Problems with using information >

Answers

1a) No, this statement is not reliable. This statistic is a result of an inappropriate estimation because of its unrepresentative sample. Choosing Oshawa as a representative population neglects regional variations including industry (i.e., resource-based, tourism, manufacturing, high-tech), employment (i.e., seasonal, permanent) and labour type (i.e., retail, government). In order to have a representative sample, the statistician must gather information from many different areas across the country, including rural, semi-urban and urban areas.

b) No, this statement is not reliable. Phone-in polls require volunteer sampling, which can lead to unrepresentative samples.

c) This statement may or may not be reliable. Its reliability is questioned because we do not know the source of the school leavers statistic.

d) Again, this statement may or may not be reliable. We do not know the origin of this information. However, if the survey was conducted properly nationwide, and if 'youth' is defined as those people between the ages of 15 and 24 years, then there is no reason to state that this statistic is incorrect.

e) No, this statement is not reliable. If the statistics are conflicting, then this must mean that there is either a difference in their respective definitions of forest cover, one or both of the sources are flawed, or the results have been misinterpreted by one or both of the parties.

2. The two types of non-sampling errors are random errors and systematic (or bias) errors.

3. A sampling error is influenced by the sample and population sizes, the variability of the characteristic of interest in the population, the sample design and the estimation method.

4. Systematic errors can result from