 27.3% 14.0% 11.4% 17.8% 2.2% 100.0% % within Are you in favour or against Britain having its own nuclear weapons? :Q445 71.9% 50.8% 36.7% 38.9% 36.0% 34.5% 46.5% % of Total 12.7% 12.7% 6.5% 5.3% 8.3% 1.0% 46.5% Female Count 143 354 323 239 424 57 1540 % within Person 1 SEX :Q54 9.3% 23.0% 21.0% 15.5% 27.5% 3.7% 100.0% % within Are you in favour or against Britain having its own nuclear weapons? :Q445 28.1% 49.2% 63.3% 61.1% 64.0% 65.5% 53.5% % of Total 5.0% 12.3% 11.2% 8.3% 14.7% 2.0% 53.5% Total Count 509 720 510 391 662 87 2879 % within Person 1 SEX :Q54 17.7% 25.0% 17.7% 13.6% 23.0% 3.0% 100.0% % within Are you in favour or against Britain having its own nuclear weapons? :Q445 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% % of Total 17.7% 25.0% 17.7% 13.6% 23.0% 3.0% 100.0% Basing on Chi –Square Tests Table below, the Pearson Chi-square row results are of major concern. It is observed that the p value is less than 0.05 and it implies that there is statistically significant association between the opinion on nuclear weapon possession and gender. Hence, males and males have different response on nuclear weapon possession. Chi –Square Tests Table Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 201.111a 5 .000 Likelihood Ratio 204.968 5 .000 Linear-by-Linear Association 132.950 1 .000 N of Valid Cases 2879 a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 40.46. It is known that the strength of association is determined by Phi and Cramer’s V tests. Basing on the symmetric measures table, it is observed that the association strength between the given variables is strong and significant Symmetric Measures Table Symmetric Measures Value Approx. Sig. Nominal by Nominal Phi .264 .000 Cramer's V .264 .000 N of Valid Cases 2879 a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis. Conclusion In conclusion, according to the findings, it can be noted that females are strongly against Britain having its own nuclear weapons. While on the other hand, males are strongly in favor of Britain having its own nuclear weapons. The study also focused on determining the association between gender and opinion on nuclear possession and this included measuring the strength of association as well as testing if this association is statistically significant. The results showed that there is statistically significant association between the gender and nuclear weapon possession opinion. The results also indicated that there is strong association between the gender and nuclear weapon possession opinion Part 2 The study majorly focuses on determining the association of two explanatory variables (improved sanitation facility and total health expenditure) and the dependent variable that include mortality rate under 5.Correlation analysis and regression analysis were both used to determine this association. Correlation analysis was done on both explanatory variable and regression analysis was done on explanatory variable that had the strongest association with the dependent variable. The two explanatory variables selected include improved sanitation facility and total health expenditure. Total health expenditure it is the sum of the private and health expenditures in terms of the total population ratio. The health service provisions of nutrition activities, family planning, curative and preventive and emergency aid are covered (WHO/UNICEF, 2014). It is also important to note that there is conversion of the data that is in international dollars with the use of purchasing power parity rates (World Bank 2014). Improved sanitation facility accession refers to the population’s percentage that use improved sanitation facility (Collignon, 2000). The facilities include flush composite toilet, pit latrine, ventilated improved pit latrine (Sulabh International, 2001; Alabaster, 2003). The dependent variable selected was mortality rate under 5. Mortality rate under 5 can be defined as the probability that a newborn baby will die per 1000 before he/she reaches five years. Histograms and summary statistics Summary statistics table Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Health expenditure per capita, PPP (constant 2005 international $) 132 88.0% 18 12.0% 150 100.0% Improved sanitation facilities (% of population with access) 132 88.0% 18 12.0% 150 100.0% Mortality rate, under-5 (per 1,000 live births) 132 88.0% 18 12.0% 150 100.0% Basing on the descriptive table below, it is observed that the mean is 1156, 71 and 33 for health expenditure, improved sanitation and mortality rate under 5 respectively. Descriptive Table Statistic Std. Error Health expenditure per capita, PPP (constant 2005 international $) Mean 1156.3258 137.71694 Median 481.5000 Variance 2503505.992 Std. Deviation 1582.24713 Improved sanitation facilities (% of population with access) Mean 71.6061 2.63308 Median 84.5000 Variance 915.172 Std. Deviation 30.25181 Mortality rate, under-5 (per 1,000 live births) Mean 33.4924 2.86442 Median 18.5000 Variance 1083.046 Std. Deviation 32.90966 Health expenditure per capita, PPP (constant 2005 international $) Histogram Basing on the above histogram, it is observed that expenditure below 2000 is the one with highest frequency. Improved sanitation facilities (% of population with access) histogram According to the histogram above, it can be noted that about 90-100 percent of the population have the highest frequency of improved sanitation facility accession. Mortality rate, under-5 (per 1,000 live births)Histogram According to the above histogram, it is observed that mortality rate under 5 below 50 has the highest frequency Analysis Scatter plots Mortality rate, under-5 against health expenditure scatter plot Mortality rate, under-5 against improved sanitation facilities scatter plot Basing on the above scatter plots, it is clearly evident that the relationship between improved sanitation and health expenditure facilities