Statics Measures Interview Preparation Guide
Strengthen your Statics Measures interview skills with our collection of 29 important questions. Each question is crafted to challenge your understanding and proficiency in Statics Measures. Suitable for all skill levels, these questions are essential for effective preparation. Secure the free PDF to access all 29 questions and guarantee your preparation for your Statics Measures interview. This guide is crucial for enhancing your readiness and self-assurance.29 Statics Measures Questions and Answers:
1 :: What sort of data is appropriate for chi square tests?
1. Scaled scores.
2. Rank ordered data.
3. Continuous scores.
4. Frequency counts
Answer: Frequency counts
2. Rank ordered data.
3. Continuous scores.
4. Frequency counts
Answer: Frequency counts
2 :: Using a goodness of fit we can test whether a set of obtained frequencies differ from a set of ______ frequencies?
1. Expected
2. Observed
3. Constant
4. Independent
Answer: expected
2. Observed
3. Constant
4. Independent
Answer: expected
3 :: Which of the following hypotheses would be suited for testing by a one variable chi square test?
1. It is hypothesized that in terms of car color, more individuals choose a red car, than a green, a black, or a silver car.
2. Choice of car color is directly related to measures of extroversion.
3. Individuals with red cars are significantly more extroverted than are individuals with green, black or silver cars.
4. None of the above
Answer: It is hypothesized that in terms of car color, more individuals choose a red car, than a green, a black, or a silver car.
2. Choice of car color is directly related to measures of extroversion.
3. Individuals with red cars are significantly more extroverted than are individuals with green, black or silver cars.
4. None of the above
Answer: It is hypothesized that in terms of car color, more individuals choose a red car, than a green, a black, or a silver car.
4 :: How do we calculate the degrees of freedom for a goodness of fit test?
1. Number of categories -1.
2. Number of categories x n.
3. N/ (Number of categories-1).
4. n-1.
Answer: Number of categories -1.
2. Number of categories x n.
3. N/ (Number of categories-1).
4. n-1.
Answer: Number of categories -1.
5 :: You are conducting a one variable chi square test to test the hypothesis that there are equal numbers of vegetarians, meat eaters, and vegans eating at the student union. The categories are vegetarian, meat eaters, and vegans. Having conducted a survey, you found 85 individuals were vegetarian, 122 ate meat, and 32 followed a vegan diet. What would the expected frequencies be in each cell?
1. 239
2. 85, 122, and 32.
3. 79.67
4. There is insufficient information provided to calculate the expected frequencies.
Answer: 79.67
2. 85, 122, and 32.
3. 79.67
4. There is insufficient information provided to calculate the expected frequencies.
Answer: 79.67
6 :: Examine the output on p. 268. How would these results be reported?
1. The chi square value of 10.490 (DF=317) achieved an associated p value of <.001. There was a significant difference between the expected and the observed frequencies. We can conclude that there is a greater prevalence of right handedness in women with IBS.
2. The chi square value of 317 (DF=1) achieved an associated p value of <.001. There was a significant difference between the expected and the observed frequencies. We can conclude that there is a greater prevalence of left handedness in women with IBS.
3. The chi square value of 10.490 (DF=1) achieved an associated p value of .001. There was no significant difference between the expected and the observed frequencies. We can conclude that being left or right handed is unrelated to IBS in women.
4. The chi square value of 10.490 (DF=1) achieved an associated p value of <.001. There was a significant difference between the expected and the observed frequencies. We can conclude that there is a greater prevalence of left handedness in women with IBS.
Answer: The chi square value of 10.490 (DF=1) achieved an associated p value of <.001. There was a significant difference between the expected and the observed frequencies. We can conclude that there is a greater prevalence of left handedness in women with IBS.
2. The chi square value of 317 (DF=1) achieved an associated p value of <.001. There was a significant difference between the expected and the observed frequencies. We can conclude that there is a greater prevalence of left handedness in women with IBS.
3. The chi square value of 10.490 (DF=1) achieved an associated p value of .001. There was no significant difference between the expected and the observed frequencies. We can conclude that being left or right handed is unrelated to IBS in women.
4. The chi square value of 10.490 (DF=1) achieved an associated p value of <.001. There was a significant difference between the expected and the observed frequencies. We can conclude that there is a greater prevalence of left handedness in women with IBS.
Answer: The chi square value of 10.490 (DF=1) achieved an associated p value of <.001. There was a significant difference between the expected and the observed frequencies. We can conclude that there is a greater prevalence of left handedness in women with IBS.
7 :: Although in one variable chi square testing each participant cannot be in more than one group, in a 2x2 chi square test, this rule does not apply?
* True
* False
Answer: FALSE
* False
Answer: FALSE
8 :: 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.
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.
9 :: A fundamental assumption of chi square tests is that no more than ____ % of cells can have an expected frequency of less than?
1. 25; 5
2. 75; 95
3. 4; 1
4. 5; n
Answer: 25; 5
2. 75; 95
3. 4; 1
4. 5; n
Answer: 25; 5
10 :: 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
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