# Center for Analysis and Design of Intelligent Agents

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public:rem4:rem4-18:hypotheses_method_execution

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public:rem4:rem4-18:hypotheses_method_execution [2018/02/06 12:37]
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-===== Results & Conclusions =====
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|  This is your stuff  | Make it look **as good as it can look**!  | |  This is your stuff  | Make it look **as good as it can look**!  |

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-====Results==== +==== Hypotheses ====
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-|  Results   | This section proves that your idea is great  | +
-|  Describe the evaluation method thoroughly but succinctly  | Nothing is more annoying than long-winded discussion of the evaluation method. Just the facts, ma'am!  | +
-|  Evaluation method description: should have a one-to-one correspondence with the results section  | This means that any table, graph, or illustration in the results should have a directly corresponding statement/motivation/ discussion in the Evaluation section. \\ If you feel like you have to include tables whose existence are not discussed -- and hence not justified -- in the evaluation section, make sure they are either motivated by a surprise finding or else put them in a Discussion section.  |+

+|  Explicitness  | Hypotheses state a predicted relation between two or three variables. Hypotheses should be stated explicitly. Null hypothesis may be stated explicitly, for clarity.  |
+|  Example  | H1: By banning ice cream sales in Central Park in the summer, muggings will be significantly reduced. (Underlying "theory": That eating ice cream impels people to mug others.)   |
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-===Presentation Data===+==== Experimental Design ====
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+|  Clarity  | Avoid ambiguous words and sentences. Structure the description of the design in a logical manner. Be straight forward - don't try to make things sound "more important" by using loaded, overblown, pompous, or otherwise baroque words or wording.     |
+|  Detail  | Give enough detail so that others can set the experiment up independently and get the same results.   |
+|  Physical  | Comparative experiments are done in physical space and time. Be explicit about the arrangement of any physical attributes of the experiment that may be important to anyone repeating your experiment.    |

-|  Be clear  | Put yourself in the shoes of the reader. Try to imagine what is essential information to grasp the findings in as short a period as possible. \\ Select the form for your data Tabular, line graph, bar graph, dot graph, pie chart, scatterplot
-|  Always summarize what the tables/graphs/etc. say with your own words, before drawing conclusions  | E.g.: Do not say "As can be seen in Graph 1, my routing algorithm works best." Say, "As can be seen in the comparison between the three routing algorithms, A, B and C, the algorithms with partial information about network topology have an advantage in networks above a certain size (point X, Graph 1). Among these, my algorithm, C, gets the best result."  |
-|  Captions: Equally important as the graph  | Make sure your graph contains all the information necessary to interpret the graphics: Title, caption and legend should be written with the same care as the title of your paper and your abstract!!  |
-|  Two principles  | The clearest presentation - make the job easy on the reader \\ The biggest impact - try to make the point as strongly as you possibly can.  |
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-===Data Presentation for Human Consumption===
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-|  Scientific papers are for people  | People have limited capacity processors. Make sure you direct them to the most important points through the right data/information presentation methods.  |
-|  Select the right format  | Unidimensional temporal data: 2-D graph \\ Three-dimensional data: 3-D graph from various angles \\ Multidimensional temporal data: Many 2-D graphs \\ Dynamic multidimensional data: Illustrations, examples
-|  When not to use graphs  | When the graph contains too much or too little data  |
-|  Common mistakes in graphs  | Equating two-dimensional space with one-dimensional space \\ Forget to indicate that an axis does not start at zero \\ Using pie charts for open-ended scales  [[http://www.ru.is/faculty/thorisson/courses/h2006/methodology/thorisson-6.html|examples]] (scroll down)  |
-|  9 tips to make your graphs great \\ (based on: [[http://www.statcan.ca/english/edu/power/ch9/sumgraphs/sum.htm|source]] - now defunct. [[http://flowingdata.com/2010/07/22/7-basic-rules-for-making-charts-and-graphs/|Alternative source]])  | 1. decide on a clear purpose \\ 2. convey an important message \\ 3. draw attention to the message, not the source \\ 4. experiment with various options and graph styles \\ 5. use simple design for complex data \\ 6. make the data 'speak' \\ 7. adapt graph presentation to suit the data \\ 8. ensure that the default visual perception process of the reader is easy and accurate \\ 9. avoid ambiguity  |
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-=== Conclusions ===
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-| Purpose  | Summarize what the main contribution is, with appropriate mentionings of the method, result and assumptions (and possibly motivation, if this is important) |
-| Format | Short, concise - it is different from the Abstract in that most will have read (most of) the paper when they read this section. \\    |
-| What to avoid | Repeating verbatim something that was said earlier.  \\ Being too wordy.  \\ Saying something new that should have been in a prior section.  \\ Not saying anything new (wrt the context, global conclusion, etc.).  |
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-=== Future Work ===
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-| Purpose | To help those who want to continue the work understand what **you** would do next  |
-| Format  | A few sentences on what will be the follow-up to this study. It is customary to put mentionings of future work in the Conclusions section, not to have it be a separate section.  |

-=== Example ===+==== Execution ====

-Typical format  | - Restate the problem/challenge (1-2 sentences) \\ - Restate what you did (1 sentence) \\ - Draw up the main conclusion, refer to your results \\ - Comment on the implications \\ - Tell them what would be done next |+ Sequential  | Physical actions are sequential. Describe the sequence of events when executing the experiment.    |
+|  Same as above  | All relevant aspects of the general pointers above about clarity and detail apply here as well.

-=== Acknowledgment ===

-| Purpose | To thank people, funding agencies, etc. that should be acknowledged but are not appropriate to list as co-authors.  |
-| Format | Comes after Results, Conclusion.  |

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