and Mortality rate, under-5 is linear. Correlations Correlation of mortality rate with improved sanitation facilities table Correlations Mortality rate, under-5 (per 1,000 live births) Improved sanitation facilities (% of population with access) Mortality rate, under-5 (per 1,000 live births) Pearson Correlation 1 -.861** Sig. (2-tailed) .000 N 150 137 Improved sanitation facilities (% of population with access) Pearson Correlation -.861** 1 Sig. (2-tailed) .000 N 137 137 **. Correlation is significant at the 0.01 level (2-tailed). Correlation of mortality rate with health expenditure table Correlations Mortality rate, under-5 (per 1,000 live births) Health expenditure per capita, PPP (constant 2005 international $) Mortality rate, under-5 (per 1,000 live births) Pearson Correlation 1 -.517** Sig. (2-tailed) .000 N 150 142 Health expenditure per capita, PPP (constant 2005 international $) Pearson Correlation -.517** 1 Sig. (2-tailed) .000 N 142 142 **. Correlation is significant at the 0.01 level (2-tailed). According to the two correlation analysis tables above, it is observed that there is a negative strong correlation. The correlation between mortality rate and improved sanitation facilities is -0.861 while the correlation between mortality rate and health expenditure per capita is -0.517.Basing on these results, it is clearly evident that the correlation (-0.861 ) between mortality rate and improved sanitation facilities was the highest when compared with correlation (-0.517) between mortality rate and health expenditure per capita. Therefore, the variable improved sanitation facilities was considered in regression analysis as shown in the next section Regression Analysis Regression model Summary Table Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change 1 .861a .741 .739 16.75157 .741 385.485 1 135 .000 a. Predictors: (Constant), Improved sanitation facilities (% of population with access) According to the model summary table above, it is observed that the R squared is 0.741 and this implies that improved sanitation facilities as the independent variable in the model accounts for 74 percent of the variation in the given percent of the access ANOVA table ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 108173.002 1 108173.002 385.485 .000b Residual 37883.027 135 280.615 Total 146056.029 136 a. Dependent Variable: Mortality rate, under-5 (per 1,000 live births) b. Predictors: (Constant), Improved sanitation facilities (% of population with access) The ANOVA table above clearly means that the significant statistics of the model for the F test shows that there is no chance for the correlation observed between mortality rate and improved sanitation facility is as a result of random sampling error. Regression model Estimates Table Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. 95.0% Confidence Interval for B B Std. Error Beta Lower Bound Upper Bound 1 (Constant) 101.009 3.726 27.107 .000 93.640 108.379 Improved sanitation facilities (% of population with access) -.938 .048 -.861 -19.634 .000 -1.033 -.844 a. Dependent Variable: Mortality rate, under-5 (per 1,000 live births) In regards to the above table, it can be noted that every increase in improved sanitation facilities was related to about 0.8 decreases in the mortality rate under 5.The partial correlation between improved sanitation facilities and mortality rate under 5 is not due to random sampling error. Conclusion In conclusion, it can be noted that improved health facilities influences negatively the most the mortality rate under 5 than health expenditure per capita. Therefore, this variable could be considered in the addressing problems related to mortality rates under five. However, health expenditure per capita should not be ruled out as well because it also had a strong association to mortality rate under 5.It should be considered as important but improved health facilities should be the preferred variable. The study objective was met and in can be noted that there is a strong significant association of both improved health facilities and health expenditure per capita with mortality rate under 5 References Jacques E. C.Hymans, 2000 “Isotopes and Identity: Australia and the Nuclear Weapons Option, 1949-1999”, Nonproliferation Review, Vol.7, No.1, Spring, pp.1-23 Park, A., Bryson, C. and Curtice, J. (eds.) (2014), British Social Attitudes: the 31st Report, London: NatCen Social Research, available online at: www.bsa-31.natcen.ac.uk WHO/UNICEF.(2014). Joint Monitoring Programme (JMP) for Water Supply and Sanitation (http://www.wssinfo.org/). Catalog Sources World Development Indicators Sulabh International .(2001). Evaluating rural latrines in Guinea. Retrieved from www. sulabhinternational.org. Waterfront, 15:17–20 Collignon B, Vezina M (2000). Independent water and sanitation providers in African cities: full report of a ten-country study. Nairobi, Water and Sanitation Program-Africa Region Alabaster G, Issaias I. (2003). Case studies: removing human waste – the Vacutug solution. Habitat Debate, September 9(3):1 DeVellis, R.F. (2003), Scale Development: Theory and Applications, 2nd edition, Applied Social Research Methods Series, 26, Thousand Oaks, Calif.: Sage Jowell, R., Brook, L., Prior, G. and Taylor, B. (1992), British Social Attitudes: the 9th Report, Aldershot: Dartmouth Spector, P.E. (1992), Summated Rating Scale Construction: An Introduction, Quantitative Applications in the Social Sciences, 82, Newbury Park, Calif.: Sage Stafford, R. and Thomson, K. (2006), British Social Attitudes and Young People’s Social Attitudes surveys 2003: Technical Report, London: NatCen Social Research Chatham House. (2010). 2481 British adults + 877 British ‘opinion formers’http://www.chathamhouse.org/sites/default/files/public/Research/Europe/0710ch_yougov_survey.pdf World Bank (2014) Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org. Read More