TABLE OF CONTENTS

...............................................................................................................................................................................................................

Introduction.................................................................................................................................................................................. 2

Part A................................................................................................................................................................................................ 3

1.1 Plan for collection of Primary and Secondary Data.........................................................................................3

1.2 Survey Methodology and Survey Technique......................................................................................................4

1.3 The Questionnaire..........................................................................................................................................................5

Part B................................................................................................................................................................................................ 7

2.1 Information of Decision Making..............................................................................................................................7

2.2 Analyzing the results....................................................................................................................................................8

2.3. Measures of Dispersion............................................................................................................................................10

2.4 Quartiles, Percentiles, Correlation Coefficient................................................................................................12

Part C............................................................................................................................................................................................. 14

3.1 Graphs Using Spreadsheet.......................................................................................................................................14

3.2 Trend Lines Using Spreadsheet.............................................................................................................................16

Part D............................................................................................................................................................................................. 17

4.1 Information Processing Tools................................................................................................................................17

4.2 Preparing a Project plan and Determining a Critical path.........................................................................19

4.3 Using Financial Tools to Make a Decision.........................................................................................................21

Conclusion................................................................................................................................................................................... 22

References................................................................................................................................................................................... 23

INTRODUCTION

Business Decision Making is one of the most useful courses for a manager-to-be, considering the fact that decision making is the most critical aspect of managing a firm. In this assignment, the most important tools for analyzing a business and making decisions regarding it, have been used in various circumstances and in various ways, giving it a complete picture of business decision making.

This assignment has been designed in such a way that a comprehensive knowledge of the course will prove to be necessary while doing it. And thus, this assignment has been done with all necessary calculations, providing a detailed view of the solutions given for every problem.

PART A

1.1 PLAN FOR COLLECTION OF PRIMARY AND SECONDARY DATA

In order to complete any research, data has to be collected, and it can be done in several ways. The collected data can be classified into mainly two types:

a. Primary data

b. Secondary Data

a. Primary Data:

The data that is collected by the researcher him/herself or by anybody paid by the researcher, right from the subject of research, is called primary Data.

Example: Survey results.

b. Secondary Data:

The data that is already present, i.e. collected by somebody else for some other purpose, is called secondary data. Secondary data maybe present in various forms.

Example: Newspaper articles, government reports, etc.

So, basically, the data obtained by the own effort of the researcher is termed as primary data, whereas, relevant data which have already been obtained by someone else is classified as secondary data. (Dawson, 2009)

In order to collect primary data, we suggest the management of Travel For London (TFL) to arrange for surveys to be conducted on the passengers of Route 23. This has to be done by using printed questionnaires to be handed out to every passenger who gets on board at every stop. This should be conducted for about 2-3 weeks so as to cover most of the passengers. The survey questionnaire has to be easy, short and precise, with close-ended answers so that the passengers are not reluctant towards the surveys, thus reducing the percentage of no-response.

The questionnaire should have the easier questions first, and then the ones which would require comparative thinking. This should also be done at various times of the day so that all sorts of passengers get to respond. The notice of the survey should also be posted beforehand, so that the passengers know about it.

In case of secondary data, the researchers will have to go through any legitimate information available over the internet, government reports, surveys carried out by other transportation companies, newspapers, etc.

1.2 SURVEY METHODOLOGY AND SURVEY TECHNIQUE

Survey Methodology:

Survey is a very effective means of collecting information. As Robson says it, Survey is suitable technique for collecting enormous amount of information in significantly short time and assets. (Robson, 2002)

Some workers need to be hired for this work, and they will be paid. They will take the printed questionnaires and distribute among the passengers. When they have done taking the survey, they printed papers will be taken back by the workers from the passengers. This will be returned to our agent, who will be present at a specified time at a specified stop of Route 23.

Some extra survey can be done by sending some workers over to the residents of Route 23, where they can be requested to fill up the form.

