Descriptive Statistics Sample Clauses

Descriptive Statistics. Our analysis focuses on the two main types on NTMs adopted by TTIP and TPP countries that affect trade flows, namely the SPS and TBT measures. We use the notifications made by these countries to the WTO.8 Each notification provides information on the notifying 8These notifications are used by the WTO in its 2012 World Trade Report (WTO, 2012) and are avail- able via the Integrated Trade Intelligence Portal (I-TIP) (▇▇▇▇://▇▇▇.▇▇▇.▇▇▇/english/res_e/statis_e/ itip_e.htm). Product codes are often missing from the I-TIP database and were added at the HS 4-digit level by the Centre for WTO Studies of the Indian Institute of Foreign Trade (▇▇▇▇://▇▇▇▇▇▇▇▇▇.▇▇▇▇.▇▇.▇▇/). country (the importer), the affected product (defined at the HS 4-digit level), and the type of measure (SPS vs. TBT). We include all measures notified up to the end of 2012 which means that our dataset is more up to date than that developed by ▇▇▇ et al. (2009) which was the basis for several previous studies.9 However, WTO members are required to notify only new or changed measures, and the notification requirements apply only to measures which differ from international standards, guidelines, or recommendations, or to situations where no standards exist, and, in addition may have a significant impact on trade. As pointed out in the literature, this could affect the results of an analysis of their trade and welfare impacts. Before we present our descriptive statistics, recall that in almost all cases, NTMs are unilateral measures, i.e. they apply to a given product regardless of its origin. Furthermore, the principle of mutual recognition applies among EU Member States. According to this principle, goods and services can move freely across Member States, and national legislation does not have to be harmonized. Therefore, to avoid bias, we exclude intra-EU trade flows from our NTMs analysis. Table 4 provides some statistics on the share of agri-food and non agri-food products (defined at the 6-digit level of the HS classification) affected by at least one NTM, in the US, EU, and TPP countries other than the US. These statistics are further broken down into SPS and TBT measures. A very large share of products is affected by NTMs in these markets; however, our results suggest some differences between agri-food and non agri-food products. TTIP and TPP countries notify SPS and TBT measures on almost all agri-food products. For non agri-food products, the picture is different. For instance, the US not...

Descriptive Statistics. The descriptive statistics for each variable are included in Table 1. I use an instrumental variable probit model to account for possible endogeneity between civil war duration and levels of humanitarian aid. There are a couple of issues of concern. First, there may be a relationship between the amount of humanitarian aid that is being delivered and the expected duration of a conflict. This could be because aid providers are actively considering how long they expect a conflict to last, or because there is some unobserved or unincluded variables that are related to both factors. Second, the level of humanitarian aid being delivered could be related to the type of conflict that is occurring. Aid donors might provide more aid to conflicts that involve rebel groups motivated by grievance rather than rebel groups motivated by greed because they are worried about the aid being looted. If either of these assumptions are true, then it would interfere with the empirical analysis. To conduct the analysis for this project, I utilize an instrumental variable probit with cubic time polynomials. The dependent variable for the probit analysis is war termination. The instrumental variable is used to model the amount of humanitarian aid sent to a country while taking into account the relationship that might exist between conflict and humanitar- ian aid deliveries. The cubic time polynomials is an approach developed by ▇▇▇▇▇▇ and ▇▇▇▇▇▇▇▇▇ (2010) to account for time in probit analysis.

Descriptive Statistics. From the table above show the mean score from post-test in the experimental class (56.62). It has been shown that using the climbing grammar mountain game can help students improve their scores. to see if the climbing grammar mountain game improves students' writing in recount texts and whether climbing grammar mountain has a significant impact on students' writing skills, using Paired Sample Test and Independent Sample Test, the researcher compared the means of one variable for two groups of cases using IBM SPSS Statistic 25.

Descriptive Statistics. The researcher used data received from OSIIS for the 2008 two-year old children to run a secondary data analysis of the immunization coverage rates. Statistical Analysis Systems (SAS) was used for the analysis. The following variables were analyzed from the data to provide a snap shot of coverage by race, county vaccination coverage rates and gender. The study did not required direct contact with children, their families, or providers. All immunization history was extracted from the immunization registry for the secondary data analysis.

