Introduction - Insights from Statistical Analysis of Financial Metrics
This report discusses the data analysis report of the different companies. Through the analysis of the data it has been set the research question, and set the hypothesis of the research. Various statistical analyses have been proved by several hypothetical tests of the dataset. The variable has been classified in the form of a different manner. Here Descriptive statistical analysis has been done of the given company's data set, where it has been discussed the description of the dataset, and knowledge about the chosen data type and their source also. Then descriptive statistics are done in the graphical format and then analyzation occurs. Here frequency distribution of the data also occurred. In the inferential statistical analysis mean median comparison was done.
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What is the difference between asset turnover’s mean over two companies?
What is the comparison between the mean median values of ROE of the two companies?
Which company’s Debt/Equity rate is higher?
2. Hypothesis development
The null hypothesis for this statistical measurement is that there is no distinction between the moderate rates of students who brought the course in the rate of the organization’s financial value and those who did not (Carrasco, et al. 2020). This suggests that a p-value of less than 0.05 disproves the null hypothesis and can conclude that there is a statistically significant difference between the two groups in terms of mean steps.
On the other hand, the data it will operate for this test will be the average rates of the students. It will estimate the mean, median, and standard deviation of the phases for each group. It will then use these values to compute the t-statistic, which will be employed to define the p-value. If the “p-value is smaller than 0.05”.
2.1 Define and classify variables
Name
Type
Width
Decimals
Label
Values
Missing
Columns
Align
Measure
Role
Company
String
1
0
None
None
None
14
Left
Nominal
Input
Date
String
10
0
None
None
None
11
Left
Nominal
Input
AssetTurnover
Numeric
4
0
Asset Turnover
None
None
10
Right
Nominal
Input
ROE
Numeric
1
0
None
None
None
13
Right
Nominal
Input
DebtEquity
Numeric
4
0
Debt/Equity
None
None
11
Right
Nominal
Input
Table 1: Data set of variables
The variables are the company’s financial analysis, Asset turnover, ROE value, and Debt Equity are numeric types.
Name
Type
Width
Decimals
Label
Values
Missing
Columns
Align
Measure
Role
Student
Numeric
12
0
None
None
None
12
Right
Scale
Input
Hoursofstudy
Numeric
12
0
None
None
None
12
Right
Scale
Input
Nooflectures
Numeric
12
0
None
None
None
12
Right
Nominal
Input
Grade
Numeric
12
0
None
None
None
12
Right
Scale
Input
Table 2: Data set of variables of students
In the second data set, the variables are numeric type.
2.2 clear hypothesis statement
Here analyzed mean median, mode analysis, regression analysis and Pearson analysis of the data set.
3. Descriptive Statistical Analysis
3.1 Dataset description
The data sets are provided. The data set is based on the company’s financial ratio. In the data set asset turnover, ROE value and Debt/Equity rate of the company have been described (Patil, 2021). The other data set of the company describes the stock return of the company this data set defines the monthly return of Tesco and S companies.
The sources of the dataset
The data set of the company has been provided.
Types of the Chosen Data
The type of the chosen data is numeric. This data set describes the financial ratios of two different companies. Here is the description of the asset turnover values of the two company, their ROE value and the Debt/Equity rate of the company. As well as here also describes the monthly return of the two companies. All the data are numeric.
Sample size
For conducting this analysis the provided data has been the total data of the company taken from September 1998 to Aug 2016. In this data set discuss the asset turnover value, ROE value and Debt/Equity value of the provided company.
From the upper figure it has been found that total asset Turnover is 70, ROE value is 70, and Debt/Equity value is 70.
