Task 1
You have been provided with data on a biodiversity survey of freshwater. Present this data in the most appropriate format and provide a figure legend.
Task 2
You have been provided with data concerning the microbiological contamination of different water sources. You are provided with counts of bacterial cells in 30 different samples of tap, river, and sea and pond water. a) Create a box & whisker diagram of the data and provide a figure legend. b) Report the mean, standard deviation, median, range and interquartile range of each water type in the table. c) Write a short description of the data of what the data is showing.
Table 1. Descriptive statistics of bacterial cell counts in different water sources.
| Water type | Tap | River | Sea | Pond |
| Mean | 10792.0667 | 11462.7 | 13796.3667 | 19826.4 |
| Standard deviation | 8399.97479 | 7707.91443 | 9242.25945 | 13364.3547 |
| Median | 7722.5 | 11983 | 11695.5 | 17003 |
| Range | -19733 | 14019 | -5467 | 5229 |
| Interquartile range | 13261 | -652 | -4292 | 3258 |
c) The data represents the different types of water bodies and contamination in terms of microbiological substances. The highest mean can be seen in pond water. The lowest standard deviation is of the river. All the other calculations are also done and represented in the above table. The box graph also shows the same (Wang, et al., 2016).
Task 3
You are provided with data on shoe size and height from 200 individuals. a) Plot this data to show whether there is a correlation between the two variables. b) Comment on the correlation and any limitations of using shoe size to predict an individual’s height.
a) Correlation
| Height (cm) | Foot Size (UK) | |
| Height (cm) | 1 | |
| Foot Size (UK) | 0.62451043 | 1 |
b) As per the correlation that is calculated, the correlation between both height in cams and size of the foot, are correlated positively. The consequences of the relevance of both variables are that both are poorly correlated and have no relevance in terms of relation (Enders, 2022).
Task 4
You have been provided with substance-associated mortality data for a particular country. This mortality data is categorized by substance type (tobacco, alcohol, illicit drug). a) Plot this data to show trends in the different risks over time and provide a legend. b) Describe any trends you notice in the data.
- a) Trends chart
- b) According to the data analysis, the death rate of persons in regard to Tobacco use is declining with time, although the rate is variable. The death rate by Alcohol use is likewise declining, albeit at a slower rate. In the case of Illicit medicines, the rate is constant; therefore no such pattern is seen.
Task 5
You are provided with the ‘before’ and ‘after’ weights of individuals undertaking a diet for 6 weeks. a) Present and analyze the data in a suitable manner and perform the appropriate t-test to ascertain whether the diet has led to significant weight loss. b) Based on this result would you accept or reject the hypothesis ‘The diet causes individuals to lose weight’?
a) t-Test: Paired Two Sample for Means
| Before diet (kg) | After Diet (kg) | |
| Mean | 72.875 | 72.21885 |
| Variance | 70.28804348 | 75.99470182 |
| Observations | 24 | 24 |
| Pearson Correlation | 0.964365566 | |
| Hypothesized Mean Difference | 0 | |
| df | 23 | |
| t Stat | 1.393635865 | |
| P(T<=t) one-tail | 0.088374559 | |
| t Critical one-tail | 1.713871528 | |
| P(T<=t) two-tail | 0.176749117 | |
| t Critical two-tail | 2.06865761 | |
b) H0>h1 the hypothesis is accepted. Although the diet promotes weight reduction, it is ineffective.
In some instances, However, after analyzing the t-test findings, the hypothesis is accepted (Grbich, 2012).
References
Enders, C.K., 2022. Applied missing data analysis. Guilford Publications.
Grbich, C., 2012. Qualitative data analysis: An introduction. sage.
Wang, J.L., Chiou, J.M. and Müller, H.G., 2016. Functional data analysis. Annual Review of Statistics and its application, 3, pp.257-295.