The future of the industry.

David Vaughn

Qnt/561

12/02/2019

Dr. Heidi Carty

The future of the industry.

The reason to be involved in the work process changes for the people and the industry, not just because of the love of what they do it can be the sole purpose of making money. Being in a lucrative industry may take the study and patience to find the job that may be considered your field of choice. The study and interview process bolstered by the confidence of a degree or knowledge of the field. I will now take this knowledge that has been gained and use it to discuss the financial future of a chosen field. Using the excel data and my textbook I will apply inferential and descriptive techniques to forecast the future of a company.

**Part 1: Preliminary analysis**

** **I want to describe the future of the company based on the sales data. Looking over the data I will be able to provide a volatility and earnings per share. There are also a few more other important financial ratios that can be calculated based on the excel spread sheet. So I will be address the financial ratios. Which will in turn describe the financial future of any company discussed. For this assignment I choose Texaco. I will discuss Texaco financial future.

The population I have chosen to discuss is based upon the financial industry. With a wealth of companies to choose from I have taken one that seems familiar to me, while I can make other choices I feel that a randomly chosen company better displays the techniques I use and my knowledge of the subject. To clarify, I have chosen a company that has a familiar name from a group of similar and finance based companies.

The data within the financial records are quantitative. Albeit for the column that describes the type of company which is qualitative and the numbers could be considered nominal which is used to clarify or classify the companies. For all the other types of data the data is of a higher order. Some of which will be ratio or interval. I will choose to describe then as ratio levels of numbers for comparison.

**Part 2: Descriptive statistics**

** **During this section I will discuss the central tendencies, not just from the standpoint of the company that I have chosen to represent as a part of this assignment. It will cover the industry itself as a whole. This I fell will better describe the functions of the formulas that will lead to not just better financial discussions but comparison.

First I want to add that because no average of this company is giving as well as some other parts of the central tendencies. A description will look like this; **example; **Texaco has a total revenue of $46667 while the industry average is $11,043.37 is this a fair comparison to say that Texaco is at least 50% more lucrative than the industry. I would say yes, as would many others who know that Texaco’s total revenue is what makes part of that total by taking the total sum of all the revenues and then dividing them by the total amount of companies in that industry giving the mean or industry average. While the entire assignment will not look this way at times the comparison can be made from the gathered data. So, the next paragraph will discuss the central tendencies for the entire industry and if allowed the comparison of Texaco can be shown in relation to those numbers.

So given the previous example of how these numbers can be related to the different companies, I can now describe the central tendencies in greater detail. Beginning with the *mean* and as stated in the previous paragraph it can be found by adding the sum of the grouped data and then divide by the number of the population being described. Next, the median and it can be described as the middle most number within a set of data. In this case I will choose the total revenue for my set of data. To do so the numbers must be placed in ascending order from lowest to highest, and then the middle most number is chosen as the median. To simplify the process use this formula (n+1) /2 that is the number of a set of data plus 1 then divide by two. Thanks to excel this is much easier and the work sheet provided can be used to make the calculations, giving the answer of $6101.00 making Texaco a top earner in the industry.

The Mode is the number that appears the most often, which in this case shows that the numbers are not repeating. The Range is the highest and the lowest numbers and then the difference between them. With a high in the industry (total revenue) of $137242 and a low of $129 counted in millions. The range is subtracted from these totals leaving a sum of $137113. Standard deviation is the square root of the variance and is 17479.12182 and the variance is calculated by squaring the sum of the totaled data. Leaving 302464502.5 as the answer, I do not believe this needs a dollar symbol placed by it. The coefficient of the variance or cv is the standard deviation divided by the mean of the population then multiplied by 100, this calculated leaves a total of .6318034803 which can be changed into a percent 63.2%.

Finally the five number summary, this is based on the statistics of 1.) The median Q2 $6101 2.) The lower quartile Q1 $2259 and 3.) the upper quartile Q3 $12,818.5, and 4.) The smallest number in a distribution $129, then 5.) The largest number in a distribution $137,242. This surmises the descriptive statistics for this analysis. I will move on the inferential statistics in the following section.

**Inferential statistics: **I thought initially that it would be a problem trying to form a hypothesis for a moderately successful company. Initially, now after studying the spreadsheet I feel that I may be able to increase the total revenue. By using the sample means formula I can try to justify how Texaco can increase its total revenue by 10%.

By using the population mean of µ=11,043.37 I can use the sample means formula set in algebra form it will be used to find my new µ. The algebraic form will look this way, ) My sample mean will be represented by Texaco’s total revenue of $46667. The formula will look this way when I use a confidence level of 90% for my Z score, which is z = 1.645. So, µ = 46667 -1.645() < µ < 46667 + 1.645() this expression says $43791.70 < µ < 49542.31 which is not quite the number that I would hve expected because it falls just short of, $51333.7 which is a 105 increase in Texaco’s total revenue. Thus at this time I must reject = µ and is accepted.

**Conclusion**

I feel after testing my hypothesis that at Texaco’s current state it would be safe to operate under it’s normal capacities. Also the new hypothesis may need more study to be implicated. The business is in fair condition to do so. We are not looking over the information and seeing sub levels to the information. We do not see the demographics nor any other independent or dependent variable for the financial database just numbers. With what looks to be a healthy list of companies Texaco’s numbers are decent. They are not the top company in the industry but have done well enough to not be considered to be in the lower quartile in total revenue. I think any additional information would be great, but with this data base a trend analysis can be formed. In conclusion Texaco is moderately successful.

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