91Ó°ÊÓ

The given statement is:

In the game of keno, 20 balls are selected at random from 80 balls numbered 1-80. In Exercise 1.48 on page 16, you used simple random sampling to simulate one game of keno.

First, divide the population size by the sample size and then round off the result to the nearest whole number(m).

In this case, the population size is 80.

and the sample size is 20.

$$\begin{gathered} m=\frac{80}{20} \\ =4 \end{gathered}$$

Now obtain a number kbetween 1 to 4,by using the random number table we obtained the number k as 2.

In the last step, we need to write every 4th number from the list. It will start from 2 and follow the same procedure until we get our 20samples.

Then the resulted numbers will be:

2, 6, 10, 14, 18, 22, 26, 30, 34, 38, 42, 46, 50, 54, 58, 62, 66, 70, 74, 78.

Systematic random sampling is much easier to conduct if we compare it with simple random sampling.

The reason being there are some disadvantages to simple random sampling. That is, in some cases, it does not provide enough information about the subpopulations.

Furthermore, when the population members are dispersed, making this method of sample collection is impractical.

Systematic random sampling usually avoids cases of biasedness, that's why it is reasonable to use systematic random sampling.