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Theory of Attributes- Basic concept and their applications: ATTRIBUTES:       Literally, an attribute means a quality or characteristic.Theory of attributes deals with qualitative characteristics  which not amenable to  quantitative measurements  are and hence need slightly different statistical treatment from that of the  variables. Examples of attributes are drinking,smoking, blindness, health, honesty, etc. An attribute may be marked by its presence (possession) or absence (dispossession) in  member of given population. It may be pointed out that the methods of statistical analysis applicable to the study of variables can also be used to a great extent in the theory of attributes and vice-versa. For example, the presence or absence of an attribute  may be regarded as changes in the values of a variable which can possess only two values, viz., 0 and 1. NOTATIONS: Suppose the population is divided into two classes according the to...

Time series: A time series is a set of observations measured at time or space intervals arranged in chronological order. For instance, the yearly demand of a commodity, weekly prices of an item, food production in India from year to year, etc. Many economists and statisticians have defined time series in different words. Wessel and Wellet: When quantitative data  are arranged in the order of their occurrence,the resulting statistical series is called a time series. Moris Hamburg : A time series is a set of statistical observations arranged in chronological order. Patterson: A time series consists of statistical data which are collected, recorded or observed over successive increments. Ya-lun-Chou: A time series may be defined as a collection of magnitudes belonging to different time periods, of some variable or composite of variables such as production of steel, per capita income, gross national product, price of tobacco or index of industrial production. Cecil H...

In Statistics, the data collection is a process of gathering information from all the relevant sources to find a solution to the research problem. It helps to evaluate the outcome of the problem. Most of the organization uses data collection methods to make assumptions about future probabilities and trends. Once the data is collected, it is necessary to underdo the data organization process. The data collection method is divided into two categories namely, Primary Data Collection methods Secondary Data Collection methods let us discuss the different types of data collection methods and their advantages and limitations 1. Primary Data Collection Methods Primary data or raw data is a type of information that is obtained directly from the first-hand source through experiments, surveys, or observations. The primary data collection method is further classified into two types. They are Quantitative Data Collection Methods Qualitative Dat...