Data was collected in 2006 for the European agri-business companies, which sell mainly food and drinks. The sales in the table are registered in billion Euros. The table in the appendix shows that Nestle is the company ahead and has the largest number of sales and employees. Nestle is on top with 22.

7 billion Euros with 71.000 employees (see Appendix – part 1 figure 2.1). The other companies range between 2 and 8.8 billion Euros and the number of employees range between 4.

800 and 38.900.It is possible that the size of an organization plays a role in the size of its business. The word possible is necessary here because it is not always like that. As we see in the appendix table that for example the company with the lowest number of sales, Ebro Puleva (2 billion), has more employees than Tate & Lyle (4.800 employees and 3.5 billion) while they have a bigger number of sales than Ebro Puleva.

However, I suggest that there could be a correlation between the number of employees and the sales. Graph 1.1 shows this relationship:The graph illustrates the relationship between the number of sales and the number of employees is linear with the correlation coefficient of 0.922568. This means that there is a strong linear relationship between the number of sales and employees. 0,8511 or 85% of the variation in sales can be explained by a linear relationship with the number of employees. The remaining 15% can be explained with other factors such as economy, market influence, training and development approaches etc.The regression analysis is: 0.

Best services for writing your paper according to Trustpilot

Premium Partner
From $18.00 per page
4,8 / 5
4,80
Writers Experience
4,80
Delivery
4,90
Support
4,70
Price
Recommended Service
From $13.90 per page
4,6 / 5
4,70
Writers Experience
4,70
Delivery
4,60
Support
4,60
Price
From $20.00 per page
4,5 / 5
4,80
Writers Experience
4,50
Delivery
4,40
Support
4,10
Price
* All Partners were chosen among 50+ writing services by our Customer Satisfaction Team

2562 number of employees + 0.0799 = number of sales. This means, according to the regression analysis that for each additional thousand employees an extra 0.

2562 billion or 256.2 million Euros would be earned. It is possible, but this also means that if thousand employees would be fired, the company would lose 256.

2 million. So if using the number from the regression analysis data set, the number of sales would be predicted by the numbers of employees. But we must be careful, because if we compare two companies from the list and took for example Sudzacker and Cadbury Schweppes. Sudzacker’s sales are 5.8 billion and have 19.600 thousand employees. The sales of Cadbury Schweppes, on the other hand, are 3.

4 billion and they have 23.500 employees.From this example we see that a higher number of employees is not necessarily the factor of a higher sales. So, the validity of the prediction is limited and must be considered along with other factors. The prediction must be caution. Even Nestle, according to the equation, earned more than they should. They should have earned �18.

1 billion instead of 22.7 billion. Part 2 – Value of retail sales from food stores Data was collected from food stores in the UK about the value of retail (see appendix – part 2, figure 2.4) Figures are expressed in index numbers, with 2005 as a base year (2005=100). The sales were measured on a quarterly basis, starting from the 1st of 2003 until the 3rd quarter of 2009 (27 quarters).

In this graph (graph 1.2) we can see how the sales were evolved. Thus, we see that in every first quarter of the year, when it is winter, the sales are the lowest. In the second quarter, when it is spring, the sales go up.

The third quarter the sales go a little down. Then the fourth and last quarter the sales go amazingly high comparing with the third quarter. There is a high possibility that the December days are the cause. People buy more food during Christmas time and the holidays in December. Also the second quarter can be explained by the spring holidays.

An analysis of the sales data shows that the trend is linear. Centered moving averages and the trend line have been added to the original data, in order to indicate the evolution (graph 1.3). We can see that each year the whole sales have increased steadily, which can be seen also from ascendant orientation of the trend line in the graph. The trend is a straight line of the correlation. The determination ½=0.9773, which is very high.

That indicates that 98% of the variation in the trend is in direct relation with the quarter number.