Financial Analysis Report: Company Performance and Stability

This report conducts a comprehensive financial analysis of 40 companies spanning 22 sectors, evaluating their performance and stability. The analysis encompasses revenues, operating expenses, net profits, number of employees, and price. The report constructs frequency distribution tables, presents data through charts, and offers insightful comments on the findings. A cross-tabulation of sectors and profits is created, with a stacked bar chart illustrating profit distribution within each sector. Key statistical measures, including mean, median, standard deviation, and IQR, are calculated for the number of employees, with a histogram and skewness analysis to assess distribution shape. Point estimates and confidence intervals for the population mean and standard deviation are also computed. Furthermore, the report develops a scatter diagram to analyze the relationship between operating expenses and net profits, estimates a regression equation, and assesses the significance of the slope variable through hypothesis testing. The findings reveal skewed employee data, profit distribution patterns across sectors, and the positive influence of operating expenses on net profits.

Assignment Instructions (attempt all tasks)
Introduction
This report seeks to analyse the financial as well as the stability of different
companies in different sectors. We randomly selected 40 companies and analysed
them in terms of the revenues, operating expenses, net profits, number of
employees and price.
Task 1: Selection of companies
Answer
This section seeks to select 40 companies from various 22 sectors which are –
Household & Personal Products; Materials; Banks; Food, Beverage & Tobacco;
Telecommunication Services; Pharmaceuticals, Biotechnology & Life Sciences;
Utilities; Insurance; Transportation; Commercial & Professional Services; Consumer
Services; Food & Staples Retailing; Capital Goods; Diversified Financials; Health
Care Equipment & Services; Consumer Durables & Apparel; Energy; Retailing;
Media & Entertainment; Real Estate; Software & Services ; Technology Hardware &
Equipment. The results are provided in the excel.
Task 2
For each of the 5 quantitative variables construct a percentage frequency distribution
table and present the data using appropriate charts. Comment on your findings.
Answer
Percentage frequency distribution table for Price (in Pence)
Class Frequenc
y
Percent
frequency
Cumulative
percent frequency
0-100 1 2.5% 2.5%
101-500 9 22.5% 25.0%
501-1000 12 30.0% 55.0%
1001-5000 15 37.5% 92.5%
5001-10000 3 7.5% 100.0%

As can be seen from the above chart, most (37.5%) of the prices fell in the 1001 to
5000 category while the least (2.5%) were in the class of 0-100.
Percentage frequency distribution table for Operating Expense (In £million)
Class Frequenc
y
Percent
frequency
Cumulative
percent frequency
0-500 8 20.0% 20.0%
501-1000 4 10.0% 30.0%
1001-5000 16 40.0% 70.0%
5001-10000 1 2.5% 72.5%
10001-20000 8 20.0% 92.5%
20001-50000 3 7.5% 100.0%

For the operating expense, most (40.0%) of them values were between 1001 – 5000
while the least (2.5%) of them were between 5001-10000
Percentage frequency distribution table for Number of Employees
Class Frequenc
y
Percent
frequency
Cumulative percent
frequency
0-1000 3 7.5% 7.5%
1001-10000 9 22.5% 30.0%
10001-50000 13 32.5% 62.5%
50001-100000 7 17.5% 80.0%
100001-500000 7 17.5% 97.5%
500001-
1000000
1 2.5% 100.0%
The above plot shows that most of the company employees selected are between
10001-50000. The least number of employees are between 500001-1000000.
Percentage frequency distribution table for Revenue (in £ million)
Class Frequenc
y
Percent
frequency
Cumulative percent
frequency
0-1000 3 7.5% 7.5%
1001-10000 16 40.0% 47.5%
10001-50000 16 40.0% 87.5%
50001-100000 3 7.5% 95.0%

100001-200000 2 0.0% 100.0%
For the revenue, the most frequent revenue earnings were between 1001-10000 and
between 10001-50000. The two groups accounted for 80% of where the company
revenue fell in.
Percentage frequency distribution table for Net Profit (in £ million)
Class Frequenc
y
Percent
frequency
Cumulative percent
frequency
0-100 2 5.0% 5.0%
101-500 7 17.5% 22.5%
501-1000 9 22.5% 45.0%
1001-5000 20 50.0% 95.0%
5001-15000 2 5.5% 100.0%

