Descriptive Analysis. In this section the researcher explained the frequencies, percentages, meanand etcof the test, based on the result of the test before and after giving the treatment in both experimental and the control class. The scoring grade canbe seen in the table 4.1
Descriptive Analysis. Table 7 showed the receipt of cervical cancer treatment patients received within two years of Medicaid enrollment. For patients with pre-invasive cervical cancer, 56.0% had any cancer work-up, 75.4% had any precancerous procedures, and 20.8% had a simple hysterectomy. For patients with invasive cervical cancer, 84.7% had any cancer work-up, 34.2% had any invasive surgery, 61.9% had any radiation and 53.8% had any chemotherapy. As we further explored the treatment combinations among the pre-invasive cervical patients, 75.3% had precancerous procedures, 7.7% had simple hysterectomy, and 13.1% had both treatments (Table 8). Less than 1% of these patients received only radiation and/or chemotherapy and only 3.6% received no cancer treatment for their disease. For invasive cases, overall, 15.3% had invasive surgery, 50.5% had radiation and/or chemotherapy, 16.7% had both, and 17.6% received no cancer treatment. As we additionally examined treatment according to stage of cancer, we found that surgery was a major procedure for treating patients with local stage(29.3%) while radiation and/or chemotherapy was mainly used for treating those with regional or distant (69.3% and 78.3%). We also found that patients with local stage of cervical cancer had the highest rate (24.3%) of no invasive treatment even though only 31.5% of them received conization.
Descriptive Analysis. The descriptive statistics were generated for all the covariates stratified by relapse detection methods in LEAD and MER cohorts, separately. For categorical variables, the frequencies and corresponding percentages of each level were presented. For continuous variables, the means and 95% confidence intervals were presented. The difference in distribution of covariates within each relapse detection group was compared using Chi-square test or Xxxxxx ‘s exact test for categorical variables and ANOVA test or Kruskal-Wallis test for continuous variables.
Descriptive Analysis. The researcher gave the description to data that obtained in terms of frequency, mean score, median, to show the result based on the level of category descriptively.
Descriptive Analysis. The descriptive analysis includes the variables: gender, ethnicity, students’ residence (participants studying at the research site either live in a dormitory or in the city with their families) and self-reported academic performance. In total, 121 respondents completed the online survey. The gender of the participants is displayed in Table 1. There were 58 boys and 63 girls who answered the questions, with 47.9 and 52.1 valid percent respectively. Table 1 Gender of the Survey Respondents Regarding the ethnicity variable, the majority of respondents are Kazakh, with 102 participants identifying as Kazakh, 10 Russian, 5 Uzbek and 4 individuals of other nationalities (Figure 3).
Descriptive Analysis. In this section, a descriptive analysis of eight dimensions of teacher-student relationships will be demonstrated. Table 1 includes the numbers of participants, means and standard deviations on the students' perceived qualities of teacher-student relationships. Results showed that, overall, the students perceive their teachers in a positive way since all means for positive attributes are higher than means for negative attributes. More specifically, results showed that students rated their teachers‟ quality of understanding (M = 25.93, SD = 4.08) higher than any others, but they gave the lowest ratings to their teachers being uncertain (M = 13.59, SD = 5.34) and dissatisfied of their learning (M = 13.29, SD = 4.84). Overall, this means that the participants of this study feel that their teachers understand them. In addition, the nominated students perceive their teachers being satisfied with their learning and behaving in a certain way. Table 1. Descriptive Statistics for Teacher-Student Relationships n M SD Understanding 57 25.92 4.08 Leadership 57 25.12 4.66 Helpful 57 24.49 4.50 Student Freedom 57 22.03 4.38 Strict 57 17.14 3.65 Admonishing 57 15.19 3.35 Uncertain 57 13.59 5.34 Dissatisfied 57 13.29 4.84 Table 2 presents the means and standard deviations on teacher-student relationships divided by gender. Results indicated that there is not difference in the way both females and males perceive their teachers‟ qualities as being helpful, strict and dissatisfied with their learning. However, male students (M = 26.18, SD = 3.76) perceive slightly higher than females (M = 25.70, SD = 4.41) the quality of Understanding in their relationships with teachers. The same trend can be observed for such qualities as Leadership, Student Freedom, Admonishing and Uncertain, with male students rating these dimensions slightly higher than their female counterparts. Overall, there is no considerable difference in the means for both genders‟ perception of teacher-student relationships. Table 2. Descriptive Statistics for Teacher-Student Relationships by Gender n M SD Understanding Male 27 26.18 3.76 Female 30 25.70 4.41 Leadership Male 27 25.92 3.65 Female 30 24.40 5.36 Helpful Male 27 24.81 4.23 Female 30 24.20 4.78 Student Freedom Male 27 22.44 3.46 Female 30 21.66 5.10 Strict Male 27 17.29 3.72 Female 30 17.00 3.63 Admonishing Male 27 15.77 3.53 Female 30 14.66 3.14 Uncertain Male 27 14.55 5.22 Female 30 12.73 5.38 Dissatisfied Male 27 13.62 4.61 Female 30 13.00 5.09 Tab...
