Title 7. TYPES OF DATA DISTRIBUTION.pdf ✅

PHARMD GURU Page 1 The statistical data can be divided into two broad categories: 1. Quantitative data. 2. Qualitative data. QUANTITATIVE DATA:  The name itself saying ‘Quantity = how much = Number’.  Quantitative data is a numerical measurement expressed not by means of a natural language description, but rather in terms of numbers.  In quantitative data, the characteristics such as births, treated, non-treated etc.. do not vary, only the frequency i.e., no. of treated, no. of non-treated etc.. are varies.  In medical studies, such Quantitative data are mostly collected in anatomy and physiology, to define the normal (or) to find the limits of deviation from the normal in healthy persons. When the measurement (or) counting crosses the normal limits, it becomes unusual and may indicate pathology.  Some of the statistical methods employed in analysis of such data are mean, range, standard deviation, coefficient of variation and correlation coefficient.  The data collected and compiled from experimental works, records and surveys should be accurate and complete. They must be checked for accuracy and adequacy before processing further.  So far they are mixed & unsorted.  Next step. Therefore, is sorting (or) classification of the data into characteristic groups or classes as per age, sex, social class etc.  They should be presented in such a way that data should:  Become concise without losing the details.  Arouse interest in the reader.  Become simple and meaningful to form impressions.  Define the problem and suggest the solution too. TYPES OF DATA DISTRIBUTION
PHARMD GURU Page 2  Become helpful in further analysis. QUALITATIVE DATA:  Qualitative data is a categorical measurement, expressed not in terms of numbers, but rather by means of a natural language.  In statistics, it is often used interchangeably with "categorical" data.  It is classified, by counting the individuals having the same characteristics and not by measurement.  Persons with the same characteristic are counted to form specific groups (or) classes i.e., Categorized. Ex: Males, Young, Old, treated, Not treated etc.  In medical studies, such data are mostly collected in pharmacology to find the action of a drug, in clinical practice to test (or) compare the efficacy of a drug.  The results thus obtained are expressed as a ratio, proportion, percentage.  The statistical methods commonly employed in analysis of such data are standard error of proportion and chi-square tests. ABOVE MATTER IS TYPES OF DATA DISTRIBUTION. THAT DATA (DISTRIBUTION) SHOULD TO BE PRESENTED IN SOMEWAY. THAT CAN BE LEARNED BELOW: METHODS OF PRESENTATION: There are two main methods of presenting frequencies of a variable character or a variable. 1. Tabulation. 2. Drawing. 1. TABULATION:  Tabulations are devices for presenting data from a mass of statistical data.  Preparation of frequency distribution table is the first requirement.
PHARMD GURU Page 3 FREQUENCY DISTRIBUTION TABLE OR FREQUENCY TABLE:  In most of the studies, the information is collected in large quantity and the data should be classified and presented in the form of a frequency distribution table.  This is a very important step in statistical analysis. It groups large number of series or observations of master table and presents the data very concisely, giving all information at a glance.  The frequency distribution table of most biological variables develops a distribution which can be compared with the standard distributions such as binomial, Poisson or normal. Tabulation of frequencies for: a) Qualitative data. b) Quantitative data. a) Qualitative data: In qualitative data, there is no notion of magnitude or size of attribute, hence the presentation of frequency distribution is very simple. b) Quantitative data: In quantitative data, Presentation of data is more cumbersome, because in quantitative data, there is a need to measure the magnitude (or) size of the attribute, such as: Height, weight, Pulse rate etc. Rules for making a frequency distribution table: 1) The class interval (or) group interval between the groups should not be too broad (or) too narrow. 2) The number of groups (or) classes should not be too many (or) too few. But be ordinarily between 6 and 16 depending on the details necessary and the size of sample. 3) The class interval should be same throughout such as 80-89, 90-99, 100-109 etc. 4) The headings must be clear such as "height" in inches or in centimeters:age" in years or months, etc. If the data are expressed as rates. mention per cent or per thousand.
PHARMD GURU Page 4 5) Groups should be tabulated in ascending (or) descending order, from the lowest value in the range to the highest such as pulse rate 61-65, 66-70, .... 106-110. 6) If certain data are omitted (or) excluded deliberately, the reasons for the same should be given. 2. DRAWINGS: It can be presented by: a) Graphs. b) Diagrams.  They may be shown either by lines and dots (or) by figures.  The drawings are meant for the non-statistical minded people who want to study the relative values or frequencies of persons or events.  For the statistical-mined persons, they are for quick eye readings.  Presentation of quantitative, continuous or measured data is through graphs. The common graphs in use are:  Histogram  Frequency polygon  Frequency curve  Line chart or graph  Cumulative frequency diagram  Scatter or dot diagram.  Presentation of qualitative, discrete or counted data is through diagrams. The common diagrams in use are:  Bar diagram  Pie or sector diagram  Pictogram or picture diagram  Map diagram.