Topics: Regression analysis, Linear regression, Curve fitting Pages: 3 (748 words) Published: April 15, 2013
3.5 Critical Analysis
McGraw-Hill Ryerson Mathematics of Data Management, pp. 202–211

1.Edwin compares the street address numbers of three of his neighbours with the quality of their front lawn, which he rates on a scale of 1 to 10. He observes a positive linear correlation and concludes that people with higher street address numbers have better lawns. In Edwin’s study: a) What are the independent and dependent variables? The independent variable is the street number and the dependent number is rating of the lawn. b) What is wrong with the way that the dependent variable is measured? It is based on Edwin’s view of lawn quality rather than an objective standard. c) Classify the type of cause and effect that is most likely to explain the correlation. Accidental is most likely. Only three data points are in the study, so a single data point makes a huge difference. d) What is wrong with the sampling technique? Explain how it could be improved. Edwin chooses three neighbours. He needs to randomize his sampling both in terms of street numbers and streets. He also needs a much larger sample.

2. A radio talk show host invites listeners to respond to her stated opinion that our country’s immigration policies are weak. Near the end of her show, she tallies that 68% of callers agreed with her statement, and then concludes that over two thirds of Canadians feel that our immigration policies are weak. a) What type of bias is present in this study?

Non-response bias is present.
b) Explain why the sampling technique may be responsible for introducing this bias. Voluntary sampling where the show host is likely to treat those who disagree rudely will usually result in the participation of people who agree with the host. c) Would you classify this bias as intentional or unintentional? Explain. It is difficult to classify without knowing whether the host understands basic statistics, but I would guess that it is...
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