Descriptive Analysis. In this section a descriptive analysis of students‟ emotional intelligence will be demonstrated. Results showed that, overall, the total emotional intelligence of nominated students in this study equals to M = 136.54, SD = 21.12. In terms of the students‟ gender, results indicated that total emotional intelligence of boys (M = 141.48, SD = 20.04) exceeds that of girls (M = 131.10, SD = 21.40). That means, boys have a higher level of emotional intelligence than girls. Regarding the students‟ language of instruction, results indicated that the students studying in Kazakh language (M = 133.89, SD = 18.73) have a relatively lower score of total emotional intelligence than Russian language students (M = 140.88, SD =25.23). That means, Russian language students report a comparatively higher level of emotional intelligence than students studying in a Kazakh group. As for the students‟ age, the analysis demonstrated that older students have a higher level of emotional intelligence that their younger counterparts. 19 years old students (M = 143.60, SD = 20.28) scored higher than 18 years old ones (M = 134.67, SD = 21.28). In this part, a descriptive analysis of students‟ level of emotional intelligence has been demonstrated. Overall, the analysis has shown that boys report a higher level of emotional intelligence than girls. Regarding the language of instruction, Russian language students demonstrate a higher level of emotional intelligence than students studying in the Kazakh group. In terms of students‟ age, 19-year-old students‟ level of emotional intelligence exceeds that of 18-year-old ones.
Descriptive Analysis. We began with a flow of funds analysis that illustrated transfer of funds from sources to payers, payers to providers, payers to services and providers to services. This initial step was important to identify links and patterns in the way funds are received and distributed within the system. We were able to determine the kinds of services offered by specific providers and who their main payers are. The goal was to see whether health providers offered the services for which they were paid by financing agents. We then proceeded to carry out a more thorough descriptive analysis of our data. We examined payments and expenditures made within individual financing schemes in order to figure out where each schemes was receiving funds from, and which providers were they working with to cover what services. This allowed us to assess the costs covered by each scheme and to weigh their health sector financing contribution.
