BSTAT 2305 FINAL PRACTICE TEST 2026
TESTED QUESTIONS WITH VERIFIED
ANSWERS GRADED A+
⩥ _______ correlation can make two variables appear closely related
when no casual relation exists. Answer: Spurious
⩥ The actual value y may differ from the expected value E(y).
Therefore, we add a ______ ____ term ε to develop a simple linear
regression model. Answer: random error
⩥ With regression analysis, we explicitly assume that one variable,
called the _______ variable, is influenced by other variable, called the
explanatory variable. Answer: response
⩥ The relationship between the response variable and the explanatory
variables is _________ if the value of the response variable is uniquely
determined by the explanatory variables. Answer: deterministic
⩥ The _______ regression model allows us to study how the response
variable is influenced by two or more explanatory variables. Answer:
multiple
,⩥ The numerical measure that gauges dispersion from the sample
regression equation is the sample _______ of the residual. Answer:
Variance
⩥ We use ______ to derive the coefficient of determination. Answer:
analysis of variance (ANOVA)
⩥ If _____ is substantially greater than zero and the number of
explanatory variables is large compared with sample size, then the
adjusted R2 will differ substantially from R2. Answer: error sum of
squares (SSE)
⩥ Which of the following identifies the range for a correlation
coefficient? Answer: None of these choices is correct.
⩥ A correlation coefficient r = −0.85 could indicate a
_______________________________. Answer: Very strong
NEGATIVE
linear relationship
⩥ The following scatterplot indicates that the relationship between the
two variables x and y is ______________.
(going up right) ----> / Answer: strong and positive
,⩥ The following scatterplot indicates that the relationship between the
two variables x and y is _______________.
(Down right) -----> \ Answer: Strong and NEGATIVE
⩥ Which of the following statements is the least accurate concerning
correlation analysis? Answer: The correlation coefficient describes both
the direction and strength of the relationship between two variables only
if
the two variables have same units of measurement.
⩥ When testing whether the correlation coefficient differs from zero, the
value of the test statistic is t20 = 1.95 with a corresponding p-value of [
0.0653 ]
At the 5% significance level, can you conclude that the correlation
coefficient differs from zero? Answer: No, since the p-value exceeds
0.05.
⩥ When testing whether the correlation coefficient differs from zero, the
value of the test statistic is t20 = -2.95 with a corresponding p-value of [
0.0061 ]
, At the 5% significance level, can you conclude that the correlation
coefficient differs from zero? Answer: Yes, since the p-value is less than
0.05.
⩥ Calculate the value of R2 given the ANOVA portion of the following
regression output: Answer: .151
⩥ The sample standard deviations for x and y are 10 and 15,
respectively. The covariance between x and y is −120. The correlation
coefficient between x and y is _____. Answer: -0.8
⩥ The variance of the rates of return is 0.25 for stock X and 0.01 for
stock Y. The covariance between the returns of X and Y is -0.01. The
correlation of the rates of return between X and Y is _____. Answer: -
0.20
⩥ Simple linear regression analysis differs from multiple regression
analysis in that
__________________________________________________________
_. Answer: simple linear regression uses only one explanatory variable
⩥ A regression equation was estimated as = -100 + 0.5x. If x = 20,the
predicted value of y is _____. Answer: -90
TESTED QUESTIONS WITH VERIFIED
ANSWERS GRADED A+
⩥ _______ correlation can make two variables appear closely related
when no casual relation exists. Answer: Spurious
⩥ The actual value y may differ from the expected value E(y).
Therefore, we add a ______ ____ term ε to develop a simple linear
regression model. Answer: random error
⩥ With regression analysis, we explicitly assume that one variable,
called the _______ variable, is influenced by other variable, called the
explanatory variable. Answer: response
⩥ The relationship between the response variable and the explanatory
variables is _________ if the value of the response variable is uniquely
determined by the explanatory variables. Answer: deterministic
⩥ The _______ regression model allows us to study how the response
variable is influenced by two or more explanatory variables. Answer:
multiple
,⩥ The numerical measure that gauges dispersion from the sample
regression equation is the sample _______ of the residual. Answer:
Variance
⩥ We use ______ to derive the coefficient of determination. Answer:
analysis of variance (ANOVA)
⩥ If _____ is substantially greater than zero and the number of
explanatory variables is large compared with sample size, then the
adjusted R2 will differ substantially from R2. Answer: error sum of
squares (SSE)
⩥ Which of the following identifies the range for a correlation
coefficient? Answer: None of these choices is correct.
⩥ A correlation coefficient r = −0.85 could indicate a
_______________________________. Answer: Very strong
NEGATIVE
linear relationship
⩥ The following scatterplot indicates that the relationship between the
two variables x and y is ______________.
(going up right) ----> / Answer: strong and positive
,⩥ The following scatterplot indicates that the relationship between the
two variables x and y is _______________.
(Down right) -----> \ Answer: Strong and NEGATIVE
⩥ Which of the following statements is the least accurate concerning
correlation analysis? Answer: The correlation coefficient describes both
the direction and strength of the relationship between two variables only
if
the two variables have same units of measurement.
⩥ When testing whether the correlation coefficient differs from zero, the
value of the test statistic is t20 = 1.95 with a corresponding p-value of [
0.0653 ]
At the 5% significance level, can you conclude that the correlation
coefficient differs from zero? Answer: No, since the p-value exceeds
0.05.
⩥ When testing whether the correlation coefficient differs from zero, the
value of the test statistic is t20 = -2.95 with a corresponding p-value of [
0.0061 ]
, At the 5% significance level, can you conclude that the correlation
coefficient differs from zero? Answer: Yes, since the p-value is less than
0.05.
⩥ Calculate the value of R2 given the ANOVA portion of the following
regression output: Answer: .151
⩥ The sample standard deviations for x and y are 10 and 15,
respectively. The covariance between x and y is −120. The correlation
coefficient between x and y is _____. Answer: -0.8
⩥ The variance of the rates of return is 0.25 for stock X and 0.01 for
stock Y. The covariance between the returns of X and Y is -0.01. The
correlation of the rates of return between X and Y is _____. Answer: -
0.20
⩥ Simple linear regression analysis differs from multiple regression
analysis in that
__________________________________________________________
_. Answer: simple linear regression uses only one explanatory variable
⩥ A regression equation was estimated as = -100 + 0.5x. If x = 20,the
predicted value of y is _____. Answer: -90
