passed 2025/2026
1. The residuals from a linear regression model True
can be used to check the underlying
assumptions and to in- vestigate model
adequacy.
2. The standard method for estimating the parameters
in true a simple linear regression model is the
method of least squares
3. A fitted linear regression model is yhat=10+2x. yi-yhat
If x = 1 and the corresponding observed ->(11-(10+2*1))=-1
value of y = 11, the residual at this
observation is:
True
4. If both the response and regressor variables
are ran- dom variables, we can calculate a
correlation coef- ficient that reflects the
linear relationship between these two
variables. false (also need B0)
5. The correlation coefficient and the slope
provide equivalent information in simple If S is the sample space,
linear regression. then the P(S) = 0
6. Which of the following is not true?
The set of all possible
If S is the sample space, then the P(S) = 0
out- comes of a random
Probabilities are numbers in the [0,1] interval.
exper-
A continuous random variable is one with an
interval of real numbers for its range.
discrete sample space can be made up of a finite set
A
the sample iment is called
of outcomes.
All of these options are not true.
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,7. Events are said to be independent when space and is denoted
the occur- rence of one event does not by the letter .5F
affect the probability of another.
true
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, IEE 380
Study online at https://quizlet.com/_8z7l6n
8. A random variable is a function that assigns a
probabil- false
ity to each outcome in the sample space of a random
experime
nt. A random variable is
a function that assigns a
real number to each
outcome in the
sample space of a
random experiment.
9. If two events are independent of one another then the FALSE -
mutually exclusive
probability of their intersection is zero. has intersection of zero
10. An experiment that results in the same outcome when False
replicated is referred to as a random experiment.
11. A random variable is said to be discrete if it False
has an infinite number of values in a finite
interval of its range.
A discrete random
vari- able is one with a
finite or countably
infinite range. Its
values are obtained by
counting.
A continuous random
vari- able is one with
an interval (either finite
or infinite) of real
numbers for its range.
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