Q.9. Write a note on the association of attributes.
Similar Questions:-
- Write a note on techniques of association of attributes.
- Give the Methods of determining attributes.
Ans. Association of Attributes: The presence of an attribute is usually denoted by capital letters A, B, C, and so on, whereas the absence of an attribute is denoted by greek letters a,b, y where a means not a and same as others. A, b, y are called complementary attributes of a, b, and c. the combination of different attributes is denoted by AB, Ac., aß, etc.
Methods of Determining Attributes: In order to assert not, the following methods may be used:
1. Comparison of Observed and Expected Frequencies Method: when this method is applied the actual observation is com expectation, the attributes are said to be independent; 11 expectations, the attributes are said to be positively associated and if the actual the expectation, the attributes are said to be negatively associated.
2. Proportion Method: Under this method, the ratios or the prop are compared. If there exists no relationship between two attributes A and proportion of A’s amongst there’s and B’s as amongst the B’s and the proportion of Bsam when came as that amongst the di. For example, if a coin is tossed we expect irrespective of whether the coin is tossed by the right hand or the left hand.
3. Yule’s Coefficient of Association: Prof. Yule has suggested the following formula to measure the association:
5 Coefficient of Contingency (Karl Pearson’s): Classification of data can be either dichotomous or manifold. When the universe is divided into two groups, say, ‘rich’ and ‘not rich’–‘A’ and ‘not A’. but a universe may also be divided into a number of parts by a similar process. Thus, attribute ‘A’ may be subdivided into A 4 A., etc. Similarly, another attribute, say B can be sub-divided into B, B9, B,, etc. The frequency falling within the different classes can be arranged in the form of a contingency table.
Q.10. What is data? Give two examples of primary and secondary data. (2014-15)
Ans. Data. Data is a single piece of information. It may consist of numbers, words or images, or even a set of variables. It is viewed as the lowest level of abstraction from information and knowledge can be easily retrieved and derived from it.
1. Internal Data: The data generated by different organizations and government departments in their routine works is called internal data. For example, number of patients in the O.P.D. of a hos number of students admitted in a particular course in a university every year, number of birth number of deaths, number of infant deaths occurred every day in a certain area, etc. This type of data is always available from the records of the concerned department and therefore can be picked up from any statistical investigation.
2. External Data: The data collected by some external agency for a certain purpose is called external data. It may be collected by either census method or sample survey every method. In census method. gata information is collected from each and every unit of the population – survey, information is collected on some part (fraction) of the populace consultation concerned. For example, in India census is conducted after every ten years, while in the socio-economic survey, data is collected from different social and economic aspects like price, sales, production, etc. from the primary source or secondary sources. Thus, the external data can be further classified as.
(a) Primary data –
(b) Secondary data –
(a) Primary Data: Primary data is the data collected for the first time by an investigator or agency who makes use of the data for the first time. It is in the shape of raw material and after use, is converted into secondary data. This data is collected originally and needs more precaution at the time of collection but less at the time of its use. For example, raw materials
used in products.
(b) Secondary Data: This data is collected for the second time or any subsequent time by an investigator who makes use of the data for any subsequent time. It is already available and is not original. It needs at the time of collection less precaution but more at the time of use. For example, finished goods are capable of further processing.
Q.11. What is an analysis of variance? Explain its testing procedure when data is classified according to two-way. (2006-07)
Ans. Analysis of Variance: Analysis of variance (abbreviated as ANOVA) is useful in the fields of economics, biology, education, psychology, sociology, business, industry, and in research of several other disciplines. This technique is used when multiple sample cases are involved. For example, the significance of the difference between the means of two samples can be judged through either Z-test or the t-test, but the difficulty arises when we happen to examine the significance of the difference amongst more than two sample means at the same time. The ANOVA technique enables us to perform this simultaneous test and as such is considered to be an important tool of analysis in the hands of a researcher. Using this technique, one can draw inferences about whether the samples drawn from populations have the same mean.
Variance Analysis in Two Way Classification: In two-way classification, the effect of one factor is studied through the column-wise figures and totals and the other through the row-wise figures and totals. The variances are calculated for both the columns and rows and they are compared with the residual variance.
Table of Variance in Two-way Classification
