a. According to Fisher Equation “a rise in inflation also rises the nominal interest rate by the same amount”. Construct a regression model by determining dependent and independent variables according to this theory
a. According to Fisher Equation “a rise in inflation also rises the nominal interest rate by the same amount”. Construct a regression model by determining dependent and independent variables according to this theory
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Question
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2.9 |
2.4 |
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a. According to Fisher Equation “a rise in inflation also rises the nominal interest rate by the same amount”. Construct a regression model by determining dependent and independent variables according to this theory.
Transcribed Image Text:TABLE D.2
Example
Pr (t > 2.086) = 0.025
Pr (t > 1.725) = 0.05
Pr (It| > 1.725) = 0.10
Percentage Points of
the t Distribution
for df = 20
0.05
%3D
Source: From E. S. Pearson and
H. O. Hartley, eds., Blometrika
Tables for Stattstictans, vol. 1,
3d ed., table 12, Cambridge
University Press, New York,
1966. Reproduced by
1.725
permission of the editors and
0.25
0.10
0.20
Pr
0.05
0.025
0.01
0.005
0.001
trustees of Blometrika.
df
0.50
0.10
0.05
0.02
0.010
0.002
1
1.000
3.078
6.314
12.706
31.821
63.657
318.31
0.816
1.886
1.638
2.920
4.303
6.965
4.541
9.925
22.327
3
0.765
2.353
2.132
3.182
5.841
10.214
0.741
1.533
2.776
3.747
4.604
7.173
5
0.727
1.476
2.015
2.571
3.365
4.032
5.893
0.718
1.440
1.943
2.447
3.143
3.707
5.208
0.711
1.415
1.895
2.365
2.998
3.499
4.785
1.397
1.383
8
0.706
1.860
2.306
2.896
3.355
4.501
0.703
1.833
2.262
2.821
3.250
4.297
10
0.700
1.372
1.812
2.228
2.764
3.169
4.144
11
0.697
1.363
1.796
2.201
2.718
3.106
4.025
1.356
1.350
12
0.695
1.782
2.179
2.681
3.055
3.930
13
0.694
1.771
2.160
2.650
3.012
3.852
14
0.692
1.345
1.761
2.145
2.624
2.977
3.787
15
0.691
1.341
1.753
2.131
2.602
2.947
3.733
16
0.690
1.337
1.746
2.120
2.583
2.921
3.686
17
18
0.689
1.333
1.740
2.110
2.567
2.898
3.646
0.688
1.330
1.734
2.101
2.552
2.878
3.610
19
0.688
1.328
1.729
2.093
2.539
2.861
3.579
20
0.687
2.845
1.325
1.323
1.321
1.725
2.086
2.528
3.552
21
0.686
1.721
2.080
2.518
2.831
3.527
22
0.686
1.717
2.074
2.508
2.819
3.505
23
0.685
1.319
1.714
2.069
2.500
2.807
3.485
24
0.685
1.318
1.711
2.064
2.492
2.797
3.467
25
0.684
1.316
1.708
2.060
2.485
2.787
2.779
3.450
26
0.684
1.315
1.706
2.056
2.479
3.435
27
0.684
1.314
1.703
2.052
2.473
2.771
3.421
28
0.683
1.313
1.311
1.701
2.048
2.467
2.763
3.408
29
0.683
1.699
2.045
2.462
2.756
3.396
30
0.683
1.310
1.697
2.042
2.457
2.750
3.385
40
60
0.681
1.303
1.684
2.021
2.423
2.704
3.307
0.679
1.296
1.671
2.000
2.390
2.660
3.232
2.358
2.326
120
0.677
1.289
1.658
1.980
2.617
3.160
0.674
1.282
1.645
1.960
2.576
3.090
00
Note: The smaller probability shown at the head of each column is the area in one tail;
both tails.
larger probability
he area in
Transcribed Image Text:TABLE D.3 Upper Percentage Points of the F Distribution
Example
Pr(F > 1.59) = 0.25
2.42) = 0.10
Pr (F > 3.14) = 0.05
5% area
Pr (F
for df N = 10
1% area
and N2 = 9
Pr (F
> 5.26) = 0.01
F
3.14 5.26
df for
denom-
df for numerator N,
Inator
N2
Pr
2
4
6 7
8.
9.
