There are several statistical software packages accessible today. SOFTWARES FOR STATISTICS, SAMPLE SIZE CALCULATION AND POWER ANALYSIS Hypothesis testing is essential to process for making logical choices regarding observed effects’ veracity. A hypothesis is a suggested explanation for a phenomenon (plural hypotheses). The goal is to prove or disprove the theories. In inferential statistics, data from a sample is analysed to conclude the entire population. The central tendency describes how observations cluster about a centre point, whereas the degree of dispersion describes the spread towards the extremes. It’s useful when it’s not possible to investigate every single person in a group. Inferential statistics use a random sample of data from that group to characterise and infer about a community as a whole. The mean, median, and mode forms, descriptive statistics give an overview of data. A hierarchical scale with increasing precision can be used based on category, ordinal, interval and ratio scales (Figure 1).ĭescriptive statistics try to explain how variables in a sample or population are related. Continuous data includes serial serum glucose levels, partial pressure of oxygen in arterial blood, and oesophageal temperature. Discrete data examples include the number of respiratory arrest episodes or re-intubation in an intensive care unit. Discrete data is made up of countable observations, while continuous data is made up of measurable observations. Continuous data can take on any value, whereas discrete numerical data is stored as a whole number such as 0, 1, 2, 3,… (integer).
Classification of variables ĭiscrete and continuous measures are used to split quantitative or numerical data.
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