Hypothesis Testing Multiple Regressions | FInancial Risk Manager Tutorial Videos| FRM Certification Video Lecture | Risk Management: An Essential Training - Management

simply learn your pace your place
financial risk manager frm pub one of
the frm exam covers the fundamental
tools and techniques used in risk
management and the theories that
underlie their use hypothesis testing
multiple regression after learning about
multiple regression let us now learn to
test the significance of the
coefficients with the help of a
hypothesis test in this session we will
learn how to test the significance of
the coefficients individually as well as
jointly will introduce another statistic
called the F statistic let us begin our
discussion by briefly outlining the
topics that will be covered agenda the
primary agenda of this discussion will
be testing the model for significance of
the coefficients that is whether the
coefficients are making a significant
impact on the dependent variable or not
we will divide the session into two
parts first we'll discuss the
significance individually through a
t-test or by using P values in the
second part we will jointly test if any
one of the coefficients is making a
significant impact on the value of the
dependent variable finally we will learn
briefly about restrictive models and
Miss specification they can occur in the
model
hypothesis testing individual
coefficient test let us apply the
concept of hypothesis testing that we
have learned earlier in testing the
significance of the coefficients of the
regression model all coefficients are
not always significant that is the
independent variables that are included
in the regression model might not always
have a significant impact on the
dependent variable to test the
significance as a given probability
confidence we apply the concept of
hypothesis testing as explained earlier
the main concept is testing if the
hypothesized value lies within the
confidence interval of the estimated
coefficient alternatively we can also
calculate the test statistic and
compared with the critical value let us
discuss these tests in more detail in
the first method we calculate the test
statistic for the estimated coefficient
this is done by subtracting the
hypothesized value from the estimated
coefficient and dividing it by the
standard error of the coefficient we now
compared the test statistic with the
critical value of the statistic used
here we use the t-test so we will
compare it with a critical t-value at
the given confidence probability you may
recall