Sampling Frame:

The sample frame would be the passengers of Route 23 who travel mostly by bus. Since around 1500 families are present around Route 23, around 300 families should be surveyed.

Sampling Techniques:

All the information collected will be compiled. A thorough study of the information will be done. For a systematic conduction, every 5th house of the area will be questioned by our representative. (Saunders, Thornhill, & Lewis, 2009) (Kish, 1995)

1.3 THE QUESTIONNAIRE

A sample of the questionnaire is provided below:

Please help us out by answering a few questions!

Date:Time:

1. Age:

a. 15-22 b. 23-30 c. 30-40 d. above 60

2. Occupation:

3. Gender:

a. male b. female c. others

4. Annual Income:

a. 5k – 10k b. 10k- 20k c. 20k-35k d. 35k-50k e. more than 50k

5. residence:

6. members in the family:

a. 1-2 b. 3-5 c. more than 5

7. marital Status:

a. married b. unmarried c. Others

8. how do you mostly travel?

a. Bus b. Train c. Car d. Foot e. Others

9. On an average, how often do you use the bus of route 23?

a. almost never b. 2-3 times a week c. once a week d. once a month e. 4-5 times a year f. never

10. please mention the time(s) that you usually travel.

11. Do any of your family members/friends use the bus of Route 23?

a. yes b. No

12. (If answer to No. 11 is yes, then) How many?

13. How frequently do they use it?

a. almost never b. 2-3 times a week c. once a week d. twice a week e. once a month f. 4-5 times a year e. almost everyday

14. Do you have car?

a. yes b. no

15. (If answer to no. 14 is yes, then) How many?

16. What do you think about the bus service of route no. 23?

PART B

2.1 INFORMATION OF DECISION MAKING

The following table shows the number of passengers boarding the bus service on Route 23:

Time Mon Tue Wed Thurs Fri Sat Sun Total700-800 8 10 9 8 10 6 0 51800-900 11 10 8 8 7 8 1 53900-1000 12 12 7 9 8 5 2 551000-1100 7 8 8 9 1 2 8 431100-1200 6 5 4 7 1 4 8 351200-1300 6 3 2 4 3 4 10 321300-1400 5 2 2 2 3 5 8 271400-1500 2 6 4 3 3 4 10 321500-1600 6 2 6 3 4 5 8 341600-1700 8 3 7 4 4 4 5 351700-1800 6 4 8 7 8 5 4 421800-1900 6 5 8 6 6 9 4 441900-2000 2 2 6 6 7 8 1 322000-2100 2 2 2 1 10 10 0 272100-2200 1 2 0 0 10 9 0 22Total 88 76 81 77 85 88 69 564

The above table indicates the number of passengers boarding the bus weekly which is 564. During the office hour which is 900-1000, it has a total of 55 passengers boarding the bus throughout the week. This is so far the highest number of boarding.

2.2 ANALYZING THE RESULTS

The table presented in 2.1 hardly gives us a lot of information on what to do in the current situation. For this reasons, some calculations need to be done, which is being presented in the following table:

For calculation, the total number of passengers has been divided by 7, thus presenting the mean.

