a) State the mean, standard deviation, minimum and maximum value for the independent and dependent variables. b) Sketch a scatter diagram and regression line for the data. c) Interpret the meaning of the intercept and slope in this problem. d) Evaluate the regression model (good or not) by assessing the regression model assumptions as follows: - residuals variances are similar - residuals are normally distributed - residuals are independent each other – existence of significant outliers Those assumptions can be assessed by plotting residuals vs predicted dependent variable (from the model), residual vs independent variable and/or residuals vs frequency for each data points.
a) State the mean, standard deviation, minimum and maximum value for the independent and dependent variables. b) Sketch a scatter diagram and regression line for the data. c) Interpret the meaning of the intercept and slope in this problem. d) Evaluate the regression model (good or not) by assessing the regression model assumptions as follows: - residuals variances are similar - residuals are normally distributed - residuals are independent each other – existence of significant outliers Those assumptions can be assessed by plotting residuals vs predicted dependent variable (from the model), residual vs independent variable and/or residuals vs frequency for each data points.
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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Please answer as professional way
Transcribed Image Text:a) State the mean, standard deviation, minimum and maximum value for the independent and
dependent variables.
b) Sketch a scatter diagram and regression line for the data.
c) Interpret the meaning of the intercept and slope in this problem.
d) Evaluate the regression model (good or not) by assessing the regression model assumptions
as
follows:
- residuals variances are similar
- residuals are normally distributed
- residuals are independent each other - existence of significant outliers
Those assumptions can be assessed by plotting residuals vs predicted dependent variable (from
the model), residual vs independent variable and/or residuals vs frequency for each data points.
Use excel about your answers
11:44 ✓/
Transcribed Image Text:a) 30 Data of Nuclear Generation by Country 2021.
Country
Region
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
USA
China
France
Russia
South Korea
Canada
Ukraine
Germany
Spain
Sweden
UK
Japan
India
Belgium
Czech
Republic
Switzerland
Finland
Bulgaria
Hungary
Brazil
South Africa
Mexico
Romania
Argentina
Pakistan
Slovenia
Netherlands
Amenia
UAE
Belarus
North America
Asia
Central Europe
Russia
Asia
North America
Russia
Central Europe
Central Europe
Central Europe
Central Europe
Asia
Asia
Central Europe
East Europe and
Russia
Central Europe
Central Europe
Russia
Russia
South America
Africa
North America
Russia
South America
Asia
Central Europe
Central Europe
Russia
Middle East
Russia
Year
1970-2021
1974-2021
1970-2021
1977-2021
1974-2021
1970-2021
1977-2021
1970-2021
1970-2021
1970-2021
1970-2021
1974-2021
1974-2021
1970-2021
1977-2021
1970-2021
1970-2021
1977-2021
1977-2021
1980-2021
1973-2021
1970-2021
1977-2021
1980-2021
1974-2021
1970-2021
1970-2021
1977-2021
2019-2021
1977-2021
Nuclear
Generation
(GWe)
95.8
53.3
61.4
27.7
24.4
13.6
13.1
65.7
7.1
6.9
5.9
31.7
6.8
5.9
3.9
3.0
4.4
2.0
1.9
1.9
1.9
1.6
1.3
1.6
3.3
0.7
0.5
0.4
4.0
2.2
Electricity
Production
(TWh)
789.9
344.7
338.7
200
150
90
70
60
55
49
49
47
45
40
38
35
35
30
30
30
28
28
25
25
25
20
25
20
5
1
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VIEWStep 3: Construct the scatter plot and regression line for the given data.
VIEWStep 4: Perform the regression analysis using excel.
VIEWStep 5: Perform the global test for the overall significance of the regression model.
VIEWStep 6: Check the assumptions for the regression model using residuals vs independent variable.
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