Name: Jecca Cervero

Section: O0C

            Book: Systems Analysis And Design /Sixth Edition

            Author: Kenneth E. Kendall, Julie E. Kendall

            Reference No.: QA 76.9 S88 K45 2005

Chapter:  Chapter 4

Quote:   Sampling can reduce cost, speed data gathering. Potentially make he study more effective, and possibly reduce the bias in the study.

Review:

Sampling

Sampling is the process of systematically selecting representative elements of a population.

Need for Sampling

1. Containing costs
2. Speeding up the data gathering
3. Improving the effectiveness
4. Reducing bias

Sampling Design

A systems analyst must follow four steps to design a good sample:

1.   Determine the data to be collected or described

The systems analyst needs a realistic plan about what will be done with data once that they are collected.

2.   Determine the population to be sampled

In the case of hard data, the systems analyst needs to decide, for example, if the last two months are sufficient, or if an entire year’s worth of repost are needed for analysis.

3.   Choose the type of sample

                  There are four main types of samples that a systems analyst can use:

·        Convenience Samples- sample are unrestricted and no probability  samples

·        Purposive Samples- moderately reliable

·        Simple Sample- not practical, especially when sampling involves documents and reports

·        Complex Samples-Complex Sampling that are most appropriate for the systems analyst are:

o       Systematic Sampling

Simplest method of probability sampling

o       Stratified Sampling

This is the most important sampling.

Stratification is the process of identifying subpopulations, or strata, and their selecting objects or people for sampling within these subpopulations.

o       Cluster Sampling

Systems analyst must selct a group of documents or people to study.

5. Decide on the sample size

The sample size depends on factors, some set by the systems analyst, some determined by what we know about the population itself.

The Sample Size Decision

• Determining sample size when sampling data on attributes
• Determining sample size when sampling data on variables
• Determining sample size when sampling qualitative data