NMIMS March/April/May 2023 MBA assignments – Calculate the Correlations for the following pairs of variables and write your Conclusion. • In Migration of Persons from other states (Census of India) & Total MSMEs • In Migration of Persons from other states (Census of India) & Active Companies • In Migration of Persons from other states (Census of India) & 2017-18 GSDP – CURRENT PRICES (` in Crore) • Total MSMEs & Active Companies
Calculate the Correlations for the following pairs of variables and write your Conclusion. • In Migration of Persons from other states (Census of India) & Total MSMEs • In Migration of Persons from other states (Census of India) & Active Companies • In Migration of Persons from other states (Census of India) & 2017-18 GSDP – CURRENT PRICES (` in Crore) • Total MSMEs & Active Companies
Calculate the Correlations for the following pairs of variables and write your Conclusion. • In Migration of Persons from other states (Census of India) & Total MSMEs • In Migration of Persons from other states (Census of India) & Active Companies • In Migration of Persons from other states (Census of India) & 2017-18 GSDP – CURRENT PRICES (` in Crore) • Total MSMEs & Active Companies
Decision Science
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Based on the following data develop the forecasting model (adopt Exponential Smoothing Technique) by considering the following alpha levels. α = 0.2, 0.4, 0.6, 0.8.
Write your conclusion after calculations of Errors (MAD and MSE only).
Forecast FTAs (foreign tourist arrival) for the year 2018.
Data: The following data shows the Foreign Tourist Arrival in the India from 1991 to 2017 Year FTAs in India (in Million)
Year |
FTAs in India (in Million) |
1991 |
1.68 |
2001 |
2.54 |
2002 |
2.38 |
2003 |
2.73 |
2004 |
3.46 |
2005 |
3.92 |
2006 |
4.45 |
2007 |
5.08 |
2008 |
5.28 |
2009 |
5.17 |
2010 |
5.78 |
2011 |
6.31 |
2012 |
6.58 |
2013 |
6.97 |
2014 |
7.68 |
2015 |
8.03 |
2016 |
8.8 |
2017 |
10.04 |
Data Source: Data.gov.in
Note: You are advised to calculate manually, do not use any software. (10 Marks)
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Calculate the Correlations for the following pairs of variables and write your Conclusion.
In Migration of Persons from other states (Census of India) & Total MSMEs
In Migration of Persons from other states (Census of India) & Active Companies
In Migration of Persons from other states (Census of India) & 2017-18 GSDP –
CURRENT PRICES (` in Crore)
Total MSMEs & Active Companies
Note: Use MS EXCEL, SPSS, SAS etc. for the calculations.
State |
Total MSMEs |
Active Companies |
In Migration of Persons from other states (Census of India) |
2017-18 GSDP – CURRENT PRICES (` in Crore) |
ANDAMAN &NICOBAR ISLANDS |
6,061 |
319 |
81,267 |
7,871 |
ANDHRA PRADESH |
6,41,929 |
1,16,210 |
15,91,890 |
15,46,313 |
ARUNACHALPRADESH |
60,932 |
237 |
1,36,010 |
22,432 |
ASSAM |
20,189 |
6,346 |
4,95,699 |
2,88,691 |
BIHAR |
9,02,520 |
20,867 |
11,11,954 |
4,84,740 |
CHANDIGARH |
11,209 |
7,956 |
6,33,966 |
38,760 |
CHHATTISGARH |
69,758 |
7,109 |
12,67,668 |
4,84,740 |
DELHI |
1,63,821 |
2,16,531 |
63,30,065 |
6,86,824 |
GOA |
8,620 |
4,125 |
2,69,689 |
70,494 |
GUJARAT |
8,07,378 |
62,619 |
39,16,075 |
13,28,068 |
HARYANA |
1,85,486 |
30,868 |
36,26,318 |
6,49,592 |
HIMACHALPRADESH |
14,674 |
3,344 |
3,95,504 |
1,38,351 |
JAMMU & KASHMIR |
9,399 |
2,745 |
1,55,187 |
1,37,427 |
JHARKHAND |
1,57,813 |
9,554 |
21,95,521 |
2,76,243 |
KARNATAKA |
3,32,872 |
68,333 |
32,47,660 |
13,57,579 |
KERALA |
1,25,934 |
31,244 |
6,54,423 |
7,01,577 |
MADHYA PRADESH |
9,34,293 |
22,315 |
27,44,332 |
7,24,729 |
MAHARASHTRA |
16,92,859 |
2,31,912 |
90,87,380 |
24,11,600 |
MANIPUR |
34,423 |
434 |
20,100 |
23,835 |
MEGHALAYA |
2,208 |
560 |
1,07,915 |
30,790 |
MIZORAM |
3,238 |
66 |
41,380 |
18,737 |
NAGALAND |
1,543 |
235 |
1,08,020 |
24,492 |
ODISHA |
1,19,291 |
15,204 |
8,55,096 |
4,34,769 |
PUDUCHERRY |
10,539 |
1,282 |
3,39,967 |
32,962 |
PUNJAB |
2,03,394 |
16,909 |
24,88,299 |
4,78,636 |
RAJASTHAN |
5,72,546 |
37,022 |
26,04,298 |
8,35,170 |
SIKKIM |
875 |
2 |
61,163 |
23,495 |
TAMIL NADU |
10,32,490 |
76,675 |
16,50,771 |
14,61,841 |
TRIPURA |
5,936 |
317 |
87,378 |
44,219 |
UTTAR PRADESH |
8,87,413 |
70,863 |
40,61,933 |
14,60,443 |
UTTARAKHAND |
40,443 |
4,792 |
12,50,575 |
2,22,836 |
WEST BENGAL |
2,31,190 |
1,35,844 |
23,81,045 |
9,99,585 |
Data Source |
https://data.gov.in/ |
https://data.gov.in/ |
https://censusindia.gov.in/ |
https://data.gov.in/ |
(10 Marks)
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a. Summarized the following data by calculating the mean and standard deviation. (5 Marks)
Note: You are advisable to use EXCEL. You are supposed to Copy the numbers (final calculations) from EXCEL and paste them into your word document.
