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Part 1
Task 1
(a)
Expenditure (£) on Stand Mixers
Mean
224.00
Standard Error
6.58
Median
224.00
Mode
224.00
Standard Deviation
75.00
Sample Variance
5625.00
Kurtosis
-0.49
Skewness
-0.32
Range
301.00
Minimum
68.00
Maximum
369.00
Sum
29120.00
Count
130.00
Coefficient of Variation
33.5%
Table 1: Task 1 calculation
(Sources: Self-Created in MS Excel)
(b) Here the mean result has suggested that the consumer will be ready to pay 224 dollars (Yletyinen et al .2019). The calculation of standard deviation is done following the Standard deviation and SQRT of Count. In this case standard deviation of 75.00 implicate included risk.
Task 2
(a)
Expenditure (£)
Frequency
Frequency (%)
Under 100
14
10.77
100 and under 200
35
26.92
200 and under 300
65
50.00
300 and over
16
12.31
Total:
130
100
Table 2: Frequency and Frequency (%)
(Sources: Self-Created in MS Excel)
Expenditure (£)
Frequency
Cumulative Frequency
Cumulative Frequency (%)
Under 100
14
14
4.56
Under 200
35
49
15.96
Under 300
65
114
37.13
Under 400
16
130
42.35
Total:
130
307
100
Table 3: Cumulative Frequency and Cumulative Frequency (%)
(Sources: Self-Created in MS Excel)
Expenditure (£)
Frequency (f)
midpoint (x)
fx
(x-mean)
(x-mean)2
f(x-mean)2
Under 100
14
13.73
192.23
-18.77
352.28
4931.98
100 and under 200
35
34.73
1215.58
2.23
4.98
174.17
200 and under 300
65
64.73
4207.50
32.23
1038.82
67523.46
300 and over
16
15.73
251.69
-16.77
281.21
4499.31
Total:
130
128.92
5867.00
-1.08
1677.29
77128.92
Table 4: midpoint (x), (x-mean), (x-mean)2 and f(x-mean)2
(Sources: Self-Created in MS Excel)
Mean
32.5
Variance
559
Standard Deviation
23.64
Table 5: Mean, Variance and Standard Deviation
(Sources: Self-Created in MS Excel)
Figure 1: Cumulative Frequency
(Sources: Self-Created in MS Excel)
(b) If a customer belongs to the bottom 25% in respect to the expenditure amount then the total estimated minimum amount is 150. The amount is 150 because it is in the middle of 100 and 200 in respect to the given figure.
Task 3
Cross sectional data
Time service is used to provide focus for every individual different time affection. Here the data are gathered for periodical time variables. As an example Tuskys time series data profit return for every end time of 2020, 2019, 2018 financial year.
Time series data
On the other side cross sectional data is known for observation of those information which come from groups or individuals. For example Quicksmart, nail nad Tuskys 31st december 2020 profit return is good.
Difference between Cross sectional data and Time series data
Most important difference between these two is the observation part which depends on individual variables and variable range (Murphy et al .2018). Here kitchen appliances should choose cross sectional data because this business survey character will carry out consumer surveys.
Task 4
(a)
Figure 2: Network Diagram
(Sources: Self-Created in MS Excel)
This networking diagram is created with forward and backward structure also by the duration. Working duration has been divided into two parts.
(b)
Paths
Duration (weeks)
A,B,D,G,H,J,
28
A,B,D,F,I,J
24
A,C,E,I,J
23
A,C,F,I,J
22
A,B,D,G,I,J
22
Table 6: Paths and Duration (weeks)
(Sources: Self-Created in MS Excel)
(c)
Critical Activities
The activities which are restricted by the time are referred to as critical activities. It also signifies that any delay in these activities delays the whole project.
Non-Critical Activities
The activities which are independent and are not restricted which the taken time is termed as non-critical activities.
Task 5
(a)
Correlation Matrix
Gross Profit (£)
Total Costs (£)
Average Order Value (£)
Sales Revenue (£)
Gross Profit (£)
1.00
0.70
0.52
0.27
Total Costs (£)
0.70
1.00
0.17
0.54
Average Order Value (£)
0.52
0.17
1.00
0.59
Sales Revenue (£)
0.27
0.54
0.59
1.00
Table 7: Correlation Matrix
(Sources: Self-Created in MS Excel)
(b)
The selected and potential predictor of the gross profit is the total value of sales or revenue. The selection of revenue is done due to certain reasons that consist of the total values of cost, number of units sold, profit and many more. Therefore, selection of revenue is accurate for the correlation matrix.
(c)
Figure 3: Scatter Graph
(Sources: Self-Created in MS Excel)
(d)
Independent variable
Gross Profit (£)
dependent variable
Sales Revenue (£)
Intercept
898.3679926
Slope
0.442037533
Regression Equation
898+0.4420X
correlation coefficient
0.272376832
coefficient of determination
0.074189139
Table 8: Correlation Coefficient and Coefficient of Determination
(Sources: Self-Created in MS Excel)
Correlation Coefficient
The relationship between two different variables which provide a specific measurement is termed as correlation coefficient (Mandalari et al .2020). According to the assignment, the correlation coefficient is 0.273 which is the correlation between total gross profit and sales.
