Good Afternoon I have completed the requested questions on section 1 a on excel however I am having a bit of trouble analysing this data and awnsering 1 b and it's sub questions. please help me solve this sub questions (xiii) This dataset is not necessarily random. Is GNP per capita a good way to determine a country’s birth rate? Comment with reference to two countries from this dataset. The comment must be done on the work I have already done on excel.
Good Afternoon I have completed the requested questions on section 1 a on excel however I am having a bit of trouble analysing this data and awnsering 1 b and it's sub questions. please help me solve this sub questions (xiii) This dataset is not necessarily random. Is GNP per capita a good way to determine a country’s birth rate? Comment with reference to two countries from this dataset. The comment must be done on the work I have already done on excel.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Good Afternoon
I have completed the requested questions on section 1 a on excel however I am having a bit of trouble analysing this data and awnsering 1 b and it's sub questions.
please help me solve this sub questions
(xiii) This dataset is not necessarily random. Is GNP per capita a good way to determine a country’s birth rate? Comment with reference to two countries from this dataset.
The comment must be done on the work I have already done on excel.
Please help,thank you.

Transcribed Image Text:Section A
(i)
(ii)
Comment on the scatterplot: form, strength, direction, outliers.
Demonstrate how to calculate the slope of the regression line manually,
using the summary statistics you generated in excel (correlation
coefficient, standard deviation of y and standard deviation of x). Show all
workings.
Now calculate the intercept, manually. Show all workings.
Write out the regression equation, (you can check that your manual
calculations match the regression output in excel).
Form a hypothesis about the effect of GNP per capita on birth rate and
state the hypothesis. Test the hypothesis at a significance level of 0.05.
Write out the formula to calculate the T stat, and manually calculate the T
1. Data on GNP per capita and Birth Rate (births per thousand inhabitants) for a sample
of 14 countries for 2019 is displayed below:
(iii)
(iv)
GNP
Birth
Country
per cap
Rate
(v)
Bangladesh
5200
18
Tanzania
2700
36
(vi)
stat. The distribution to test for the coefficient is T distribution n-2
Sierra
degrees of freedom. Show all workings.
Leone
1770
33
(vii) Look up the T table and verify the P value. What line along the T table
should you use to check the p value for the t stat?
(viii) Write out how to calculate the residual for Nepal (you can check your
Sudan
3990
32
Kenya
4430
29
manual result matches the excel output). Show all workings.
Indonesia
11970
18
(ix)
Comment on the residual.
(x)
This is updated data for the 14 countries studied in the in-class mock
exam. Compare the regression equation from the 1980s data used in the
exam with this data from 2019 and comment on one similarity and one
difference between the two time periods.
If the GNP per capita of Malawi were to increase by US$ 1000, what
Panama
15730
19
Chile
14890
12
Venezuela
16054
18
(xi)
Turkey
Malaysia
Nepal
9120
16
would you expect its birth rate to be? Show all workings.
(xii) Using the Bsquared from the regression output calculate the correlation
coefficient manually. Show all workings.
11410
15
1070
19
(xii) This dataset is not necessarily random. Is GNP per capita a good way to
Malawi
410
34
Argentina
determine a country's birth rate? Comment with reference to two
countries from this dataset.
9910
17
Copy the data into excel. (Or use the excel file containing the data uploaded to
Moodle)
(i)
a.
Generate summary statistics for correlation coefficient and mean and
standard deviation for each variable.
(ii)
(ii)
Generate a scatterplot of birth rate vs gng per capita.
Generate the line of best fit where gng is the explanatory variable for
birth rate, the response variable.
(iv) Display equation for line of best fit on the graph.
(v)
(vi)
Display R squared on the graph.
Generate regression summary.

Transcribed Image Text:1 Country
2 Bangladesh
3 Tanzania
4 Sierra Leone
5 Sudan
6 Kenya
7 Indonesia
8 Panama
9 Chile
10 Venezuela
11 Turkey
12 Malaysia
13 Nepal
14 Malawi
15 Argentina
16
17 Mean
18 St Dev
19 Correlation Coeficient
GNP per cap Birth Rate
5200
Chart Title
y=0.0011x + 30.944
R= 0.5451
18
40
2700
36
35
1770
33
30
3990
32
25
4430
29
20
15
11970
18
10
15730
19
14890
12
16054
18
18000
2000
4000
6000
8000
10000
12000
14000
16000
9120
16
GNP per Capita
11410
15
1070
19
410
34
SUMMARY OUTPUT
9910
17
Regression Statistics
7761
22.57142857
Multiple R 0.775729
5634.950153
R Square
8.234208997
0.601755
Adjusted F 0.565551
Standard E 5.576425
Observatic
-0.738279458 -0.738279458
20
21
22
23
13
ANOVA
izificance F
24
25
26
27
28
29
30
31
of
Regression
Residual
Total
516.8614
516.8614
16.6212
0.00183
11
342.0617
12
858.9231
31.09652
Caefficienttandand En
31.90516
5200 -0.001129 0.000277
Stat
Fvalue Lower 9oper 95X.ower 950pner 950%
1.32E-07 25.98048 37.82984 25.98048 37.82984
0.00183 -0.001738 -0.000519 -0.001738 -0.000519
Intercept
2.69183
11.85259
-4.07691
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
RESIDUAL OUTPUT
CbservativFredicted Residals
1 28.85771 7.142293
2 29.90739
3.092615
27.4017 4.598297
4 26.90508
18.39479 -0.394789
2.094919
6
14.15093
4.84907
7
15.09903 -3.099026
13.78524
4.214764
9
21.61154
-5.611544
10
19.02685 -4.026853
11 30.69747 -11.69747
12
31.4424 2.557602
13
20.71988 -3.719882
Birth Rate
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