Business Statistics - NMIMS

 

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NMIMS Global Access

School for Continuing Education (NGA-SCE)

Course:  Business Statistics

Internal Assignment Applicable for September 2020 Examination

Assignment Marks: 30

Instructions:

·       All Questions carry equal marks.

·       All Questions are compulsory

·       All answers to be explained in not more than 1000 words for question 1 and 2 and for question 3 in not more than 500 words for each subsection. Use relevant examples, illustrations as far aspossible.

·       All answers to be written individually. Discussion and group work is not advisable.

·       Students are free to refer to any books/reference material/website/internet for attempting theirassignments, but are not allowed to copy the matter as it is from the source of reference.

·       Students should write the assignment in their own words. Copying of assignments from otherstudents is not allowed.

·       Students should follow the following parameter for answering the assignment questions.

 

For Theoretical Answer

 

For Numerical Answer

Assessment Parameter

 

Weightage

 

Assessment Parameter

 

Weightage

 

Introduction

20%

Understanding and usage of the formula

20%

Concepts and Application related to the question

60%

Procedure / Steps

50%

Conclusion

20%

 

Correct Answer & Interpretation

30%

 

 

Question 1: Data Set:

Sample of 7 different species of fish has been taken and their weight in grams, lengths (vertical, diagonal, cross given as length 1, length 2 and length 3 respectively), height and width in cm is given below:

 

