Crime statistics

The Effect of Carbon Sources on Yeast Growth Introduction Biofilms are encountered every day through a multitude of ways whether it’s by dental plaque on our teeth, in our showers or on medical equipment. (Hall-Stoodley 2004). A biofilm is formed when single bacterial cells stick to each other (Schussler 2014). Biofilms as a group converse and work together as a complex unit which allow them to be effective in growing, surviving and reproducing (Liu et al. 2015). Moreover, yeast biofilms are an…

3.12: Data Analysis process Overall, the objective of the research analysis is to try to answer the research questions formulated in Chapter 1. Accordingly, a conceptual framework and propositions have been developed from these questions, and justified in the literature review section. Therefore, the data analysis will be pursued to gather evidence pertaining to the several concepts identified. Quantitative data from the questiormaire survey will be analyzed by utilizing the Statistical…

In order to examine the data, we utilized SPSS statistical software and conducted a regression analysis of the direct variables of Organizational Citizenship Behavior, Work and Well-being, and Job Satisfaction against the constant independent variable, Frequency of Supervisor Feedback. We used regression analysis because it allowed us to discern any causal relationships between our dependent variables and one constant variable that might support or reject our hypotheses. We were looking for…

The goal of this experiment was to determine whether is there a significant difference in stomatal densities between young and old leaves or no. The stomatal density of young and old leaves has not significantly different densities. The age of the leaf does not аffect and do not correlate with stomatal density. Because, when the leaf is a baby leaf it makes all the stomata and as leaf growth it just pulls apart from each other. Stomata has an essential rоle in all plаnts. Stomata helps to…

students’ results and attendance will be summarised, analysed and interpreted. Data 2.1 Research Stanford University found that on average, males outperform females on mathematics tests (Niederle & Vesterlund, 2010), which would be expected in the statistics course BSB123. The majority of the BSB123 sample (56.8%) was female, which may affect exam results. Additionally, quiz results are positively correlated with exam results (Wambuguh & Yonn-Brown, 2013) and students…

In this project, I will analyze the problem of gender inequality in terms of labor income. This problem is important in our society because people with same background and same experience should be treated the same in the same working environment. Women should not be judged based on their biological gender. The data sample used in this project is working individuals between ages 25 and 54 from Current Population Survey, 2012. Sample size contains 999 observations. I will first discuss the…

A within subject’s experimental design, compared the perceived differences in length of different sized paperclips on different body parts. The perceived distance of the paperclips, were rated on a scale of 0 to 2; zero meaning equal, one meaning shorter and two meaning longer. There were three conditions; the Finger-Wrist condition, the Finger-Forearm condition, and the Wrist-Forearm condition. 20-psychology students participated in the study. All 20 participants participated in all three…

2.4. Data Analysis For the analysis of the quantitative data, one-way ANOVA, Chi-Square test of independence and descriptive statistics were applied. For ANOVA, in order to determine which groups caused the significant difference, Tamhane T2 test, one of the most common post hoc (multiple comparison) tests, was used. For the normal distribution of data, the skewness and kurtosis coefficients were examined. For the normality test skewness coefficient of a distribution taken in the range of -1.5…

Explain TABLE REGRESSION Table 4.9: Result of simple linear regression between level and ovitrap index Variable SLR Level b (95% CI) p-value -2.5 (-7.7, 2.9) 0.236 R2 = 0.421. The model not fit well: Model assumption are not met There is statistically no significant linear relationship between level and ovitrap index (p= 0.236). The increase of the multi –storey house level is not associated with the ovitrap index level. With level, the model explains 42% of variation of the ovitrap…

Table 4.2 System suitability results for Lamivudine, Zidovudine and Nevirapine Parameters Lamivudine Zidovudine Nevirapine Retention time 2.327 2.864 5.608 Area 212473 338930 228426 USP Plate count 2715.09 3350.07 4979.51 USP Tailing 1.38 1.32 1.18 4.3.1.2 Linearity A linear correlation coefficient factor was obtained between the concentrations of Lamivudine, Zidovudine and Nevirapine versus the peak area. The calibration curves were linear for concentrations between 15-150 µg/mL. The linearity…