30 Questions
What is the researcher's obligation regarding the presentation of data and inferences?
To keep the presentation of the data separate from the inferences and speculations
How do researchers conducting research in the context of their own values affect the problem investigated?
Values may influence the problem investigated and the conclusions or solutions proposed
What is the purpose of striving to gather and present data in as pure a form as possible?
To minimize distortion or falsification based on personal values
Why should laypersons and scientists be cautious of technical language and catchy titles?
They may not indicate expertise or scientific support for claims
What is a common misleading presentation associated with numbers in scientific research?
Misleading through words, emphasis, and percentages
How can consumers identify unreliable sources of scientific information?
By checking website indicators, 'About Us' pages, and using fact-checking tools
What are the four common means of connecting a product with science as described in the text?
Using scientific costumes and props, quoting or relying on authorities, employing technical vocabulary, and selecting promising names
What is the purpose of mentioning technical words in a deliberately offhand fashion as mentioned in the text?
To give the impression of expertise or to suggest scientific verification of a product's quality
What do advertisers, scientists, lawyers, and social reformers use disciplinary jargon for, as mentioned in the text?
To give the impression of expertise or to suggest that scientific techniques have verified the quality of the product
What type of graph uses symbols to represent data?
Pictograph
How can the design choices of a graph affect interpretation?
They may mislead the observer
What can minimize or maximize the impression of differences in graphs?
The radius of pie graphs
What should be clearly marked in bar graphs?
The frequency dimension
Why should graphs for which no raw data are provided be ignored?
They lack clarity
What type of graph can visually distort differences among the bars?
Broken bar graph
What is one version of the fallacy of misplaced concreteness?
Inappropriately applying findings about groups expressed in terms of probabilities to individual cases
What is the key reason for being alert to the larger context within which probabilities are derived and interpreted?
To make sense of the researcher's claim
What effect might violating the assumptions behind statistical tests have on the statistic in question?
It may lead to misleading results/inferences
What should be identified if a research includes only males or females?
Research that includes only males or females should be identified as such
Why might small differences be statistically significant in large samples?
Due to the construction of sampling distributions based on certain assumptions
What is the potential problem with representing the change in handgun sales using a pictograph?
The pictograph may visually distort the actual change in sales due to the two-dimensional nature of pictures.
What is suggested as a simple corrective for potential mistakes in pictograph representations?
Analyzing the raw numbers used to create the graph.
What mistake can occur in pictograph representations with surprising frequency?
Visual distortion due to the two-dimensional nature of pictures.
What does the text recommend if the raw numbers used to create a graph are not available?
The graph should be ignored.
What is the potential consequence of failing to keep a pictograph proportional?
The visual impact may not accurately reflect the actual change in the data.
What is the primary concern when interpreting statistical significance?
Confusing it with practical significance
What is the potential consequence of media pressure on scientists and researchers?
Unjustified claims turning probabilities into certainties
Why is it important for researchers to be cautious about interpreting levels of significance?
Confusing statistical significance with practical significance
What should researchers consider when comparing groups based on research results?
Individual members within those groups may not all exhibit the same characteristics
What is the main caution researchers should exercise in hypothesis testing?
The rejection of the null hypothesis, not direct affirmation of the research hypothesis
Study Notes
Interpreting Graphs: Types and Hazards
- Graphs are spatial representations of numerical data, vividly communicating descriptive data to an audience.
- Bar graphs can be vertical or horizontal, and can also be segmented to represent parts of a whole.
- Pie graphs are constructed by dividing a circle into wedges, with the size of each wedge representing the component parts.
- Pictographs use symbols to represent data, either by a fixed size representing a specified number of objects or by varying the size of the symbol to represent variations in quantity.
- Graphic presentations of data are powerful communicators but may mislead an observer who is not alert.
- The scale chosen by the designer affects the appearance of the graph and may affect how the graph is interpreted.
- Changes in the radius of pie graphs and the scale of bar graphs can minimize or maximize the impression of differences.
- The frequency dimension of bar graphs should be clearly marked, and the raw data for pie graphs and other spatial representations of data should be clearly indicated.
- Graphs for which no raw data are provided should be ignored because it is impossible to interpret their meaning.
- Broken bar graphs, with separation of bars demarked by wavy lines, can visually distort differences among the bars.
- It is important to be cautious and critically analyze the design and presentation of graphs to avoid being misled by visual impressions.
- The presenter may use scale and design choices to influence the interpretation of the data.
Correlation and Causation
- High positive correlation doesn't necessarily indicate causation, as seen in the relationship between the number of fire trucks and damage in a fire.
- Significant correlations can result from using different measurements of the same phenomenon, leading to spurious correlations.
- Scientists and researchers may make unjustified claims due to pressure from the media and public, turning probabilities into certainties.
- Hypothesis testing typically involves the rejection of the null hypothesis, not direct affirmation of the research hypothesis.
- Researchers should consider formulating multiple alternative hypotheses and be cautious of type I and type II errors in inference.
- Statistical significance should not be confused with practical significance, as very small differences can achieve high confidence levels.
- Probabilities in science never reach 100% certainty and pertain to groups of entities, not individual constituents.
- When comparing groups based on research results, it's important to remember that individual members within those groups may not all exhibit the same characteristics.
- Careful conceptual analysis and definitional precision are crucial to avoid misleading correlations.
- The media's demand for quick sound bites can lead to oversimplification of scientific findings and the neglect of the tentative nature of science.
- Researchers should be cautious about interpreting levels of significance and remain aware that probabilities always apply to what will happen in the long run.
- Shifting to a new unit of analysis without retaining probabilistic language is a mistake, as probabilities apply to specific units of analysis for which they were derived.
Test your understanding of graph interpretation with this quiz. Learn about various types of graphs such as bar graphs, pie graphs, and pictographs, and how to avoid being misled by visual impressions. Explore the impact of scale and design choices on data interpretation to enhance your analytical skills.
Make Your Own Quizzes and Flashcards
Convert your notes into interactive study material.
Get started for free