Descriptive Statistics. Summary statistics on the socio-demographic and economic background of our subject pool are presented in Table 1. The objective of collecting such information is to investigate potential heterogeneous effects of experimental treatments but also to check the validity of the randomized allocation procedure to the different experimental treatments. Apart from a higher proportion of students in the IES treatment (27% versus 14% in the PES treatment, t- stat of 3.1) and a larger average household size in the PES treatments (4.7 versus 4.2 in the IES treatment, t-stat of 1.9), covariates are well balanced across the experimental treatments.xiii Despite randomizing the assignment of treatments to sessions, initial trust and trustworthiness turned out to be significantly higher in the IES than in the PES treatment. Trust is measured as the amount sent and trustworthiness as the average amount returned as percentage of the amount sent, averaged over all the possible amounts sent (elicited with the strategy method). Subjects assigned to the PES and IES treatments sent on average 5.2 and

Descriptive Statistics. Descriptive statistics for all variables included in multivariate models are presented in Table 3. Seventy one (55%) countries out of 130 for which NCPI data were available were compliant with the “Three ones” recommendation, that is, have adopted a multi-sectoral approach to fighting AIDS, established one national coordinating body, and allocated a budget for monitoring and evaluation. Average per capita spending on AIDS was 5.96 US dollars. On average, countries in the sample covered about 49% of the expenditures on fighting AIDS from domestic sources and about 2% of total expenditure has been allocated to programs for men who have sex with men, commercial sex workers and their clients, and intravenous drug users. About 26% of people in need to anti- retroviral therapy were receiving it, on average, in countries for which data were available, and some 29% of HIV positive pregnant women where receiving AZT to prevent vertical transmission from mother to child. 55% of CSWs and 47% of MSM reported having accessed HIV prevention programs in countries for which data were available. About 30% of the population could correctly identify routes of HIV transmission and prevention methods. 78% of CSWs and 57% MSM reported using a condom the last time they had sex. In the time period under analysis (2003-2007), on average, about 17% of the population had access to the Internet. The average ethnic fragmentation score was 0.44, and the average age of the largest government party was 35.5 years. The average value of the electoral market imperfections composite score was 2.07 and the score ranged in the data from 0.62 to 2.87. The average imputed Freedom House/Polity score was 6.62. The mean value of the imputed HIV prevalence was 2.26%. The average per capita GDP in the sample was 11,569 US dollars and some 34% of the observations were classified as wealthier (per capita income above the sample mean). On average, governments in the sample spent some 11% of their overall expenditure of health. Some 60% observations had electoral institutions based on proportional representation. 34% of the observations in the data were classified by the DPI as having a parliamentary system, 57% - as a presidential system with the president elected in direct elections, and 9% - as presidential systems with a strong presidency with the president elected in indirect elections.

Descriptive Statistics. The degree of change within patients was evaluated by comparing the mean raw item scores between the pretest and posttest. Uniformity in the pretest to posttest interval was evaluated by calculating quantiles of the days between the pretest and posttest.

Descriptive Statistics. Initially, 790 charts were studied, but 566 were included in the final analysis. There were 51 incomplete skin test records and 3 duplicate entries, resulting in 736 complete charts to review. The average patient age was 35.5 years old with a range of 2 to 83 years old. Fifty-seven percent of the patients were female. Forty-four percent were dog owners and 40% owned cats. Seven percent were current smokers, and 19% had smoked in the past.

Descriptive Statistics. Table 2.1 presents descriptive statistics for the sample of low-wage workers who benefitted from the implementation of the NMW (treatment group) as well as for employees who did not experience a pay raise (control group) for 1997. It is observable that individuals from both groups are similar regarding most characteristics and demographics before the policy change. Since a portion of the treatment group includes 144 workers who were paid below the new NMW in the pre-treatment period, it is not surprising that average personal income of treated people is lower than that of individuals belonging to the control group (£553.86 vs. £966.34). Only small differences between the groups exist regarding the share of people reporting to be in excellent or very good health (73.1% vs. 75.7%). The statistics furthermore show that the share of women is substantially larger in the treatment group which is consistent with findings by ▇▇▇▇▇▇▇ and ▇▇▇▇▇▇▇▇▇ (2002). Table 2.2 shows sample statistics for health conditions in the first year of the study. Panel A provides the share of individuals reporting suffering from the 13 health conditions for each group. It is observable that treated individuals are 6.7 percentage points more likely to suffer from any health condition, whereas the shares for the two groups are comparable across all conditions besides migraine. In order to further examine the role of wage increases on health, I create two groups of health conditions in Panel B, based on the hypothesis that individuals are more likely to purchase over-the-counter medication following a raise: (1) conditions that could be treated immediately by additional earnings; (2) long-term/chronic conditions that should not be affected by having more money in the short-run. Despite the fact that the NHS provides universal health insurance coverage, issues like quality of care as well as long waiting times were prevalent at the time of the study (Vizard and Obolenskaya, 2013). In order to avoid long waiting times, individuals in the UK can purchase a relatively small number of medications, which are placed on the General Sales List, at pharmacies without any prescription.20 Finding declines in the presence of immediately “treatable” conditions after the reform could provide additional evidence for improvements in self-reported health status, whereas examining short-run changes in the presence of long-term conditions serves as a falsification test. Figure 2.1 provides an overview of chan...