Q.How can different methods of sampling and data collection be useful in impact evaluation of government social schemes. Describe with a suitable example 2018-15mrks.

Model answer outline:

A sample is a cross section of the population. Sampling techniques are used to estimate some characteristics of the entire population. It comes in two forms : probability and non probability. Under probability technique, randomly selected BPL-households using gas stove for cooking under the Ujjawala scheme may give us data about the satisfaction level of the scheme. For this, we may use survey methods involving questionnaire or rating scale. Some individuals, for example may give it 3 point as the cost of cylinder is about Rs 1000 even when subsidy is given after some time. Other may give better points like 8 or 10 on a ten points rating scale.

Both samples and methods of data collection are important. We cannot use a non probability technique ( quota sampling for example) to generalise the results for the entire population. Likewise, we can not use a case study method to infer the liking of the whole population for the scheme.

The non probability technique of sampling like cluster sampling may be useful in assessing the viewpoints of different peoples on Kishan samman scheme. Non probability sampling techniques focus on definite inclusiveness of the members of the target groups. We may servay farmers and non farmers for their attitudes towards this scheme. Again, we can not use case study methods in this case to collect data.

Case studies methods, however, could be used to assess rural development under ” Shansad adrash gram yojana”. In depth studies of a few such cases in point can reveal the effectiveness of this government scheme..

# Kindly elaborate the ideas