State |
District |
Number Of Indigenous (Desi) Total Cattle |
TotalBuffalo |
UTTARAKHAND |
Uttarkashi |
82991 |
25945 |
UTTARAKHAND |
Chamoli |
132165 |
37922 |
UTTARAKHAND |
Rudraprayag |
71277 |
31115 |
UTTARAKHAND |
Tehri Garhwal |
80833 |
79394 |
UTTARAKHAND |
Dehradun |
87753 |
52185 |
UTTARAKHAND |
Garhwal |
235412 |
30076 |
UTTARAKHAND |
Pithoragarh |
108417 |
37056 |
UTTARAKHAND |
Bageshwar |
70863 |
31432 |
UTTARAKHAND |
Almora |
132038 |
77444 |
UTTARAKHAND |
Champawat |
45506 |
18599 |
UTTARAKHAND |
Nainital |
101009 |
77759 |
UTTARAKHAND |
Udham Singh Nagar |
63311 |
152911 |
UTTARAKHAND |
Hardwar |
63728 |
214480 |
Data Source: Ministry of agriculture and farmers’ welfare.
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b. Write about the general pattern (here, time series component) across the given years using an appropriate graph. (5 Marks)
Note: You may use EXCEL, Tableau, and Power BI Etc. for creating Graph
PLEASE CHECK THE TABLE BELOW
Year |
ProductivityGroundnut(Kg./hectare) |
ProductivityRapeseed&Mustard(Kg./hectare) |
Year |
ProductivityGroundnt(Kg./hectare) |
ProductivityRapeseed&Mustard(Kg./hectare) |
Year |
ProductivityGroundnut(Kg./hectare) |
ProductivityRapeseed&Mustard(Kg./hectare) |
Year |
ProductivityGroundnut(Kg./hectare) |
ProductivityRapeseed & Mustard(Kg./hectare) |
1950-51 |
775 |
368 |
1968-69 |
653 |
469 |
1986-87 |
841 |
700 |
2003-04 |
1357 |
1159 |
1951-52 |
649 |
393 |
1969-70 |
720 |
493 |
1987-88 |
855 |
748 |
2004-05 |
1020 |
1038 |
1952-53 |
611 |
408 |
1970-71 |
834 |
594 |
1988-89 |
1132 |
906 |
2005-06 |
1187 |
1117 |
1953-54 |
811 |
389 |
1971-72 |
823 |
396 |
1989-90 |
930 |
831 |
2006-07 |
866 |
1095 |
1954-55 |
766 |
425 |
1972-73 |
585 |
545 |
1990-91 |
904 |
904 |
2007-08 |
1459 |
1001 |
1955-56 |
752 |
336 |
1973-74 |
845 |
493 |
1991-92 |
818 |
895 |
2008-09 |
1163 |
1143 |
1956-57 |
783 |
411 |
1974-75 |
724 |
612 |
1992-93 |
1049 |
776 |
2009-10 |
991 |
1183 |
1957-58 |
734 |
387 |
1975-76 |
935 |
580 |
1993-94 |
941 |
847 |
2010-11 |
1411 |
1185 |
1958-59 |
828 |
426 |
1976-77 |
747 |
496 |
1994-95 |
1027 |
958 |
2011-12 |
1323 |
1121 |
1959-60 |
708 |
365 |
1977-78 |
866 |
460 |
1995-96 |
1007 |
916 |
2012-13 |
996 |
1262 |
1960-61 |
745 |
467 |
1978-79 |
835 |
525 |
1996-97 |
1138 |
1017 |
2013-14 |
1750 |
1188 |
1961-62 |
725 |
425 |
1979-80 |
805 |
411 |
1997-98 |
1040 |
668 |
2014-15 |
1400 |
1089 |
1962-63 |
695 |
417 |
1980-81 |
736 |
560 |
1998-99 |
1214 |
869 |
2015-16 |
1465 |
1183 |
1963-64 |
769 |
300 |
1981-82 |
972 |
541 |
1999-00 |
766 |
960 |
2016-17 |
1398 |
1304 |
1964-65 |
814 |
507 |
1982-83 |
732 |
577 |
2000-01 |
977 |
935 |
2017-18 |
1893 |
1410 |
1965-66 |
554 |
446 |
1983-84 |
940 |
673 |
2001-02 |
1127 |
1002 |
2018-19 |
1422 |
1511 |
1966-67 |
604 |
408 |
1984-85 |
898 |
771 |
2002-03 |
694 |
854 |
2019-20 |
2063 |
1331 |
1967-68 |
759 |
483 |
1985-86 |
719 |
674 |
2020-21 |
1676 |
1511 |
Calculate the Correlations for the following pairs of variables and write your Conclusion. • In Migration of Persons from other states (Census of India) & Total MSMEs • In Migration of Persons from other states (Census of India) & Active Companies • In Migration of Persons from other states (Census of India) & 2017-18 GSDP – CURRENT PRICES (` in Crore) • Total MSMEs & Active Companies
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