There are strengths and weaknesses to graphical analysis research techniques. For this discussion, begin by reviewing the technique of graphical analysis in your textbook. Then, keeping this technique in mind, read the following quotes:
- “Errors using inadequate data are much less than those using no data at all.”—Charles Babbage
- “Statistics is the science of variation.”—Douglas M. Bates (1985)
- “All models are wrong, but some models are useful.”—George E. P. Box (1979)
- The greatest moments are those when you see the result pop up in a graph or in your statistics analysis – that moment you realize you know something no one else does and you get the pleasure of thinking about how to tell them.—Emily Oster
Also consider the following ways to make a graph misleading from Misleading Graphs (Links to an external site.) (Passy, 2012):
- “Vertical scale is too big or too small.
- Vertical axis skips numbers, or does not start at zero.
- Graph is not labeled properly.
- Graph does not have a title to explain what it is about.
- Data is left out.
- Scale not starting at zero.
- Scale made in very small units to make graph look very big.
- Scale values or labels missing from the graph.
- Incorrect scale placed on the graph.
- Pieces of a pie chart are not the correct sizes.
- Oversized volumes of objects that are too big for the vertical scale differences they represent.
- Size of images used in pictographs being different for the different categories being graphed.
- Graph being a non-standard size or shape.”
Based on the above quotes, along with this week’s assigned readings and Instructor Guidance, compare graphical analysis with quantitative analysis (a technique you explored last week), and discuss why graphical analysis is important in research. Finally, describe guidelines for using graphical tools to present information clearly and effectively.
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