Lastly, most of the company’s net profit for the companies ranged between 1001-
5000 million euros.
Task 3
Prepare a cross tabulation using sectors (rows) and profits (columns). Compute row
percentages for the cross tabulation and construct a stacked bar chart showing the
percentage distribution of profits within each sector type. Comment on the
relationship between variables.
Answer
Count of Profits Grouped profits
Row Labels 0-100 101-
500
501-
1000
1001-
5000
5001-
15000
Grand
Total
Banks 2 2
Capital Goods 2 2
Commercial & Professional Services 2 2
Consumer Durables & Apparel 2 2
Consumer Services 2 2
Diversified Financials 1 1 2
Energy 1 1 2
Food & Staples Retailing 1 1 2
Health Care Equipment & Services 1 1 2
Insurance 2 2
Materials 1 1 2
Media & Entertainment 1 1 2
Pharmaceuticals, Biotechnology & Life
Sciences
1 1 2
Real Estate 2 2
Retailing 1 2 3
Software & Services 2 2
Technology Hardware & Equipment 1 1
Telecommunication Services 1 1
Transportation 1 1 2
Utilities 1 2 3
Grand Total 2 7 9 20 2 40
Percentage rows
Count of Profits Grouped profits
Row Labels 0-100 101- 501- 1001- 5001- Grand

500 1000 5000 15000 Total
Banks 0% 0% 0% 100% 0% 100%
Capital Goods 0% 0% 0% 100% 0% 100%
Commercial & Professional Services 0% 0% 0% 100% 0% 100%
Consumer Durables & Apparel 0% 0% 100% 0% 0% 100%
Consumer Services 0% 0% 0% 100% 0% 100%
Diversified Financials 0% 0% 50% 50% 0% 100%
Energy 50% 0% 0% 50% 0% 100%
Food & Staples Retailing 0% 0% 50% 50% 0% 100%
Health Care Equipment & Services 0% 50% 50% 0% 0% 100%
Insurance 0% 0% 0% 100% 0% 100%
Materials 0% 0% 0% 50% 50% 100%
Media & Entertainment 0% 0% 50% 50% 0% 100%
Pharmaceuticals, Biotechnology & Life
Sciences
0% 0% 0% 50% 50% 100%
Real Estate 0% 100% 0% 0% 0% 100%
Retailing 33% 0% 67% 0% 0% 100%
Software & Services 0% 100% 0% 0% 0% 100%
Technology Hardware & Equipment 0% 100% 0% 0% 0% 100%
Telecommunication Services 0% 0% 0% 100% 0% 100%
Transportation 0% 50% 0% 50% 0% 100%
Utilities 0% 0% 33% 67% 0% 100%
Grand Total 5% 18% 23% 50% 5% 100%

The stacked bar chart above shows that most of the sectors had their profits ranging
between 1001-5000. Sectors such as banks, capital goods, commercial &
professional services, consumer services, insurance and telecommunication
services had 100% of their profits falling between 1001-5000.
Task 4
Compute the mean, median, standard deviation, IQR (Interquartile Range) for the
number of employees and comment on your results.
Answer
Mean=∑ xi
n = 281+285+638+…+ 241000+ 464520+527180
40 = 2774181
40 =69354.53
To calculate the median, we arrange the data in ascending order. The median falls
between the 20th value and 21st value
20th value = 25531
21st value = 26146

Median= 20 thvalue +21 st value
2 =25531+26146
2 = 51677
2 =25838.50
Standard deviation= √Variance
Variance=∑ ( xi−x ) 2
n−1 = ( 281−69354.53 )2 + ( 285−69354.53 ) 2 + ( 638−69354.53 ) 2+ …+ ( 527180−69354.53 )2
40−1 =
Standard deviation= √Variance= √12,683,010,424.92=112,618.92
To compute the interquartile range we need to compute the 1st quartile and the third
quartile
1 st quartile= 10 thvalue+11 th value
2 =6121+8335
2 = 14456
2 =7228
3 rd quartile=30 th value+31 st value
2 = 80418+92000
2 = 172418
2 =86209
Interquartile range (IQR) = 86209-7228=78981
Skewness=∑ ( xi−x ) 3
s3 (n−1) = 1.59236 ×1017
1.357 ×1015∗39 =3.009
As can be seen, the average number of employees for the selected companies is
69354.53 with the median number of employees being 25838.5. The interquartile
range is 75532. This values shows that the data on number of employees is widely
varying.
Draw a histogram using the data on the number of employees and calculate the
skewness. Comment on the shape of the distribution.
Answer

