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by
Mrs. Dobbert
Vocabulary
Calculator
Calculations
Dobbert’s
Doozies
100
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500
Residual is the distance between the data y value and the
predicted y value.
Deviation is the difference between the data y value and
the average y value. y – “y hat”
Describe the difference between
residual and deviation.
Cite appropriate
notation.
Row 1, Col 1
Exponential
Make a scatter plot of the data.
State the type of function that models the data set.
Be prepared to share with the class.
X
1
2
3
6
7 8
9
10
Y 10643 4776 2194 637 483 371 298 222
1,2
Power or exponential
Make a scatter plot of the data.
State the type of function that
models the data set. Find the
Regression equaiton.
X
Y
100
60
200
46
500
31
700
26
1000
21
1,3
Interpolation corresponds with a value within the domain
of the data set.
Extrapolation corresponds with a value outside the
domain of the data set.
Describe the difference between
interpolation and extrapolation.
1,4
R is the correlation coefficient and describes the trend of
the data, positive or negative, strong or weak. 1  r  1
2
R2 is the coefficient of determination and describes the
percent of variability of the data accounted for by the
regression equation.
0  r 2 1

What information does r and r
provide us?
What vocabulary term is

associated with r and r 2 ?
2,1
Y = 1.924x + 13.089
Find the appropriate regression
equation for the set of data.
X
Y
10 14 16 20 25 26 30
30 40 46 54 60 63 70
2,2
792.833
Use lists on your calculator to find.
SSdev Be prepared to share with
the class.
X
Y
10 14 16 20 25 26
30 40 46 54 60 63
2,3
7.5 + 3.607lnx = y
Algebraically find the logarithmic
equation that contains the points
(2,10) and (8,15).
2,4
The centroid is the point defined by
(x-average, y-average). It is the point that always lies
on the linear regression equation.
Define centroid.
What is its significance with respect to a
linear regression equation?
3,1
Exponential
Make a residual plot to determine
if a linear or exponential equation
better models the data set.
X 0 2
Y .07 .2
4
.6
6
2
8
5
10
16
3,2
0.990
Given the data set, calculate the
coefficient of determination. Use
the definition that includes SSres
and SSdev.
X 2 4 6 8 10 12
Y 10 17 21 28 35 38
3,3
linear add-add
power
multiply-multiply
exponential add-multiply
logarithmic multiply-add.
Describe the numerical patterns
that describe linear, power,
exponential, and logarithmic
functions.
3,4
(Type the question for 4,1 here.)?
Using sigma notation, write an
Expression that express the sum of
the square of the residuals.
4,1
Yes…the points possess a random pattern.
Based on the linear residual plot, is
a linear model a good fit for the
data? Support your claim.
4,2
(Type the question for 4,3 here.)?
Find the power and exponential regression
equations. Paste the equations into y1 and y2.
Create residual plots for the power and
exponential models. Determine which model
is a better fit.
X
3
4
5
6
7
8
9
10
Y
46 41 36 31 27 24 21 18
11
15
4,3
Tuesday, December 18 @ 10:20
State the date and time of the math
Exam.
4,4
R2 = (SSdev - SSres )/SSdev
Write the expression that calculates
The coefficient of determination.
5,1
No, the plot indicated there is a function with a better fit.
The plot has a non-random pattern.
Based on the logarithmic residual
plot, is a logarithmic model a good
Fit for the data? Support your
claim.
5,2
Linear
Find the linear and exponential regression
equations. Paste the equations into y1 and y2.
Create residual plots for the linear and
exponential models. Determine which model
is a better fit.
X
Y
3
23
4
37
5
50
6
62
7
76
8
89
9
10 11
102 114 126
5,3
L3 = (L2 – mean(L2))2
Data has been entered into lists 1 and 2,
describe the rule to calculate y  y
State the rule for list 3 and any other
Calculator instructions needed.
2

5,4