ROE
Frequency
Per cent
Valid Percent
Cumulative Percent
-
6
8.6%
8.6%
8.6%
0
9
12.9%
12.9%
21.4%
1
1
1.4%
1.4%
22.9%
2
4
5.7%
5.7%
28.6%
3
9
12.9%
12.9%
41.4%
4
7
10.0%
10.0%
51.4%
5
10
14.3%
14.3%
65.7%
6
7
10.0%
10.0%
75.7%
7
4
4.3%
4.3%
80.0%
8
8
11.4%
11.4%
91.4%
9
6
8.6%
8.6%
100.0%
Total
70
100.0%
100.0%
100.0%
Table 4: Result of ROE
From the upper table, it has been found that the total ROE frequency of the two company 70. The percentage of ROE of the two companies is 100. The valid percent of ROE of the two companies is 100.
Figure 1: Result of debt and equity
The frequency of Debt/equity is 70. The total Percent of Debt equity is 100. The total valid percent of Debt equity is 100.
Figure 2: Bar chart showing the result of debt
The upper graph describes the asset turnover of the two companies. The X axis defines the Asset turnover of two companies and the “Y axis defines the frequency of two companies”.
Figure 3: Result of ROE
Source:
The upper graph describes the ROE value of the two companies. The X-axis describes the ROE value and the Y-axis defines the frequency.
Figure 4: Bar chart showing result of ROE
The upper graph defines the Debt/Equity of the two companies. The X-axis define the Debt/Equity and the Y-axis describe the frequency.
Data set 2:
Variable
N
Minimum
Maximum
Mean
Std. Deviation
Variance
Kurtosis
Std. Error
Student
36
1
36
18.50
10.536
111.000
-1.200
0.768
Hoursofstudy
36
10
160
79.86
39.758
1580.694
-0.721
0.768
Grade
36
15
82
54.47
16.688
278.485
-1.140
0.768
Nooflectures
36
0
8
4.72
2.537
6.435
-0.552
0.768
Table 5: Descriptive statistics
The description of the upper figure, and the descriptive statistics of the data set. For conducting this descriptive statistic the total number of students is 36. The minimum number of study hours is 10. The maximum number of study hours is 160 (Washington, et al. 2020). The mean value of study hours is 79.86. The standard deviation of study hours is 39.758. The variance of hours of study is 1580.69. The kurtosis standard is -721. The minimum grade value is 15. The maximum grade value is 82. The mean statistics of grade is 54.47. The standard deviation of the grade is 16.68. The variance statistics value of the grade is 278.485. The kurtosis statistics of grade is -140.
3.4 Frequency distribution
The frequency analysis occurs of Asset turnover, ROE value and Debt equity of the company. The mean median and mode values are described.
Variable
N
Minimum
Maximum
Mean
Std. Deviation
Variance
Kurtosis
Std. Error
Student
36
1
36
18.50
10.536
111.000
-1.200
0.768
Hoursofstudy
36
10
160
79.86
39.758
1580.694
-0.721
0.768
Grade
36
15
82
54.47
16.688
278.485
-1.140
0.768
Nooflectures
36
0
8
4.72
2.537
6.435
-0.552
0.768
Table 6: Result of frequency table
The upper figure describes the Asset turnover value of the company. The total frequency of the Asset turnover value is 70. The total valuation of percent is 100. The valuation of valid percent is 100 and “the cumulative percent is 100”.
Measure of location
The measure of the location of the data is taken from an Excel data set. Four variants are taken as a data set. The type of the data set is numeric type. Four variables are taken: student, hours of study, number of lectures, and grade.
Measure of variety
There are four varieties of data sets are taken for the data. The variables are students, hours of study, number of lectures and grade. The other data set is a data set of the company. Here describe the asset turnover, ROE value and Debt equity of the company. The type of the data set is a string.
Measure of Association
The first data set helps to measure the data of their company’s asset turnover, ROE value and Debt Equity of T and S Company (Love, et al. 2019). Another set of data helps to measure the data of the student’s hours of study, number of lectures and grades of the students.
4. Inferential statistical analysis
Figure 5: Result of the T-test
Here is the description of the upper figure one sample T-test. The t value of study hours is 12.052, its df value is 35. The mean difference in hours of study is 79.861 (Simeunovi?, et al. 2019). The t value of the number of lectures is 11.169, its df value is 35. “The mean difference is 4.722”. The t-value of the grade is 19.585. The df value of the grade is 35. The mean difference in grade is 54.472.
