Basics of Probability and Statistics Week 1 Challenge

1. Population variance refers to value of variance that is calculated from the population data that is the entire data. Sample variance refers to the value of variance that is calculated from the sample data. So the major difference is denominator. For sample data it is n-1 and for population data it is n

2.Stratified Sampling: Here the population is divided in to homogeneous segments and then the sample is taken randomly from the segments. Here the samples are taken randomly from the segments.

Cluster Sampling: Here the members of the sample are selected randomly from the naturally occured groups called 'cluster'. Here the samples are taken randomly from the naturally occured group.

3. maximum sample size is usually around 10% of the population, as long as this does not exceed 1000. For example, in a population of 5000, 10% would be 500. In a population of 200,000, 10% would be 20,000. This exceeds 1000, so in this case the maximum would be 1000.

Even in a population of 200,000, sampling 1000 people will normally give a fairly accurate result. Sampling more than 1000 people won’t add much to the accuracy given the extra time and money it would cost.

4.1/221

5.When two dice are drawn there will be 36 combinations. However, for getting the same number on both dies, there will be 6 possibilities which are (1,1),(2,2),(3,3),(4,4),(5,5),(6,6). Hence, the required probability is 6/36 which reduces to 1/36.