10
11
12
.25
5.83
7.50
8.20
8.58
8.82
8.98
9.10
9.19
9.26
9.32
9.36
9.41
1
.10
39.9
49.5
53.6
55.8
57.2
58.2
58.9
59.4
59.9
60.2
60.5
60.7
.05 161
200
216
225
230
234
237
239
241
242
243
244
.25
2.57
3.00
3.15
3.23
3.28
3.31
3.34
3.35
3.39
3.37
9.38
3.38
3.39
8.53
18.5
2
.10
9.00
9.16
9.24
9.29
9.33
9.35
9.37
9.39
9.40
9.41
.05
01
19.0
19.2
19.2
19.3
19.3
19.4
19.4
19.4
19.4
19.4
19.4
98.5
99.0
99.2
99.2
99.3
99.3
99.4
99.4
99.4
99.4
99.4
99.4
.25
2.02
2.28
2.36
2.39
2.41
2.42
2.43
2.44
2.44
2.44
2.45
2.45
5.54
5.46
9.55
5.25
8.85
27.5
5.24
5.23
8.79
27.2
.10
5.39
5.34
5.31
5.28
5.27
5.22
5.22
9.28
9.01
28.2
.05
10.1
9.12
8.94
8.89
8.81
8.76
8.74
.01
34.1
30.8
29.5
28.7
27.9
27.7
27.3
27.1
27.1
25
1.81
2.00
2.05
2.06
4.11
2.07
2.08
2.08
2.08
2.08
2.08
2.08
2.08
.10
4.54
4.32
4.19
4.05
4.01
3.98
3.95
3.94
3.92
3.91
3.90
.05
7.71
6.94
6.59
6.39
6.26
6.16
5.96
5.94
6.09
15.0
6.04
6.00
5.91
.01
21.2
18.0
16.7
16.0
15.5
15.2
14.8
14.7
14.5
14.4
14.4
.25
1.69
1.85
1.88
1.89
1.89
1.89
1.89
1.89
1.89
1.89
1.89
1.89
.10
4.06
3.78
3.62
3.52
3.45
3.40
3.37
3.34
3.32
3.30
3.28
3.27
.05
6.61
5.79
5.41
5.19
5.05
4.95
4.88
4.82
4.77
4.74
4.71
4.68
.01
16.3
13.3
12.1
11.4
11.0
10.7
10.5
10.3
10.2
10.1
9.96
9.89
.25
1.62
1.76
1.78
1.79
1.79
1.78
1.78
1.78
1.77
1.77
1.77
1.77
3.05
3.01
2.96
4.10
.10
3.78
3.46
3.29
3.18
3.11
2.98
2.94
2.92
2.90
.05
5.99
5.14
4.76
4.53
4.39
4.28
4.21
4.15
4.06
4.03
4.00
01
13.7
10.9
9.78
9.15
8.75
8.47
8.26
8.10
7.98
7.87
7.79
7.72
.25
1.57
1.70
1.72
1.72
1.71
1.71
1.70
1.70
1.69
1.69
1.69
1.68
7
10
3.59
3.26
3.07
2.96
2.88
2.83
2.78
2.75
2.72
2.70
2.68
2.67
4.35
4.12
3.79
.05
.01
5.59
4.74
3.97
3.87
7.19
3.73
3.68
3.64
3.60
3.57
12.2
9.55
8.45
7.85
7.46
6.99
6.84
6.72
6.62
6.54
6.47
25
1.54
1.66
1.67
1.66
1.66
1.65
1.64
1.64
1.63
1.63
1.63
1.62
2.62
3.50
8.
.10
3.46
3.11
2.92
2.81
2.73
2.67
2.59
2.56
2.54
2.52
2.50
.05
5.32
4.46
4.07
3.84
3.69
3.58
3.44
3.39
3.35
3.31
3.28
.01
11.3
8.65
7.59
7.01
6.63
6.37
6.18
6.03
5.91
5.81
5.73
5.67
1.63
1.63
2.69
1.61
2.55
1.60
2.51
25
1.51
1.62
1.62
1.60
1.59
1.59
1.58
1.58
2.42
3.14
.10
3.36
3.01
2.81
2.61
2.47
2.44
2.40
2.38
05
5.12
4.26
3.86
3.63
3.48
3.37
3.29
3.23
3.18
3.10
3.07
.01
10.6
8.02
6.99
6.42
6.06
5.80
5.61
5.47
5.35
5.26
5.18
5.11
Source: From E. S. Pearson and H. O. Hartley, eds., Biometrika Tables for Statisticians, vol. 1, 3d ed., table 18, Cambridge University Press, New York, 1966.
Reproduced by permission of the editors and trustees of Biometrika.
3.
6.
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