measure of central tendency
In statistics, the measure of central tendency is a typical and central value in the probability distribution. The central tendency also is referred to be the location or centre of the distribution. In the measuring of central tendency, all of the measures are referred to as averages. The node, median and the arithmetic mean are the commonly known measures to central tendency (Zhao et al., 2017). A middle tendency is set and get calculated for a theoretical distribution or the finite set of values.
Many authors use the central tendency for denoting tendency of qualitative data around some central values to the cluster. In any distribution of central tendency, it is contrasted with its variability or dispersion. Analysis judges if data contain strong or weak central tendency through checking its central tendency.
Before calculating any central tendency, it is important and appropriate to transform data. For instance, taking logarithms or squaring the values helps to transform data and used to the dimensional data prepared (Zhao et al., 2017). Transformation depends on the data being analyzed whether transformation will be appropriate or not. Mean or arithmetic mean is worked out through summation of total measurements dividing with observation number in the set data. Median is the value separating half from lower and higher set data. However, median and mode measures are used for ordinal data since the values get ranked relatively at each other but not measured. The mode is referred to be frequent value in the set data. The value is used for qualitative assignments with nominal data.
Parametric tests assume the normal values distributed like the height values, which are considered normal distribution of values. If the height values were to get graphed, a curve that is typically bell-shaped could be seen (Burke et al., 2018). The distribution is referred to as Gaussian distribution. The tests are generally more potent if compared with nonparametric tests. On the other hand, non parametric tests get used where theparametric tests are not used or not suited. They entail some rankings that checks weirdness and measurements of the distribution. However, parametric tests are recommended because they are able to differentiate two arms. The difference between the tests is that nonparametric tests entail 95% more efficient than parametric in hypothesis testing.
Cross sectional Study
The cross sectional study on coronary heart disease shows results of a study done about contribution of smoke to cause the heart disease. From the data shown, despite the coronary being associated to smoking habits, the smoking consequences are not well elucidated in the data. The study gives some values to determine if smoke can or cannot play a bigger role in causing the disease. The data shows the values in percentages to understand mthe numerical values through the research. In the study, cardiovascular diseases are mostly caused tgrough abusing drug substance which includes the smoking habit shown on the tables. The total population checked are 100. It is beneficial when deciding the outcome nd input variables in a study (Burke et al., 2018). However, on a study sometimes there occurs missing data. It could be due to a variety of reasons like taking correct and critical measurements, failure of electronic data, incapable of following subjects required. Luckily, pre-emptive actions can help minimize or eradicate the effects.
In concusion, biostatistics helps medics to know how to manage some diseases and the level they have affected people. Statistics data are critical in that they assit to avoid workload when looking for essential information to a vast group of people. They are effective like in a country where problems needs to get solved and relevant authorities or stakeholders require some data to plan and execute their mintentions. Performing parametriics and nonparametrics helps to evaluate various variables with every test vital in time of need. The central tendency assists to work out some data and get confident results if incorporated.