# Statics Measures

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## 29 Statics Measures Questions And Answers

### 1⟩ What is Cramers V used for?

1. Cramer’s V is used instead of X2 in analyses which are bigger than 2x2.

2. Cramer's V is used when assumptions for conducting chi square are violated.

3. Cramer's V is a measure of effect used for tests of association.

4. Cramer's V is a way of reporting the ratio between the observed and expected scores.

Answer: Cramer's V is a measure of effect used for tests of association.

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### 2⟩ For a 2x2 chi square test, which of the following equations would be used to calculate the degrees of freedom?

1. (r-1) x (c-1) x (n-1)

2. (r-c) x (n-1)

3. (r-1) x (c-1)

4. (r+1) x (c+1)

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* True

* False

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### 4⟩ One serious complication associated with the analysis of more than three levels (4 x 5) is?

1. The sample size would have to be so large that chi square analysis would not be powerful enough to interpret the data.

2. It can be difficult to interpret accurately all of the relationships within a large contingency table.

3. That type of analysis would not meet the criteria for a chi square test.

4. They would have to be analyzed by hand as SPSS has no option for tables larger than 3x3.

Answer: it can be difficult to interpret accurately all of the relationships within a large contingency table.

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### 5⟩ Should you use a one-tailed, or a two-tailed hypothesis when doing a chi square test?

1. Two-tailed.

2. It doesn't matter.

3. One-tailed.

4. SPSS will include the right one in the output.

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### 6⟩ Which of the below statements is false of chi square testing?

1. Chi square tests can be used to check how well a model fits the data

2. Chi square can be applied to continuous variables; it just means that a larger contingency table is needed.

3. Chi square is used in research to measure the association between two categorical variables.

4. None of these statements are false, it is a trick question.

Answer: Chi square can be applied to continuous variables; it just means that a larger contingency table is needed.

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1. 3x2

2. 3x3

3. 2x2

4. 3x1

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### 8⟩ What does the Fishers Exact Probability test show?

1. Fisher's Exact Probability Test shows the F statistic associated with the chi square value when the null is assumed to be true.

2. The Fisher's Exact Probability Test shows the probability of reaching the assumption of 25% of cells with an expected frequency of less than 5.

3. The Fisher's Exact Probability Test shows the percentage of variation which one variable accounts for in the other.

4. The Fisher's Exact Probability Test shows the probability of obtaining the chi square value when the null is assumed to be true.

Answer: The Fisher's Exact Probability Test shows the probability of obtaining the chi square value when the null is assumed to be true.

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### 9⟩ When reporting your results, what elements should you include from the SPSS output?

1. The number of participants, the X2 value, and the probability level

2. The Pearson's X2, degrees of freedom and the probability level.

3. The number of participants, the degrees of freedom, X2, and the probability level

4. The X2 and the probability level.

Answer: The Pearson's X2, degrees of freedom and the probability level.

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### 10⟩ What are quantitative models?

Quantitative models are frequently used in different engineering disciplines for predicting situations, due dates, required cost and so on. These quantitative models are based on some kinds of measure performed on project data or items.

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### 11⟩ What is number of inequalities?

The number of (in)equalities is the number of times that the operator is found in atomic conditions of a program.

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### 12⟩ If the assumption mentioned in question 10 is not met for a 2x2 chi square test, you should proceed to conducting _________?

1. A Pearson's correlation coefficient

2. A 2x2 test of independence

3. One variable chi square test (goodness of fit)

4. A Fisher's Exact Probability Test

Answer: a Fisher's Exact Probability Test

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1. 25; 5

2. 75; 95

3. 4; 1

4. 5; n

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### 14⟩ What is a nesting degree?

The nesting degree is the maximum number of conditional statements that are nested one inside another.

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### 15⟩ You conduct a study exploring whether or not students planned their time and whether or not they submitted their assignment on time, your SPSS output shows a value for Cramers V of 0.42. How would you interpret this?

1. 8% of the variation in frequency counts of essay submission timing (on time or late) can be explained by time planning.

2. 42% of the variation in frequency counts of essay submission timing (on time or late) can be explained by time planning.

3. 64.8% of the variation in frequency counts of essay submission timing (on time or late) can be explained by time planning.

4. 4.2% of the variation in frequency counts of essay submission timing (on time or late) can be explained by time planning.

Answer: 8% of the variation in frequency counts of essay submission timing (on time or late) can be explained by time planning.

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### 16⟩ What is a branch coverage?

branch coverage is the percentage of branches exercised in a program. This coverage measure is used in most of the related papers in the literature.

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### 17⟩ What is a cyclomatic complexity?

Cyclomatic complexity is a complexity measure of code related to the number of ways there exists to traverse a piece of code. This measure determines the minimum number of test cases needed to test all the paths using linearly independent circuits.

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### 18⟩ What is statement coverage?

Statement coverage is defined as the percentage of statements that are executed.

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### 19⟩ How is cyclomatic complexity computed?

Cyclomatic complexity is computed using the control flow graph of the program, the nodes of the graph correspond to indivisible groups of sentences of a program and a directed edge connects two nodes if the second sentence might be executed immediately after the first sentence.

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### 20⟩ What does cyclomatic complexity apply to?

Cyclomatic complexity may also be applied to individual functions, modules, methods or classes within a program, and is formally defined as follows:

v(G) = E − N + 2P

where E is the number of edges of the graph, N is the number of nodes of the graph and P is the number of connected components.

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