Time Mon Tue Wed Thurs Fri Sat Sun Total Mean700-800

8 10 9 8 10 6 0 51 7.285714

800-900

11 10 8 8 7 8 1 53 7.571429

900-1000

12 12 7 9 8 5 2 55 7.857143

1000-1100

7 8 8 9 1 2 8 43 6.142857

1100-1200

6 5 4 7 1 4 8 35 5

1200-1300

6 3 2 4 3 4 10 32 4.571429

1300-1400

5 2 2 2 3 5 8 27 3.857143

1400-1500

2 6 4 3 3 4 10 32 4.571429

1500-1600

6 2 6 3 4 5 8 34 4.857143

1600-1700

8 3 7 4 4 4 5 35 5

1700-1800

6 4 8 7 8 5 4 42 6

1800-1900

6 5 8 6 6 9 4 44 6.285714

1900-2000

2 2 6 6 7 8 1 32 4.571429

2000-2100

2 2 2 1 10 10 0 27 3.857143

2100-2200

1 2 0 0 10 9 0 22 3.142857

Total 88 76 81 77 85 88 69 564Mean 5.86666

75.066667

5.4 5.133333

5.666667

5.866667

4.6

The graph below can show the allotment of passengers all round the day. The chart shows a slight rise during 900-1000, which clearly shows that since working hour starts from 1000, most of the passengers take the bus to get to work. During 700-800 and also during 800-900 people travel as well. Understandably, the curve decreases at midday and ascends from the evening.

This curve clearly shows that people board the bus during the whole day, keeping none of the time slots vacant. This is a clear indication that the bus service of route 23 should not be stopped.

700-800

800-900

900-1000

1000-1100

1100-1200

1200-1300

1300-1400

1400-1500

1500-1600

1600-1700

1700-1800

1800-1900

1900-2000

2000-2100

2100-22000

10

20

30

40

50

60

51 53 55

4335 32

2732 34 35

42 44

3227

22

Passengers Every Hour

Passengers Every Hour

2.3. MEASURES OF DISPERSION

Variance and standard deviation are frequently used actions of dispersion.

The formula for variance is:

∑ (X−μ )2

n

And standard deviation is the square root of variance.

These values can be simply measured by putting the values into MS Excel using the functions,

STDEV.P( ) and VAR.P( ). But here, it has been done by steps-

Here is the average sum of passengers per week’s time slot = 564/15 = 37.6.

X Μ X−μ (X−μ )2

43 37.6 13.4 179.56

53 37.6 15.4 237.16

55 37.6 17.4 302.76

43 37.6 5.4 29.16

35 37.6 -2.6 6.76

32 37.6 -5.6 31.36

27 37.6 -10.6 112.36

32 37.6 -5.6 31.36

34 37.6 -3.6 12.96

35 37.6 -2.6 6.76

42 37.6 4.4 19.36

44 37.6 6.4 40.96

32 37.6 -5.6 31.36

27 37.6 -10.6 112.36

22 37.6 -15.6 243.36

∑ (X−μ )2 1397.6

No of observations 15

Varianc

e93.2

Standard Deviation 9.65

So, here the average value of per time slot is 37.6. Variance is 93.2 and the standard deviation is 9.65.

The mean of the passengers of each day = 556/7 = 79.4

X Μ X−μ (X−μ )2

88.0 80.6 7.43 55.18

76.0 80.6 -4.57 20.90

81.0 80.6 0.43 0.18

77.0 80.6 -3.57 12.76

85.0 80.6 4.43 19.61

88.0 80.6 7.43 55.18

69.0 80.6 -11.57 133.90

∑ (X−μ )2 297.71

No of observations 7.0

Variance 42.5

Standard Deviation 6.52

Here, the average is 80.6. The variance is 42.5 and the standard deviation is 6.52.

2.4 QUARTILES, PERCENTILES, CORRELATION COEFFICIENT

Quartiles:

Quartiles are of three types. It some random numbers are selected, arranged in increasing order, then the number exactly in the middle is called the median. So, the median represents 50% or half of the arranged numbers, or corresponds to 50% percentile. (Median Value, 2003)

The median is also called the 2nd quartile, which represents 50% percentile. Accordingly, the 1st

percentile will correspond to 25% of the percentile and the 3rd percentile will correspond to 75% percentile. (Mean, Variance and Standard Deviation, 2012)

Mathematically, the quarantines can be determined using the following formula:

Q = L + [ {(K.N/4)-F} ÷ f ] a

Here,

Q= Required quartile

L= lower limit of the quartile class

N= sum total of frequencies/responses

F= cumulative frequency/responses of just below the selected quartile class

A= width of the quartile class

F= frequency or responses of the quartile class

Percentiles:

As concepts, quartiles and percentiles are extremely related. As an example, we can say that, in a group of 10 members, Johan earns the second highest. So, Johan earns more than 80% of the entire group. So, we say that mathematically Johan is in the 80 th percentile. So, percentiles basically act as representative values, just like the quartiles.

