Descriptive Analysis Clause Samples
Descriptive Analysis. Tables 6-1 and 6-2 show the mean values of access charges in autumn 2003, separated between East- and West-Germany. Given the structural feature of consumption density we would expect increasing access charges if the cable rate increases. Regarding East-Germany and low voltage network the values in the feature “CR high” contradicts this expectation (table 6-1). Moving to West-Germany/low voltage network suppliers access charges will not increase with higher CR-feature if medium or high density is given. Keeping the structural feature “cable rate” in East Germany constant the mean access charge for high consumption/ medium cable rate only is contradictory to our hypothesis, the same contradictorily result is given for West-Germany/low cable rate/medium density (table 6-1). Table 6-1: Mean values of access charges – low voltage 09/2003 East West CR „cable rate“ High 6.23 6.09 5.89 5.53 5.25 5.15 medium 6.84 5.97 6.12 5.51 5.35 5.20 low n=1 n=1 5.71 5.53 5.68 5.21 Source: VDN 2003 Table 6-2 represents the mean values of medium voltage networks with population density as the first structural feature. Keeping constant D we have any expected sign in East Germany, and for West Germany unexpected values in high cable rate/low density and in medium cable density/medium density are calculated. Assuming a given cable rate we only get an “anomaly” in West-Germany/low CR and medium D. Table 6-2: Mean values of access charges – medium voltage 09/2003 East West Low medium high low medium high CR „cable rate“ High 3.13 3.21 3.08 2.81 2.71 2.58 medium 3.39 3.35 n=1 2.96 2.60 2.50 low 3.43 n=1 n=1 2.67 2.74 n=1 Source: VDN 2003 The descriptive values show that the variable cable rate can not be confirmed many times. But the density variables also have unexpected signs.
Descriptive Analysis. The researcher explains the frequencies, percentages, and mean score of the tests in this section based on test results in both the experimental and control groups before and after the intervention. Table 4.1 shows the assessment criteria for writing from ▇▇▇▇▇▇ (2003) .
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. 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. 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. Plasma concentrations and PK parameters will be summarized by renal function classification with descriptive statistics (number, arithmetic mean, standard deviation, coefficient of variation [CV%], geometric mean, geometric CV%, median, minimum, and maximum). In addition, summary statistics for unbound LOXO-305 will be tabulated by renal function classification.
Descriptive Analysis. 4.1.1. The Prevalence and Characteristics of Unhealthy Weight among Children Under 5- year-old from 2000-2014
Descriptive Analysis. In descriptive analysis, the researcher explained the mean, median standard deviation, maximum score, minimum score, percentage and others of the test before and after giving treatment betweencontrol class and experimental class. The scoring grade can be seen in the table 5.
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 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 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.