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# CSC 595 Lecture #5 Hypothesis & Argument formulation PowerPoint PPT Presentation

CSC 595 Lecture #5 Hypothesis & Argument formulation. Reference Book: Justin Zobel , Writing For Computer Science, 2 nd Ed. Springer, 2004. Dr. Manar Hosny. The Literature Review Model. Addresses. Step 3. Develop the Argument. Step 4. Survey the Literature. Step 6.

CSC 595 Lecture #5 Hypothesis & Argument formulation

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## CSC 595Lecture #5Hypothesis & Argument formulation

Reference Book:

Justin Zobel, Writing For Computer Science, 2nd Ed. Springer, 2004

Dr. ManarHosny

### The Literature Review Model

Step 3.

Develop the Argument

Step 4.

Survey the Literature

Step 6.

Write the Review

Step 1.

Select a topic

Step 2.

Search the Literature

Step 5.

Critique the Literature

Specifies and frames

Documents and discovers

Explores and catalogs

Organizes and forms

### Hypothesis

• The first stages of a research involve identifying a specific issue to investigate develop a specific question to answer

• For example, how something works, interacts, or behaves

• This forms a hypothesis of your research

• In computer science a hypothesis is usually about whether a proposed approach is fit for a certain purpose

### Hypothesis

• For example, a research hypothesis may be: “Using algorithm X we can reduce the number of memory accesses and make the program faster”

• Another research hypothesis may be: “Sorting algorithm Y can be improved if we replace a tree-based structure with an array-based structure”

• The goal of the research will be to test this hypothesis

• The hypothesis should be clear, precise and unambiguous

• Often is important to state what is not being proposed (the limitations of the hypothesis)

### Hypothesis

• Consider that there are two data structures: P-List, and Q-List and you believe that Q-list is superior to P-lists

• Now consider the following hypotheses:

• Q-lists are superior to P-lists

• Wrong Hypothesis (un-testable) Success has to apply in all applications, in all conditions, for all times

• As an in-memory search structure for large data-sets, Q-lists are faster and more compact than P-lists

• Good Hypothesis (testable) the scope is limited to a domain that can feasibly be explored

### Hypothesis

• Another important factor is that the hypothesis must not be vague

• Q-List performance is comparable to P-List performance

• Vague Hypothesis

• Our proposed query language is relatively easy to learn

• Vague Hypothesis

### Hypothesis

• Sometimes you need to refine the hypothesis as a result of initial testing

• However, this does not mean that the hypothesis should follow the experiment

• The hypothesis makes a prediction

• The hypothesis is confirmed if the prediction is successful

• Tests should be blind

• If the experiment has been fine-tuned to fit the hypothesis, we cannot say that the experiment confirmed the hypothesis

### Defending Hypotheses

• As part of the research process, you need to test your hypothesis and assemble supporting evidence.

• The argument relates your hypothesis to the evidence.

• In constructing an argument, imagine that you want to defend your hypothesis to a colleague and convince her that your hypothesis is correct.

• Rebut likely objections

• Admit when you are not certain

• Search for counter examples

### Defending Hypotheses

• For example if you want to defend the hypothesis

that “algorithm X is faster than algorithm Y”, your argument can be:

• Since the complexity of algorithm X is O(log2n) and the complexity of algorithm Y is O(n)  algorithm X is faster than argument Y

• A hypothesis may be wrong.

• In that case, DO NOT cling to it and twist the results to defend it

### Evidence

• There are 4 types of evidence that can be used to support your hypothesis:

• An analysis or proof (e.g. complexity analysis)

• A model: a mathematical description of the hypothesis

• A simulation: an implementation or partial implementation of simplified form of the hypothesis, done in a tightly controlled environment

• An experiment: a full test of the hypothesis, based on real data