Assessment of the Nature of Car Markets
An expert who works for a car magazine obtained random data (rounded to the nearest thousand) among two categories of used or new cars:
The expert would like to understand sales based on list price (rounded to the nearest thousand dollars), sale price (rounded to the nearest thousand dollars), and number of days it takes to sell each car.
Assessment of the Nature of Car Markets
An understanding of market dynamics in every venture is necessitated, especially with time’s progression in which economic turbulences become more prevalent. For competitive advantage, the interests of stakeholders and potential investors alike have escalated to dissection of market knowledge to avert the dismay while enhancing risk management (Storr, 2013). Based on this and other reasons, empirical evidences that enhance an understanding of the nature of markets have been widely published with a primal targeting of the corporate investors. However, the challenge of most published market overview reports have been on validation questions of the dashboards mostly presented, as most present visualizations inclined to false audience impression (Kirkpatrick II & Dahlquist, 2010). This paper reports an assessment of the random data for the car industry, with the bid of extracting valuable information and inclining clear understanding of the dataset while also answering rising questions on the nature of the data.
The random dataset includes categories of new and used cars in terms of origin as foreign or domestic. The variables are list price (rounded to the nearest thousand dollars) – which denotes the manufacturer’s suggested retail price (MSRP), sale price (rounded to the nearest thousand dollars) – which is the price at which the cars were finally sold inclusive of any reduction or discounts, and the number of days it takes to sell each car. General descriptive analysis is executed on the data to extract important insights geared towards integrating the nature of car sales.
The mean sale price of domestic cars was $37,378 (SD = 18.4999), which is less than the list price which was $39,949 (18.5733), as expected. The median of the list price is $41,400 while that of sale price was $39,050, indicating that both prices were skewed to the left (a larger portion of cars sold were at a price higher than the Mean, a phenomenon similar to their list prices). The range of list prices was $62,500 while that of Sale prices was $63,500. The coefficient of variation (CV) for list price 46% while that of Sale Prices is 49%, with the mean being corrected to thousands. Averagely, the cars took 29.9 (SD = 15.8805) days to be sold, with a mode of 29 days. The variable is slightly positively skewed, this means that most of the cars were actually sold in less than 29.5 days. The range, however is 56, which is large. The standard deviation for “days to sell” variable was 53% of the mean. There was no outlier for any of the variables. None of the variable observations was an outlier.
The estimated 98% confidence interval for population mean of Sale prices of domestic cars is between $34,310 and $40,446, with a margin of error of $3,068. Moreover, there is 98% confidence that the population mean sale days for these cars is from 27.27 days to 32.53 days (Margin of Error = 2.6335). This means that there is 98% confidence that any domestic car will be sold in between 27.27 days and 32.53 days at prices ranging between $34,310 and $40,446.
The 98% confidence interval for the mean sale price of foreign cars is between $47,771 and $57,146, with a margin of error of $4,688. The 98% confidence interval for sale days of foreign cars is between 43.55 days and 51.98 days (MOE = 4.22). This means that there is 98% confidence that any foreign car will be averagely sold for prices between $47,771 and $57,146 in a period averagely ranging from 43.55 days to 51.98 days.
The domestic cars have a higher stock flow rates due to the relatively lower prices as compared to the foreign cars.
Kirkpatrick II, C. D., & Dahlquist, J. A. (2010). Technical analysis: the complete resource for financial market technicians. FT press.
Storr, V. (2013). Understanding the culture of markets. Routledge.