Co-efficient of Co-relation:

Karl Pearson’s co-efficient of co-relation is something that’s used to determine what nature or characteristics are the relations between two variables of. If, during the increase of one variable, the other variable increases, the variables have a positive co-relation. If, during the decrease of one variable, the other variable decreases, they still have a positive co-relation.

But, if with the increase/decrease of one variable, the other variable takes the opposite direction, then the variables are said to have a negative co-relation.

This relation can also be understood from their values. The value of the co-efficient can range from +1 to -1. Usually, the value lies somewhere in the middle. But if the value exceeds 0.8, the variables are supposed to have a very strong positive relation. If the value becomes lower than -0.8 then they have a very strong negative relation.

If the absolute value is somewhere between 0.5 to 0.8, it is considered to have a moderate value.

Mathematically, considering the variables as x and y, their coefficient correlation can be determined by the formula:

r = (n ∑xy- ∑x∑y) ÷√[{n∑x^2-(∑x)^2}{n∑y^2-(∑y)^2}]

(Analysis of Karl Pearson's Co-efficient of Co-relation, 2012)

Using the Microsoft Excel, the values can be easily calculated. This concept can readily help in case of business purposes, like relation between people’s income and the demand for a commodity, people’s income and their preference for discount shops, etc.

PART C

3.1 GRAPHS USING SPREADSHEET

A bar chart is drawn below showing the number of passengers availing each day by the bus service of route no.23

Mon

Tues

Wed

Thurs

Fri

Sat

Sun

0 10 20 30 40 50 60 70 80 90 100

88

76

81

77

85

88

69

Total Passengers Per Day

Total Passengers Per Day

On the above bar chart, the number of passenger is on X axis and the days are on Y axis. The chart above indicates that the highest number of passengers travels both on Monday and Saturday equally and the number is 88. On Sunday people tend to travel less and thus it has the lowest number of passengers which is 69. Rest of the days has passengers that are very close in number.

And now another graph has been drawn showing the relation of the number of passengers and the

time slot per hour.

People mostly travel at 900-1000 which is quite obvious as it is the office time. People go to their workplace at this time so there is a slight rush at this time. Actually the rush starts from the early morning and continuous till 1000. Again we can see that at the afternoon more people tend to travel by bus as it is the time of returning home. But the mid day seems to be off peak hour for the bus service.

700-800

800-900

900-1000

1000-1100

1100-1200

1200-1300

1300-1400

1400-1500

1500-1600

1600-1700

1700-1800

1800-1900

1900-2000

2000-2100

2100-22000

10

20

30

40

50

60

51 53 5543

35 32 27 32 34 3542 44

32 27 22

Passengers Every Hour

Passengers Every Hour

3.2 TREND LINES USING SPREADSHEET

A scatter chart showing the number of passengers on each day is given below-

0 1 2 3 4 5 6 7 80

10

20

30

40

50

60

70

80

90

100

88

7681

7785 88

69

Daily Journeys

Daily JourneysLinear (Daily Journeys)Moving average (Daily Journeys)Moving average (Daily Journeys)

From the chart it is clear that the bus service has fewer passengers on Sunday which is a holiday. It has higher passengers on Monday and Saturday. Also it can be seen that Linear line through the number of journeys is an up and down curve where the average of daily journey is almost straight.

