Research Methods and Statistics [GATE (Graduate Aptitude Test in Engineering) Psychology (XH-C5)]: Questions 311 - 315 of 436

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Question 311

Appeared in Year: 2012

Question MCQ▾

How many interactions can be studied in a factorial design? (December)

Choices

Choice (4)Response

a.

4

b.

30

c.

5

d.

29

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Question 312

Appeared in Year: 2012

Question MCQ▾

A test of Abstract thinking had the norms in terms of normalized T scores (mean ) the subject received a T score of 60, what would be his percentile rank? (June)

Choices

Choice (4)Response

a.

84

b.

16

c.

66

d.

60

Edit

Question 313

Question MCQ▾

Vijay obtained a percentile rank of 16 on Abstract Reasoning Test. If normalized T scores

(Mean = 50, SD = 10) were developed for this test, what is the expected T score for Vijay?

Choices

Choice (4)Response

a.

45

b.

16

c.

40

d.

34

Edit

Question 314

Question MCQ▾

Which one of the following is not the purpose of designing an experiment?

Choices

Choice (4)Response

a.

To control error variance

b.

To study the influence of extraneous variance

c.

To maximize experimental variance

d.

To investigate the effect of independent variable

Edit

Passage

Read the given passage and answer the five questions which follow:

A researcher wanted to predict academic achievement using intelligence Test - A (IT-A) , Intelligence Test B (IT-B) , Type of school (rural/urban) , and conscientiousness as predictors. She used multiple regression analysis. She collected data on 200 students on all variables. The OLS estimator was used. The , for the entire model. In individual predictor analysis, lT- B was the insignificant predictor. The suitable test indicated homoscedasticity. The model and adjucted . Both intelligence tests are significantly correlated with the criterion variable and with each other.

Question 315 (1 of 2 Based on Passage)

Appeared in Year: 2020

Question MCQ▾

Which of the following is the reason for insignificance of IT-B?

Choices

Choice (4)Response

a.

Poor predictive power

b.

Heteroscedasticity

c.

Multicollinearity

d.

Small sample size

Edit