BMT Simple linear regression
BMT Simple linear regression (HL)
Is somebody getting fired?
The CEO of X-peng (a Chinese car company) has asked for reliable data on sales people at the firm from one of their smaller, regional offices!
The CEO is pretty displeased with sales performance and wanted to see if there exists a link between years at the firm (experience) and volume of sales made.
To shed some light on this issue, the CEO decided to convene a team to examine the issue.
QUESTIONS: IS SOMEBODY GETTING FIRED?
- Using the data above, use a scatter diagram to plot the data to show sales per month against years at Xpeng [4]
- Draw an appropriate line of best fit [1]
- Identify the two outlying data points (members of the sales team) from the scatter diagram [2]
- Using your response from question 3, suggest what they mean in terms of these two members of staff [4]
- Interpret (using the scatter diagram) whether or not the number of years and sales are correlated strongly, weakly or not at all [2]
- Determine which member of staff is in most need of training in order to improve their monthly sales [1]
- Suggest whether or not there is an argument to introduce performance related pay (which is something that both Kate and James would like to see introduced) [2]
Sales of Edrive cars
The Chinese EV market is booming, with loads of new car makers coming to the market. Here we focus on ‘Edrive.
The manager wants to forecast sales into the future to help plan materials and staff required to budget.
Since beginning trading, the company has seen some quite significant swings in terms of sales!
The sales data for Edrive can be seen on the right!
QUESTIONS: WHAT HAPPENS NEXT FOR EDRIVE?
- Plot a scatter diagram of the sales for Edrive (sales on the Y axis and months on the x axis) [4]
- Comment on your findings from your scatter diagram [2]
- Draw an appropriate line of best fit for Edrive [1]
- Using the technique of extrapolation, forecast the likely sales for the following January and February [2]
Unit BMT Simple linear regression overview
Linear regression models are statistical methods employed to identify the apparent relationship between two variables, such as marketing expenditure and sales revenue, or the seasonal effects on the demand for specific goods and services.
These techniques are:
Scatter diagrams
The ability to ascertain correlation enhances business decision-making and strategic planning!
SUGGESTED ANSWERS TO...
1 Using the data above, use a scatter diagram to plot the data to show sales per month against years at Xpeng [4]
2 Draw an appropriate line of best fit [1]
3 Identify the two outlying data points (members of the sales team) from the scatter diagram [2]
Kate and James seem to be the two outlying members of staff who are performing ahead of the other members of the sales team.
4 Using your response from question 3, suggest what they mean in terms of these two members of staff [4]
Kate:
James:
5 Interpret (using the scatter diagram) whether or not the number of years and sales are correlated strongly, weakly or not at all [2]
Correlation suggests that the two variables are related (years of work and number of sales) in this case! The scatter diagram does show correlation, which is to be expected. Whist there are outliers, there is a reasonably strong correlation between the two variables.
6 Determine which member of staff is in most need of training in order to improve their monthly sales [1]
The scatter diagram is not that useful when it comes to identifying the under-performer!
One way to examine the data would be to quantity how many sales on average does one years experience lead to.
For example, for Kate (the star performer) 17 sales per month / 2 years experience gives an average of 8.5 cars sold per year of experience!
However, at the other end of the spectrum is Sally with 22 sales per month / 13 years which gives the lowest number pf 1.6 cars sold per month for each year of experience
7 Suggest whether or not there is an argument to introduce performance related pay (which is something that both Kate and James would like to see introduced) [2]
There is a general trend of more experience equates to more cars sold. However, the manager may wish to invest in more training for the following reasons:
1.) Kate has shown that inexperienced staff can sell high volumes!
2.) The reverse is true!
3.) The manager may wish to cement this trend by incentivizing through increased pay.
4.) There are many arguments to support the introduction with PRP, certainly for Kate and James who desire more money for their extraordinary sales success.
