QMET 251 Final Exam – Study Guide, Practice Questions & Exam
Review
70 points
all multiple choice
not cumulative
formula sheet given
Tuesday May 4th @11:00-1:30
Room Moody 106
regression and correlation analysis - correct answer ✔✔two powerful tools that show the
extent to which two or more sets of data (or variables) are related mathematically
shows NO proof of cause and effect, just because two variables are related mathematically,
does not mean that one variable causes the other variable to change
for example; if two variables (independent (X) and dependent(Y)) have a good linear or
mathematical relationship, that does not necessarily mean that X will cause Y to change
gives the decision maker a better reason
correlation - correct answer ✔✔associative tool, does not make prediction, measures strength
and direction (+ or -) of the relationship that exists between two or more variables
only two calculations: r and r^2
, regression - correct answer ✔✔predictive tool, takes past values of two or more sets of
data/variables and calculates an equation which can be used to predict future values of one of
the variables
calculating a and b and the regression equation
simple regression - correct answer ✔✔has only two sets of data; independent (x) and
dependent (Y)
multiple regression - correct answer ✔✔has more than two sets of data
Regression equation - correct answer ✔✔Y= a+b(x)
b - correct answer ✔✔also known as slope of the line/coefficient
is the expected change in Y for each one unit change in X
*always calculate first in equation, but after extra columns are made
how to interpret b - correct answer ✔✔for each # (increase/ decrease) in (independent (x)) we
expect (dependent(Y)) to (increase/ decrease) by #
if b is positive= "increasing"
if b is negative= "decreasing"
a - correct answer ✔✔also known as the "Y intercept"
Review
70 points
all multiple choice
not cumulative
formula sheet given
Tuesday May 4th @11:00-1:30
Room Moody 106
regression and correlation analysis - correct answer ✔✔two powerful tools that show the
extent to which two or more sets of data (or variables) are related mathematically
shows NO proof of cause and effect, just because two variables are related mathematically,
does not mean that one variable causes the other variable to change
for example; if two variables (independent (X) and dependent(Y)) have a good linear or
mathematical relationship, that does not necessarily mean that X will cause Y to change
gives the decision maker a better reason
correlation - correct answer ✔✔associative tool, does not make prediction, measures strength
and direction (+ or -) of the relationship that exists between two or more variables
only two calculations: r and r^2
, regression - correct answer ✔✔predictive tool, takes past values of two or more sets of
data/variables and calculates an equation which can be used to predict future values of one of
the variables
calculating a and b and the regression equation
simple regression - correct answer ✔✔has only two sets of data; independent (x) and
dependent (Y)
multiple regression - correct answer ✔✔has more than two sets of data
Regression equation - correct answer ✔✔Y= a+b(x)
b - correct answer ✔✔also known as slope of the line/coefficient
is the expected change in Y for each one unit change in X
*always calculate first in equation, but after extra columns are made
how to interpret b - correct answer ✔✔for each # (increase/ decrease) in (independent (x)) we
expect (dependent(Y)) to (increase/ decrease) by #
if b is positive= "increasing"
if b is negative= "decreasing"
a - correct answer ✔✔also known as the "Y intercept"
