Descriptive Statistics, Data Types, Networking, Expected Values, and Breakeven Analysis

This coursework covers topics such as ungrouped descriptive statistics, grouped descriptive statistics, data types, networking, expected values, and breakeven analysis. It includes a discussion on personalized learning and the high-low strategy for cost estimation.

Coursework

Contents
Contents...........................................................................................................................................2
PART 1............................................................................................................................................1
TASK 1: Ungrouped Descriptive Statistics.................................................................................1
TASK 2: Grouped Descriptive Statistics.....................................................................................1
TASK 3: Data Types...................................................................................................................3
TASK 4: Networking...................................................................................................................3
TASK 6: Expected values............................................................................................................6
TASK 7:.......................................................................................................................................7
PART 2............................................................................................................................................7

PART 1
TASK 1: Ungrouped Descriptive Statistics
(a) The aggregate mean and standard deviation from the activities table are displayed on
existing processing units.
Expenditure (£) on Stand
Mixers
Mean 224.00
Standard Error 6.58
Median 224.00
Mode 224.00
Standard Deviation 75.00
Sample Variance 5625.09
Kurtosis -0.49
Skewness -0.32
Range 301.00
Minimum 68.00
Maximum 369.00
Sum
29120.0
0
Count 130.00
Coefficient of
Variation 33.5%
(b) Standing processors expenses have an undetermined mean and standard deviation of
£224 and £75, respectively. We can infer that perhaps the statistics are grouped towards
the standard since the average is greater as compared to that of usual variability. Because
the mean, median, and mode values are all the same, the expenses are evenly distributed.
TASK 2: Grouped Descriptive Statistics
(a) Table 1 , 2 and 3 are as follows:
Expenditure (£) Frequency
Frequency
(%)
Under 100 15 11.54
100 and under 200 34 37.69
200 and under 300 64 86.92
300 and over 17 100
Total: 130 236.1538462

Expendit
u re (£)(x)
Frequency
(f)
Cumulat
ve
Frequen
c
y
Cumulatv
e
Frequenc
y
(%) fx (x-mean) (x-mean)2
f(x-
mean) 2
Under 100 15 15 11.54 1500 -163.85 26845.56
402683.
43
Under 200 34 49 37.69 6800 -63.85 4076.33
138595.
27
Under 300 64 113 86.92 19200 36.15 1307.10
83654.4
4
Under 400 17 130 100 6800 136.15 18537.87
315143.
79
Total: 130 307
236.15384
62 34300
-
55.384615
38 50766.863
91
940076.
92
Expenditure (£)
Frequency
(f)
midpoint
(x) fx (x-mean) (x-mean)2 f(x-mean)2
Under 100 15 50 750 -163.85 26846.82 402702.34
100 and under
200 34 150 5100 -63.85 4076.82 138611.97
200 and under
300 64 250 16000 36.15 1306.82 83636.64
300 and over 17 350 5950 136.15 18536.82 315125.98
Total: 130 27800 -55.4 50767.29 940076.93
(b) From the collected activities information, the calculated mean, standard deviation, and
variance are 213.85, 7231.36, and 85.04, respectively. Basic qualitative transactional
indicators have mean, standard deviation, and variance values of 263.85, 7231.36, and
85.04, correspondingly. To compute the mean and standard deviation from continuous
factors, we utilized all input readings from the same time according to the mid-point of
the chosen span. As a consequence, computing the mean and standard deviation with
sampling variability statistics on spending is more accurate.
(c) We can extrapolate from the statistic that now in addition to be in the top 25% of buyers,
(100-85) 15 clients should invest higher on standing processing units.
TASK 3: Data Types
(a) The major difference between cyclical domain figures and cross-sectional data is
typically measurable quantities are made up of a multitude of elements with different
temporally limits, but cross-sectional data shows attributes across the same time period.

0 3 3 3 1 4
B D
5 5 8 8 5 9
8 4 12
F
9 1 13
13 4 17
I
13 0 17
Start
Periodic data set relies on a specific element over a predetermined amount of time, while
crossing series data includes many variables at the same time. The food statistics of shop
prices necessitates crossing sectoral data in order to obtain particular demographic
elements at a particular point in time.
TASK 4: Networking
(a) The network diagram is as follows:
0 5 5 5 3 8 8 5 13
A C E
0 0 5 5 0 8 8 0 13
Representation of each decision point:
Early Start Duration Early
Finish
Task
Late Start Slack Late
4 2 6
G
11 7 13
0 8 8
H
9 9 17
17 3 20
Finis
h
J
17 0 20

0 5 5 5 3 8 8 5 13
20017
J
20317
Finish
Finish
0 5
E
8 0 13
(b)
4 2 6
G
1 7 1
1 3
0 8 8
H
9 9 17
0
A
805
C
Start
8 4 12
F
9 1 13
13 4 17
I
1 0 1
3 70 3 3
B
5 5 8
3 1 4
D
8 5 9

