Essay on Regression model

Submitted By bahae
Words: 1368
Pages: 6

Introduction:

Correlation analysis:
Sales and price:
Price is an important factor for the success of a business. Price is amount of money someone is willing to pay in exchange for an asset or service. It is crucial that the price is not too low that the company does not make profit or if the price is too high less people will be able to purchase the product. Price plays a significant impact on sales. Price and sales tend to have a negative relationship. In other words when price increase demand or sales decreases and vice versa. In an example of this is shown in the sunglasses model for every unit of price cut, sales will rise by 12.11(000). To put it differently whenever the price of the sunglasses is reduced by unit sales will rise by 12.11(000). ADD COMPANY EXAMPLE
Sales and advertisement expenditures
Advertising is usually a paid for announcement that will help inform or promote a particular product, service or event. Most business use advertisements to endorse their products whether through newspapers, television ads, billboards or media. The correlation between sales and advertisement is sometimes subtle. Advertisement does help promote products which may have an increase on sells. There is a positive relationship an increase of advertisements will increase sales. However the impact is not very significant. As seen in the sunglasses company that for every one unit (1000) of advertisement expenditures increased, sales will also rise by 1.92(1000). There is an increase in sales when advertisement expenditures rise however the impact is not as substantial as other independent variables. ADD COMPANY EXAMPLE
Sales and number of households:
The number of households or when population increases that has an increase on sales. When the numbers of households increase it has a positive influence on sales revenue. However this does not have a tremendous impact on sales as seen in the sunglass model. The sales revenue will rise by 0.053 when the numbers of households increase by one unit.
Sales and average sales experience:
Sales experience is when the worker has more years in the selling market. Sales experience plays a role on sales since if the person that is selling the product is persuasive and more familiar with that atmosphere. They will most likely be able to sell the product to the consumer. Therefore the relationship between sales revenue and sales experience is positive so when sales increase sales experience has to increase as well. As shown in the sunglass model; when the average sales experience rise by a unit; sales will also increase by 0.98. This means that the more sales experience the more the sales.
Sales and mean daily hours:
Mean daily hours or hours of sunshine this is when there is more sunlight during the day plays a role in the sunglass marketplace. Sunglasses tend to be sold more during when there is more sunshine. For example sunglasses are usually bought more in the summer and spring rather than in the winter or fall seasons. The sales and sunshine hours have a positive relationship. In other words when daily sunshine hours increase, sunglasses are more likely to be bought. This supported by the sunglasses model the mean daily hour’s increase that will influence the sales revenue to increase by 13.35.
Regression analysis:
Regression model
Sales= 76.05055-12.1145Price+1.916498Advert+0.05375796No.Households+0.9811673SaleExperience+13.44926DailyHours
Goodness of fit/ Strength of regression:
The goodness of fit is a statistical model that measures how connected a group of served values and the model's predicted values are.
Multiple R- 0.995159 or 99.5%
Since the multiple R is 99.5% that means that there is an almost perfect correlation between the dependent variable which is sales and the independent variables which are price, advert experience, number of households, average sale experience, and the hours of sunshine.
R Square- 0.990342 or 99.03%
R-square measures the square of the relationship