Coefficient of Determination
The value of coefficient of determination is nothing but the square of the value of correlation coefficient.
(e)
The significant equation of the regression equation is 898+0.4420X which is the general answer based on the formula of the regression equation. It is calculated with the help of the values of intercept and slope.
Task 6
(1)
coefficients of variation
Coefficients of variation (%)
Venture A
0.042971
4.30
Venture B
0.0333
3.33
Table 9: Coefficient of Variation and Coefficient of Determination of Variation (%)
(Sources: Self-Created in MS Excel)
(2) The project B should be chosen because it has lower price segmentation and the standard deviation is sufficient to work with.
Task 7
This reflection is given as per the personal knowledge gaining reflection information. This information is about which things create problems to fulfill the requirement or project potential. In the following step the discussion is provided as per the little bit of feedback form.
Before concluding in the future path first things need to be learned about controlling stress. In the present more techniques have been learnt.
There should be a long term horizon decision making life goals which will be used like some objectives. Therefore, if I get another assignment like this, I will complete the assignment with less amount of time because my efficiency increased after completing the assignment. That will be helped to consume time section properly.
To build good and long term relationships with surrounding people which will transfer more effective and genuine dealing factors.
For this project through crystallization has been procure all the requer potential. also the challenges created on the aspect of course work and the most brutal honest path. This way helps to move everything in the correct direction. In future more natural and environmental creative aspects will be found to develop the next assignment.
Part 2
(a)
Month
Sales (units)
Total Cost (£)
July
14502
195000
August
15000
200400
September
14000
200000
October
19100
241000
November
24806
308060
December
34000
400000
Variable cost
10.25
per unit
Fixed cost
51500
Table 10: Fixed and Variables cost
(Sources: Self-Created in MS Excel)
High and low methods have defined the variable cost as well as fixed cost; this detail provides more periodical information. This particular method is most suitable at the segregate FC and VC data variables.
(b)
Particulars
Sales (units)
Total Cost (£)
High
34000
400000
Low
14502
195000
Variable cost per unit
10.51
Fixed cost per unit
42527.44
Breakeven point
4044.88
Table 11: Fixed and Variables cost
(Sources: Self-Created in MS Excel)
(c)
If the profit target hits
profit target
60000
Total cost for profit target
150000
Total sell for profit target
210000
Total numbers of unit to sell (units) for target profit
10500
Table 12: Profit Target
(Sources: Self-Created in MS Excel)
In order to achieve the targeted profit value which is 60000, Enka limited have to sell 10500 units of t-shirt to achieve the targeted profit. Therefore, the total cost will be 150000 and the total revenue will be 210000 for achieving the target profit.
(d)
The total margin of safety for the year of 2022 January will be there compared to the other months of the year because in the past months the company has earned a large number of profit compared to the current target profit.
(e)
There are several advantages and disadvantages of the process of breakeven analysis which are projected below.
Advantage of Break Even Analysis
The most significant and practical purpose of the breakeven analysis is to evaluate the total profit and the total amount of loss in the different stages of the production of the product and the sales of the product (Acharya et al .2018). It helps the companies to understand the all over activity of the product from production to sales.
This one is considered as the changing and circulating help point which makes ensurity in business decisions for business.
This is the most simple and easiest factor for decision making.
At any variable output result point this system is usable.
Disadvantages of Break Even Analysis
The concept of breakeven analysis has certain limitations and disadvantages at the same time that it is to calculate levels of output by assuming the total sales price in constant form.
It also calculates on the assumptions that the levels of production and sales are going to be the same.
The process of breakeven analysis is restricted towards a single product of the company or a blend of products but it is considered as a single product of a company.
This one only provides information of efficient case long term planning that is not applicable for it.
At the break even time it creates complexity for multiple product mixes.
If the estimated business is full with both type costs then the complex level is included in the calculation part.
Reference list
Journals
Acharya, V.V., 2018. Understanding and managing interest rate risk at banks. Macroeconomics and Finance in Emerging Market Economies, 11(2), pp.218-231.
Arora, L., Singh, P., Bhatt, V. and Sharma, B., 2021. Understanding and managing customer engagement through social customer relationship management. Journal of Decision Systems, pp.1-21.
Mallinson, A., Maire, R., Beyaert, C., Vibert, D., Coffinet, L., Longridge, N., Vanspauwen, R., Dumas, G., Petersen, H. and Perrin, P., 2021. Understanding and Managing Trauma-Induced Vestibular Deficits. The Journal of International Advanced Otology, 17(6), pp.559-565.
Mandalari, G., 2020. Symposium ‘understanding and managing satiety: processes and opportunities’. Journal of Nutritional Science, 9.
Murphy, S.A., Paltridge, R., Silcock, J., Murphy, R., Kutt, A.S. and Read, J., 2018. Understanding and managing the threats to Night Parrots in south-western Queensland. Emu-Austral Ornithology, 118(1), pp.135-145.
Yletyinen, J., Brown, P., Pech, R., Hodges, D., Hulme, P.E., Malcolm, T.F., Maseyk, F.J., Peltzer, D.A., Perry, G.L., Richardson, S.J. and Smaill, S.J., 2019. Understanding and managing social–ecological tipping points in primary industries. BioScience, 69(5), pp.335-347.
