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The chief motive for examining a sample rather than a population is cost

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The chief motive for examining a sample rather than a population is cost. Statistical inference permits us to draw conclusions about a population parameter based on a sample that is quite small in comparison to the size of the total population. For instance, if you wanted to investigate Smoke-Cola's claim of a 1 in 10,000 chance of winning a cigarette - you might not want to buy 10,000 (at least!) Smoke-Colas. You would take a representative sample, estimate and use a sample statistic as an estimate of the population parameter.

You've heard this all before.

A simple random sample is a sample selected in such a way that every possible sample with the same number of observations is equally likely to be chosen. A stratified random sample is obtained by separating the population into mutually exclusive sets or strata and then drawing simple random samples from each stratum. A cluster sample is a simple random sample of groups or clusters of elements.

Answer these questions. You will need to use random numbers.

1. Richard Cheney, mall developer, would like to ask people in his community their views on a proposed new shopping centre. By the latest Census, there are 500 households in his community, numbered 1 through 500. He would like to randomly select 25 of these households. Help him by designing a sampling mechanism and selecting these households.

2. Ralph Nader, safety guru, wants to determine the proportion of vehicles in his state with worn tires. The state license plate contains six digits; the 4th digit is either 0 or 1 (0 indicates a passenger car, 1 everything else).

Design a sampling method and generate a sample of 60 cars.