Test on Understanding Statistical Fallacies and Misrepresentation
Understanding Statistical Fallacies and Misrepresentation
Statistical Misleading Techniques
20 questions
Question 1: When a study claims a new medicine works for 2 out of 3 participants, this is always strong enough data to conclude the medicine is effective.
A. Ano
B. Ne
Explanation: Chapter 3 states that if a medicine works for 2 out of 3 people, this does not necessarily prove it is effective because the sample size is too small. This highlights the importance of paying attention to whether the data is strong enough to support the conclusion.
Question 2: The study materials define the mode as the total divided by the number of values.
A. Ano
B. Ne
Explanation: The study materials define the mean as the total divided by the number of values. The mode is defined as the value that appears most often.
Question 3: Graphs that use truncated axes are a method by which visual information can be distorted.
A. Ano
B. Ne
Explanation: Chapter 5 states that truncated axes can mislead readers by visually distorting information. For example, if a vertical axis starts at 90 instead of 0, a small increase in sales can appear much larger.
Question 4: Truncated axes on a graph always make small differences appear less significant.
A. Ano
B. Ne
Explanation: Truncated axes can mislead readers and exaggerate differences. For example, a small increase in sales can be made to look huge if the vertical axis starts at 90 instead of 0, making differences appear more significant.
Question 5: To properly evaluate a statistic, one should consider whether the sample used accurately represents the entire population.
A. Ano
B. Ne
Explanation: Chapter 1, 'The Sample with the Built-in Bias,' states that a key lesson before trusting a statistic is to ask, 'Does the sample represent everyone?', highlighting the importance of sample representation.