Descriptive Analysis. Table 4 displays number of items, means, standard deviations and internal consistency of instruments used to measure academic burnout, personality factors and academic motivation. The results showed that the level of academic burnout of NIS high-school students may be described as average (M=30.78, SD=8.10). It is possible to consider School Burnout Inventory an internally consistent instrument (α=.75). However, looking at each dimension separately, it is seen that exhaustion dimension has a lower internal consistency coefficient (M= 30.78, SD= 8.10, α= .52) than other dimensions. As for Big Five Instrument, the internal consistency coefficient for extraversion (M=26.76, SD=5.77, α=.77) is higher than for other factors. Agreeableness (M=31.13, SD=5.02, α=.55), conscientiousness (M=28.97, SD=4.89, α=.56) and neuroticism (M=26.25, SD=4.60, α=.56) showed similar internal consistency coefficients. Internal consistency coefficient for openness was lower than for extraversion, but higher than for other factors (M=38.42, SD=5.58, α=.68). Looking at the descriptive statistics of Academic Motivation scale, students of NIS scored higher in intrinsic motivation oriented on knowledge, external motivation identified and external motivation oriented on external regulation, and lower in internal motivation oriented on accomplishment, internal motivation oriented on experience, and external motivation introjected. Internal consistency coefficients of intrinsic (α=.92), external (α=.85) and amotivation (α=.79) were satisfactory (see Table 3). Table 3 Descriptive Statistics for key variables factors with internal consistencies Variable Items M SD α ABS total 9 30.78 8.10 .75 Exhaustion 4 14.09 4.01 .52 Cynicism 3 10.04 3.75 .74 Inadequacy 2 6.58 2.84 .70 PF Extraversion 8 26.76 5.78 .77 Agreeableness 9 31.13 5.02 .55 Conscientiousness 9 28.97 4.89 .56 Neuroticism 8 26.25 4.60 .56 Openness 10 38.42 5.58 .68 AM IM total 12 54.27 16.06 .92 IM_knowledge 4 19.65 5.95 .88 IM_accomplishment 4 17.64 6.37 .87 IM_expereince 4 16.78 5.57 .71 EM total 12 60.25 13.22 .85 EM_identified 4 21.07 5.36 .78 EM_introjected 4 16.87 5.96 .77 EM_external regulation 4 22.11 5.40 .80 Amotivation 4 9.93 5.51 .79 ABS= Academic Burnout in School setting; PF= personality factors; AM= academic motivation; IM=intrinsic motivation; EM=extrinsic motivation; M = Mean; SD = Standard Deviation.
Descriptive Analysis. COUNTRY RANKINGS Tables 2 and 3 present the country rankings for presence-of-policy and policy settings, respectively, in 1970, 1980, 1990 and 2000. A lower figure indicates a smaller distance to the SAPO, i.e for each point in time the ‘best performers’ are at the top of the list. First, the steady lowering of the mean gap for presence-of-policy across the entire country sample (from 0.8767 in 1970 to 0.2917 in 2000) shows that over the past 30 years environmental policies have spread effectively. In 1970, several countries had few or even none of the policies in place that were ‘avail- able’ at the time (i.e. a country mean gap close or equal to 1). In 2000, almost all countries had installed at least half of the ‘current’ policies (i.e. a country mean gap below 0.5). In 1970, even in the ‘best performing’ countries more than half of the then ‘available’ policies had not gained footing. This had dramatically 684 Journal of European Public Policy Culture (dominant religion) Institutional structure Protestant Other Neo-corporatist Liberal-pluralist Statist Austria + + Table 1 Characterization of countries for the independent variables ‘culture’ and ‘institutional structure’ Belgium + + Bulgaria + + Denmark + + Downloaded by [Radboud Universiteit Nijmegen] at 04:52 09 July 2012 Finland + + France + + Germany + + Greece + + Hungary + + Ireland + + Italy + + Japan + + Mexico + + Netherlands + + Norway + + Poland + + Portugal + + Romania + + Slovakia + + Spain + + Sweden + + Switzerland + + UK + + USA + + Sources: Xxxxx 2002; xxxx://xxx.xxxxxxxxxxxx.xxx; Xxxxxxxxxx 1989; Xxx Xxxxxxx 1995; Xxxxxxx 1999; adapted from Xxxxxxxx et al. 2005. improved in 2000. The settings figures, moreover, suggest that policies not only spread as such but did so at an ever stricter level. In fact, two trends are com- bined here: both the SAPO as such becomes stricter over the years for almost all policies and the average distance to this increasingly strict SAPO decreases. Second, the rankings for 1990 and 2000 roughly confirm the conventional division between leaders and laggards in environmental policy (x.x. Xxxxxxxx and Xxxxxxxxxx 1997; Bo¨rzel 2002; Ja¨nicke 2005). While countries located pre- dominantly in North-western Europe head the lists, countries from the southern and eastern parts of Europe as well as Mexico and – surprisingly – the USA populate the lowest ranks. However, this division stands out considerably less clearly in the 1970s and 1980s. For instance, Germany, ...