The above histogram shows that the data on number of employees is not normally
distributed but is rather sewed to the right (long tail to the right).
Skewness
The value of skewness was found to be 3.009; this value clearly shows that the data
set on number of employees is highly positively skewed.
Task 5
Calculate the point estimate of the population mean and population standard
deviation of the number of employees. Compare the estimates to the population
parameter.
Answer
Point Estimate Population parameter
Population Mean 69,354.5 69,354.5
Population Standard deviation 111,202.3 112,618.9
The point estimate of the population mean of the number of employees are the same
however, there is slight difference in the point estimate if the population standard
deviation of the number of employees.
Construct a 95 percent confidence interval for the population mean for the number of
employees. Interpret your results.
Answer
C . I=x ± zα/ 2 S . E

x=69354.5; zα / 2=1.96
S . E= 112,618.9
√ 40 =17806.612
C . I =x ± zα/ 2 S . E →69354.5 ± 1.96∗17806.612=69354.5± 34900.959
Lower limit: 69354.5−34900.959=34453.541
Upper limit: 69354.5+34900.959=104255.459
Thus from the above we are 95% confident that the true population mean of the
number of employees is between 34453.541 and 104255.459.
Task 6
Develop a scatter diagram to analyse the relationship between operating expenses
and net profits, where operating expenses is the independent variable and net profits
the dependent variable. Comment on the relationship.
Answer

The scatterplot above shows that there is a positive linear relationship between net
profit and operating expenses. Increasing operating expenses is likely to result to an
increase in the net profit.
Estimate the regression equation using the above variables and comment on the
slope variable.
Answer
The following are the formulas for the coefficients;
a=∑ y ∑ x2−∑ x ∑ xy
n∑ x2 − ( ∑ x )
2
b= n∑ xy−∑ x ∑ y
n∑ x2− ( ∑ x )
2
a= 74081∗5873038449−276932∗1018960056
40∗5873038449−2769322 =966.3004
b= 40∗1018960056−276932∗74081
40∗5873038449−2769322 =0.1279
From the calculations we can estimate the regression equation as;
Net Profit=966.3004+ 0.1279(Operating Expense )
The coefficient of operating expense is the slope and this value is given as 0.1279;
this value implies that a unit increase in the operating expenses would result to an
increase in the net profit by 0.1279. Likewise, a unit decrease in the operating
expenses would result to a decrease in the net profit by 0.1279
Find the coefficient of determination (R-squared) and comment on its value.
Answer
The coefficient of determination (R-Squared) is given as 0.3354; this means that
33.54% of the variation in the net profit is explained by the operating expenses in the
model.
SUMMARY OUTPUT
Regression Statistics

Multiple R
0.5791
42
R Square
0.3354
05
Adjusted R
Square
0.3179
16
Standard
Error
1837.4
02
Observations 40
Calculate the t-statistic and test whether the slope variable is significant using
hypothesis testing.
Answer
The t-statistics for the slope is 4.37923. This value is greater than the critical t-value.
Further the p-value is seen to be less than 5% level of significance. We therefore
reject the null hypothesis and conclude that the slope is significant at 5% level of
significance.
Coefficient
s
Standar
d Error
t Stat P-
value
Lower
95%
Upper
95%
Intercept 966.2907 353.9897 2.7297
1
0.0095
5
249.68 1682.9
1
Operating Expense
(in £million)
0.127934 0.029214 4.3792
3
0.0000 0.0687
9
0.1871
Conclusion
This paper sought to analyse the financial as well as the stability of different
companies in different sectors. We randomly selected 40 companies and analysed
them in terms of the revenues, operating expenses, net profits, number of
employees and price. The following are the key findings;
 The dataset on the number of employees is heavily skewed (skewed to the
right)