ETS Statistical Analysis 5

Question 1

Which of the following best describes a lurking variable in statistical analysis?

Accepted Answer

An unmeasured variable that influences the relationship between two studied variables

Answer

A lurking (confounding) variable is an unmeasured variable that affects both the independent and dependent variables, potentially creating a spurious association.

Question 2

The central limit theorem states that as sample size increases, the sampling distribution of the mean approaches:

Accepted Answer

A normal distribution regardless of population shape

Answer

The central limit theorem holds that the sampling distribution of the sample mean becomes approximately normal as n increases, regardless of the population's shape.

Question 3

In hypothesis testing, statistical power is defined as:

Accepted Answer

The probability of correctly rejecting a false H₀

Answer

Power = 1 − β, where β is the probability of a Type II error; it is the probability of correctly detecting a false null hypothesis.

Question 4

A box plot shows the following five-number summary: Min=10, Q1=20, Median=30, Q3=45, Max=80. Using the 1.5×IQR rule, what is the upper outlier fence?

Accepted Answer

82.5

Answer

IQR = Q3 − Q1 = 45 − 20 = 25; upper fence = Q3 + 1.5×IQR = 45 + 37.5 = 82.5, so values above 82.5 are outliers; the lower fence = Q1 − 1.5×IQR = 20 − 37.5 = −17.5.

Question 5

Multicollinearity in multiple regression refers to:

Accepted Answer

High correlation among the independent predictor variables

Answer

Multicollinearity occurs when two or more predictor variables are highly correlated with each other, making it difficult to isolate their individual effects.

(ETS) Educational Testing Service Practice Test

(ETS) Educational Testing Service Practice Test

ETS Statistical Analysis 5