A task with such a lag value of 0 is referred to as a "crucial route." The crucial path for
this software is A-C-E-I-J.
It would require 20 weeks to finish this project:
Duration (A-C-E-I-J) = 5+3+5+4+3 = 20 weeks.
(c) Non-essential activities can commence and stop whenever they choose, while vital
activities should have a predetermined beginning and stop period. Non-critical jobs have
a lot of extra variables which can be delayed, but crucial procedures have none. The
linear section of the route is referred to as an element of the network. This program's non-
critical activities are B, D, F, G, and H.
TASK 5 Relationships
(a) The matrix for sales profit, total cost, average deal value, and net earnings are as follows:
Sales
Revenue
(£'000)
Total
Costs
(£'000)
Average Order
Value
(£)
Gross
Profit
(£'000)
Sales Revenue
(£'000) 1
Total Costs (£'000) 0.546350669 1
Average Order
Value (£) 0.973533731 0.466050155 1
Gross Profit (£'000) 0.42291345 0.842573515 0.333656281 1
(b) The correlation factor between median deal value and sales revenue has the highest
advantage of 0.973, followed by the correlation factor between total costs and sales
revenue, which has a value of 0.546. As a consequence, the average deal volume is the
best predictor of sales revenue.
(c) The following is a scattering plot of the statistics:

(d) The correlation value is 0.947, showing that an increase in mean deal volume correlates
to a one-component increase in sales revenue. This method can accommodate for 95% of
the variation in average activity volume.
(e) The quantitative equation for regression is as follows:
Y= 0.0309x+10.676
The programme estimates a sales revenue of 10. 676 (£'000) if the deal volume is zero.
There seems to be a 1 element variation in buying cost after just a 0.0309 comparable change in
periodic sales revenue.
TASK 6: Expected values
1. The coefficient of variation may be calculated using the following linear model:
CV = Standard deviation/expected value Assumed, for project A
EV= £48.0 and S.D = £31.08
CV for venture A = 31.08/48 =0.6475
For venture B
EV= £42.2 and S.D = £14.32
CV for venture B = 14.32/42.2= 0.3393
2. The CV depicts the risk connected with a change in anticipated outcomes. Since the
danger in venture B (0.339) is so low, the retailer should choose it.
TASK 7:
Individualized learning is a teaching strategy. The goal is to develop educational systems
and teaching methodologies that can do more than simply discover the most suitable and
effective material for students. Personalized learning emphasises student-driven teaching goals,
tools, pace, and sequence. Learners' perspectives on learning goals, substance, strategies, and
scheduling would almost certainly differ at some time as they seek for capability which meets
defined criteria. In a truly customized learning context, seclusion and customization are not more
important. It facilitates students' accessibility to information via project-based learning. In
addition to attain the project's specified purpose, various students will have to acquire various
talents. In the case of quantitative understanding, for example, some information often lacks a
Scatter plot between Sales Revenue (£'000) and Average order value
120.00
100.00
80.00 f(x) = 0.03 x + 10.68
R² = 0.95
60.00 Average Order Value (£)
Linear (Average Order Value (£))
40.00
20.00
0.00
0 500 1000 1500 2000 2500 3000
Average Order Value (£)
Sales Revenue (£'000)

full picture of the data. During conducting this project, I learned a set of mental strategies that
may have an impact on our daily activities. Marketing automation is something I'd like to
understand more about.
PART 2
The high-low strategy that splits composite spending into fixed and variable costs, should be
used by Andreea Ltd.'s advertising agencies, depending on the facts. The approach for estimating
variable expenses is as follows:
= High price- Low price/ no. of max. manufactured unit- no. of max. manufactured unit
= 410000-193200/(36000-14320)
= 10 per units
This equation could be used to determine permanent costs:
= High price- High variable price
= 410000- (36000*10)
= 4100000-360000
=50000
Intermediate costs vary based on the firm's conditions, like employees, salary, and net
volume. Fixed costs stay unchanged irrespective of the degree of production.
The net amount of items at which total revenue and expenditure are equivalent and that
there is no gain or deficit is referred to as the "breakeven point." The following formula can be
employed to calculate the contributions margin:
= Fixed price/ sale price per unit- variable cost per unit
= 50000/ (15-10)
= 10000 units
To break even, Andreea Ltd. intends to generate 10,000 t-shirts and market them in January
2021.
Targeted profit = Fixed cost+ desired profit/contribution margin
= 250000/5
= 50000units
To make the financial targets in January 2021, Andreea Ltd. requires to generate 50000 pieces of
t-shirts.
To estimate the margin of safety, we must first determine the planned and breakeven revenues.

Budgeted sales= 50000 units * 15
= 750000
Contribution margin ratio= Fixed cost/total contribution margin/budgeted sales
= 50000/ (250000/750000)
=150000
Margin of safety= Budgeted sales-Breakeven sales
= 200000-150000
=50000
The margin of safety refers to the total number of things whereby a decrease in income
would not lead in a shortfall.
Limitations of the breakeven point concept- In a breakeven analysis, everything is held
constant. The selling cost is believed to be stable, while the fixed cost is clear. It's not practical.
There really is no simple process of dividing all expenditures into fixed and variable costs. It
does not reflect differences in product layout.