Spss Assignment1

Develop research hypothesis

Hypothesis 1: whether there is a significant relationship between price and total revenue depends on demand elasticity of the products. If the demand of a product is elastic, there will be a significant negative correlation between price and sales revenue. If the demand of a product is inelastic, there is no significant relationship between price and total sales revenue.

The total sales revenue is calculated as the quantity multiplied by the unit price, which means the quantity and price are considered as the most important factors when assessing the sales performance. It is said from the article that the quantity of the product is highly sensitive to the change of the price if the product has elastic demand such as beverages. A 1-percent price change may lead to a 5-percent change of sales volume. On the contrary, if the product has inelastic demand such as cigarettes, the quantity of the product isn’t so sensitive to the price change, which means a 1-percent price change may only lead to 1-percent change of the quantity demand. Therefore, if the product has elastic demand, there will be a negative correlation between price and the revenue. If the product has inelastic demand, the revenue will increase when price rises even the sales volume decline slightly.

Reference:

Jenifer Tuck. The Relationship Between Price Elasticity & Total Revenue. Chron. Retrieved from

http://smallbusiness.chron.com/relationship-between-price-elasticity-total-revenue-24544.html

Hypothesis 2: There is a significant relationship between advertising cost and sales revenue.

The article assessed the effectiveness of advertising in a company’s sales performance including total sales revenue and sales profitability. The author first made a hypothesis that there is a significant relationship between advertising expenditure and total sales revenue according to some prior research findings. He then adopted correlation and regression analysis to test this hypothesis and finally proved his statement since the regression result implied that the relationship between advertising expenses and sales revenue as a control variable jointly explained about 91%, the rest percentages may due to other factors such as the product promotion or the brand reputation. Therefore, there is a significant relationship between advertising cost and total sales revenue.

Reference:

Abdullahi, Dauda (2014) Assessment of Advertising on the Sales Revenue and Profitability of Nigerian Bottling Company Plc. European Journal of Business and Management

Data collection

Test hypothesis 1:

1. Divided all gas stations into two groups. Group A: gas stations located in residential areas. Group B: gas stations located in non-residential areas.
2. Collect data about monthly average price in each gas stations in group A and group B.
3. Collect data about monthly revenue in each gas stations in group A and group B.
4. Conduct regression analysis about the relationship between monthly average price and monthly revenue in group A and group B respectively.
5. Interpret the results of two groups and give a conclusion.

Test hypothesis 2:

1. Divided all gas stations into two groups according to the location. Group A: gas stations located in residential areas. Group B: gas stations located in non-residential areas.
2. Gather the information about the monthly advertising cost in each gas station in group A and group B.
3. Gather the information about the total monthly sales revenue in each gas stations in group A and group B.
4. Conduct correlation and regression analysis about the relationship between monthly advertising spending and monthly sales revenue in group A and group B respectively.
5. Interpret the results of the analysis and make a conclusion.