PART D

4.1 INFORMATION PROCESSING TOOLS

Pearson’s correlation coefficient is an accepted instrument for decisive the character of relation

amid two independent variables. The number of cars that each household has is one variable. The

number of bus journey of the members is the other variable. It is obvious that the families having

more cars will have less bus journeys. The correlation coefficient has been calculated with the

help of MS Excel. In X axis, there is the number of cars each family has and in y axis , the

number of bus journeys has been put. There are 15 pairs of variables. The formula is as follows if

X & Y are the two variables:

R = (n ∑xy- ∑x∑y) ÷√[{n∑x^2-(∑x)^2}{n∑y^2-(∑y)^2}]

Here, R is the value of the coefficient & n is the total number of entries.

Cars Journeys

2 5

4 1

4 2

5 0

1 7

3 5

3 4

2 5

3 4

2 6

5 1

3 1

6 0

2 6

0 10

Co efficient -0.93434

Here the coefficient is -0.93434. It means the two variables have strongly negative correlation.

4.2 PREPARING A PROJECT PLAN AND DETERMINING A CRITICAL PATH

A PERT chart is a tool that is used to schedule, organize, and coordinate tasks within a project. The

Critical Path Method (CPM) is another tool for determining the minimum time required to finish a

task.

Activity Time Predecesso

r

Time/Days

A Select office site _ 2

B Create organizational and financial plan _ 3

C Determine personnel requirements B 1

D Design facility A,C 3

E Construct interior D 8

F Select personnel to move C 1

G Hire new employees F 6

H Move records, key personnel etc F 3

I Make financial arrangement with a bank B 7

J Train new personnel. H,E,G 2

Mr. Anderson should complete task A and task B without any delay. When he has done these tasks

he may move to task C. And once C is done he can start with his work D and then he can move

towards with the other works. We have to determine 4 things for this-

Earliest Start Time

Earliest Finish Time

Latest Start Time

Latest Finish Time

We can calculate and say that the latest finish time for task J is 17 days. We can calculate the latest

start time now by using the following formula- LS = LF – t

And now the slack time of the project has to be calculated. Slack time means how much time we can

delay without delaying the whole project. It can be measured by the formula- Slack = LS – ES = LF –

EF

The tasks with a slack time which is zero shape the critical path.

Therefore the Critical Path is: B C D E J

4.3 USING FINANCIAL TOOLS TO MAKE A DECISION

NPV or Net Profit Value is an essential tool to determine whether it should be wise to invest in a project or not. It also helps to identify the sustainability of a business.

Here, Mr. Anderson wants to shift his business from East London to Central London due to some problems. A table showing the NPV for both the East London clinic and the Central London clinic is shown below-

Year East London Clinic Cost of Capital

20%

Central London Clinic0 -255000 -5300001 90000 400002 85000 800003 90000 1400004 91000 2500005 110000 320000

NPV 19202.67 -110928

From the above calculation we can see that Central London clinic has a negative NPV. It means that shifting the clinic may incur a huge loss of Mr. Anderson. On the other hand, in spite of the increased rent, Mr. Anderson will somehow manage to generate some profit in East London.

Payback Period

Payback period is another tool to identify which project will be more viable to accept. By calculating in MS excel, we have found that the payback period of East London clinic is 2.89 and the payback period of Central London is 4.06. It is known that the project having a lower payback period should be accepted because it tends to be more feasible. So, here East London clinic is more profitable than the Central London Clinic. So Mr. Anderson should not shift his office to Central London if he wants to jeep his business profitable.

CONCLUSION

The assignment has been extremely realistic and stimulating, thus urging us to think and use the skills acquired to utilize in this piece. The practice of everything that has been covered in this course is simply outstanding, and effective.

A lot more calculations could be placed in this assignment, but due to limitations, I have kept the assignment short and simple. I look forward to more knowledge and skills on Business Decision making and hope that this assignment meets the necessary requirements.

REFERENCES

Analysis of Karl Pearson's Co-efficient of Co-relation. (2012).

Dawson. (2009).

Kish. (1995).

Mean, Variance and Standard Deviation. (2012).

Median Value. (2003).

Robson. (2002).

Saunders, Thornhill, & Lewis. (2009).