4.1 Explanation of hypothesis test(s)
Here for the hypothesis test, Variable classification well-distributed
The variables contain versatile samples.
Through this hypothesis test, Systematic sampling, Stratified sampling, and Cluster sampling are done effectively.
Hypothesis testing is an effective tool for the design-making about the parameter which is based on the sample data. This allows to creation of interferences about the sample-based data and then utilizes this interference to create the decision (Meeker, et al. 2022). Through this hypothesis testing it helps that the assumption of their population is correct and it helps to create decisions accordingly. This is an effective tool for making a variety of situations that are used in different fields.
The one sample test is occurred. The t value of Asset turnover is 47.88, its df value 67, and the mean difference value is 790. The t value of ROE is 13.12. The df value is 63. The mean difference is 4.609. The t value of debt/equity is 13.247. The df value is 69.
4.3 Discuss & interpret the results
After the interpretation of the 1st data set is based on the company’s Asset turnover, ROE value and Debt/Equity it is analyzed that the t value of Asset turnover is higher (Lüdecke, et al. 2021). The debt/equity value of df is 69. The mean difference in asset turnover is 790.
The description of the upper figure is the T-test analysis of the company’s Asset turnover, ROE value and Debt/Equity value. The total number of Asset turnover is 68, its mean value is .79, and the standard deviation value is .136. The total ROE value is 64, its mean value is 4.61, its standard deviation value is 2.809 (Onyutha, 2021). The mean of std. error is .351. The total number of debt/equity is 70, its mean value is 62, and the standard deviation value is .392.
Figure 7: Result of the T-test
The description of the upper figure is the T-test of the second data sample. The total number of hours of study is 36, its value of mean is 79.86, and the value of standard deviation is 39.758. The standard error mean is 6.626 (Jiang, et al. 2019). The total number of lectures is 36, its mean value is 4.72, and the standard deviation value is 2.537. The mean of the standard error is 243. The total number of grades is 36. The value of mean the grade is 54.47. The grade of standard deviation is 16.688. The standard error is 2.781.
mean/median comparison
From the company’s financial data set analysis, it has been found that the Asset turnover mean is higher than ROE and Debt/equity mean value.
In another student data set the mean hours of study is higher than the number of lectures and grade values. The mean hour of study is 79.86.
Association
Figure 8: Result of the correlation
The upper figure describes the Pearson correlation test, student and hours of study are taken as variables. The total number of students is 36. Hours of study are .129, .453 and 36.
The description of the upper figure, is the Pearson correlation test of the following two credentials Asset turnover and ROE value. The Pearson correlation of asset turnover is 1 and the ROE value is -019. The Pearson correlation of ROE value is 1.
5. Discussions and Conclusions
5.1 Summary of Findings
In this statistical data analysis report, mean median, mode, T-test, regression analysis and Pearson test have occurred of the provided two data samples.
5.2 Possible limitations of the data analysis contained in the dataset
There are so many limitations present in the data set, the sample size is short, errors in the variable distribution, and large variables (McElreath, 2020). The data set is limited which is not properly reflect the research study. The set of the data is biased by the methods that are used to collect the data.
Any issue with the sample size or the representativeness of the sample?
Yes, there is an issue with the sample size and representatives. The sample size is too small, and this is not representative of statistical analysis, resulting in inaccurate results (Shrestha, 2021). If the sample is not chosen randomly the sample may be biased, leading to skewing the outcome.
Any flaws in the chosen hypothesis tests or the linear regression model construction?
The chosen hypothesis test or the linear regression model is simple and fails to capture the data complexity. The assumption of both tests was carefully evaluated (Ansorge, et al. 2021). If the violation occurs, the assumption can lead invalid outcome.
How might these limitations affect the conclusions drawn from the data analysis results?
If the data analysis does not occur properly it leads to an incomplete and inaccurate outcome.
Reference list
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