Species

Weight

Length1

Length2

Length3

Height

Width

Bream

725

31.8

35

40.9

16.36

6.0532

Bream

720

32

35

40.6

16.3618

6.09

Bream

714

32.7

36

41.5

16.517

5.8515

Bream

850

32.8

36

41.6

16.8896

6.1984

Bream

1000

33.5

37

42.6

18.957

6.603

Bream

920

35

38.5

44.1

18.0369

6.3063

Bream

955

35

38.5

44

18.084

6.292

Bream

925

36.2

39.5

45.3

18.7542

6.7497

Bream

975

37.4

41

45.9

18.6354

6.7473

Bream

950

38

41

46.5

17.6235

6.3705

Roach

0

19

20.5

22.8

6.4752

3.3516

Roach

110

19.1

20.8

23.1

6.1677

3.3957

Roach

120

19.4

21

23.7

6.1146

3.2943

Roach

150

20.4

22

24.7

5.8045

3.7544

Roach

145

20.5

22

24.3

6.6339

3.5478

Roach

160

20.5

22.5

25.3

7.0334

3.8203

Roach

140

21

22.5

25

6.55

3.325

Roach

160

21.1

22.5

25

6.4

3.8

Roach

169

22

24

27.2

7.5344

3.8352

Roach

161

22

23.4

26.7

6.9153

3.6312

Roach

200

22.1

23.5

26.8

7.3968

4.1272

Roach

180

23.6

25.2

27.9

7.0866

3.906

Roach

290

24

26

29.2

8.8768

4.4968

Roach

272

25

27

30.6

8.568

4.7736

Roach

390

29.5

31.7

35

9.485

5.355

Whitefish

270

23.6

26

28.7

8.3804

4.2476

Whitefish

270

24.1

26.5

29.3

8.1454

4.2485

Whitefish

306

25.6

28

30.8

8.778

4.6816

Whitefish

540

28.5

31

34

10.744

6.562

Whitefish

800

33.7

36.4

39.6

11.7612

6.5736

Whitefish

1000

37.3

40

43.5

12.354

6.525

Parkki

55

13.5

14.7

16.5

6.8475

2.3265

Parkki

60

14.3

15.5

17.4

6.5772

2.3142

Parkki

90

16.3

17.7

19.8

7.4052

2.673

Parkki

120

17.5

19

21.3

8.3922

2.9181

Parkki

150

18.4

20

22.4

8.8928

3.2928

Parkki

140

19

20.7

23.2

8.5376

3.2944

Parkki

170

19

20.7

23.2

9.396

3.4104

Parkki

145

19.8

21.5

24.1

9.7364

3.1571

Parkki

200

21.2

23

25.8

10.3458

3.6636

Parkki

273

23

25

28

11.088

4.144

Parkki

300

24

26

29

11.368

4.234

Perch

5.9

7.5

8.4

8.8

2.112

1.408

Perch

32

12.5

13.7

14.7

3.528

1.9992

Perch

40

13.8

15

16

3.824

2.432

Perch

51.5

15

16.2

17.2

4.5924

2.6316

Perch

70

15.7

17.4

18.5

4.588

2.9415

Perch

100

16.2

18

19.2

5.2224

3.3216

Perch

78

16.8

18.7

19.4

5.1992

3.1234

Perch

80

17.2

19

20.2

5.6358

3.0502

Perch

85

17.8

19.6

20.8

5.1376

3.0368

Perch

85

18.2

20

21

5.082

2.772

Perch

110

19

21

22.5

5.6925

3.555

Pike

430

35.5

38

40.5

7.29

4.5765

Pike

345

36

38.5

41

6.396

3.977

Pike

456

40

42.5

45.5

7.28

4.3225

Pike

510

40

42.5

45.5

6.825

4.459

Pike

540

40.1

43

45.8

7.786

5.1296

Pike

500

42

45

48

6.96

4.896

Pike

567

43.2

46

48.7

7.792

4.87

Pike

770

44.8

48

51.2

7.68

5.376

Pike

950

48.3

51.7

55.1

8.9262

6.1712

Pike

1250

52

56

59.7

10.6863

6.9849

Smelt

6.7

9.3

9.8

10.8

1.7388

1.0476

Smelt

7.5

10

10.5

11.6

1.972

1.16

Smelt

7

10.1

10.6

11.6

1.7284

1.1484

Smelt

9.7

10.4

11

12

2.196

1.38

Smelt

9.8

10.7

11.2

12.4

2.0832

1.2772

Smelt

8.7

10.8

11.3

12.6

1.9782

1.2852

Smelt

10

11.3

11.8

13.1

2.2139

1.2838

Smelt

9.9

11.3

11.8

13.1

2.2139

1.1659

Smelt

9.8

11.4

12

13.2

2.2044

1.1484

Smelt

12.2

11.5

12.2

13.4

2.0904

1.3936

 

Q1: Find the mean and standard deviation for each type of fish for every variable.

Answer: 1. To compute the mean and standard deviation we will use the below formulas.

The mean  \small \overline{X} is computed as follows,

\small \overline{X}=\frac{1}{n}\sum_{i=1}^{n}X_{i}

Also, the sample variance \small s^{2}is,

\small s^{2}=\frac{1}{(n-1)}\small \left ( \sum_{i=1}^{n} X_{i}^{2} -\frac{1}{n}\left ( \sum_{i=1}^{n}X_{i} \right )^{2}\right )

 

 

Question 2. If you need to choose a fish on the basis of weight, which fish you choose?

Answer   : The mean and standard deviation for Weight variable for all species is below:

 

Species

Mean

Standard Deviation

Bream

873.4

113.1471019

Roach

176.4666667

88.95574073

Whitefish

531

309.6029716

Parkki

154.8181818

78.75508642

 

 

 

Question.3. Find mean, median, quartiles for the entire data set for each variable. (10 marks)

Answer :  Mean:

 

 By using the same formula as in part (a), the mean are,

 

The sample size is n = 73. The provided sample data along with the data required to compute the sample mean \small \overline{X} for each variable of all species is shown in the table below:

Mean

 

 

Question 2 : Regress the following: (10 Marks)

  1. Taking weight as dependent variable and height as independent variable. Is variable is found to be significant?

Answer :  Below is the output:

Regression Statistics

Multiple R

0.094799718

 

 

  1. Taking weight as dependent variable and width as independent variable. Is variable is found to be significant?

Answer : 

Regression Statistics

Multiple R

0.913804714

R Square

0.835039055

 

  1. Taking weight as dependent variable and length1, length 2 and length 3 as independent variable. Are variables is found to be significant? Which variable is not significant?

Answer : 

Regression Statistics

Multiple R

0.938718572

R Square

0.881192557

Adjusted R Square

0.876027017

 

  1. Taking weight as dependent variable and height, width, length 1, length 2 and length 3 as independent variable.

Answer : 

Regression Statistics

Multiple R

0.940567787

R Square

0.884667763

Adjusted R Square

0.876060879

Standard Error

117.7864532

Observations

73

ANOVA

 

df

SS

MS

F

Significance F

Regression

5

7130089.418

1426017.884

102.7860752

4.85005E-30

 

  1. On basis of adjusted R square compare the model of part a, b, c and d. which model is best to predict weight?

Models

Adjusted R Square

a)       Weight vs Height

-0.004970943

b)       Weight vs Width

0.832715661

 

 

 

 

Question 3.  The daily COVID 19 cases (in hundred) for Delhi for past 2 week is summarize in the following table:

Day

1

2

3

4

5

6

7

8

9

10

11

12

13

14

Cases

28

29

33

31

37

34

36

43

41

32

34

37

39

32

 

 

  1. Using exponential smoothing method forecast the cases for 15 days, taking alpha as 0.3 and Initial forecast is the average of all data. (5 Marks)

Answer : First we need to compute mean of the data.

The mean  \small \overline{X} is computed as follows,

\small \overline{X}=\frac{1}{n}\sum_{i=1}^{n}X_{i}

   Mean = (1/14)* 486 = 34.7142857.

  1. Using linear trend analysis, find the trend line for number of COVID 19 cases in Delhi and forecast for next 3 days. Also compute the Mean Square Error. (5 Marks)

Answer : The independent variable is Time, and the dependent variable is Cases. In order to compute the regression coefficients, the following table needs to be used:

 

Days (X)

Cases (Y)

Days*Cases (XY)

Days^2 (X^2)

Cases^2 (Y^2)

1

28

28

1

784

2

29

58

4

841

3

33

99

9

1089

4

31

124

16

961

5

37

185

25

1369

6

34

204

36

1156

7

36

252

49

1296

8

43

344

64

1849

9

41

369

81

1681

10

32

320

100

1024

11

34

374

121

1156

12

37

444

144

1369

13

39

507

169

1521

14

32

448

196

1024

Sum =

105

486

3756

1015

17120

 

 

Hello MBA aspirants,

Get MBA assignments of NMIMS University solved by educational professionals at a nominal charge.

Mail us at: help.mbaassignments@gmail.com

Call us at: 08263069601

 

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