I have been asked to investigate factors that affect the depreciation
of cars.
I have been asked to investigate factors that affect the depreciation
of cars. To do this I would ideally like to collect my own data about
used cars. This would be called primary data. I would have collected
data on the make, model, mileage, engine size, age, price and price
when new of several hundred used cars. Unfortunately this would have
taken a lot of time, but the advantage would have been that it would
have been reliable data which I could trust, and I could have found
out exactly the information that I wanted.
It would have been impossible for me to do such a large survey,
however, so I had to use secondary data that I got from the CCEA
website. The advantage of this was that it was quick, cheap and easy,
but I can't be sure of the accuracy of these results and I don't know
if any bias was involved when it was being collected. I have also
found that many of the results are incomplete.
From the very start, I am sure that two of these results are wrong - a
Renault Laguna which costs £50,000, and a Renault Clio that increases
in value. I have deleted these results straight away.
Hypothesis 1
My first hypothesis is that cars depreciate more as they get older. I
used the spreadsheet on the computer to test this hypothesis, but
first I had to get the age and percentage depreciation for each car,
neither of which are recorded in the table.
Firstly, to get the age of the cars, I subtracted the year in which
they were made from 2002, the year when the data was collected. I
first created a new column on the spreadsheet and called it age. Then
I typed into the first box under the title the formula for age-
=2002-F2
where F2 is the column for the year the car was made. This filled the
box with the age of the car. I then highlighted the box, right clicked
and selected copy, before highlighting all the boxes below and
selecting paste special, formula. This filled in the ages for all of
the cars.
Next, to get the percentage depreciation, I made another column and
filled it with a more complicated formula-
=(I2-H2)/I2*100
where I2 is the price when new and H2 is the price now. This filled
the first box in the percentage depreciation column with the
appropriate value, and I copied the formula into the other boxes as
before.
I then highlighted these two columns and copied them into chart 2.
The automaker Chevrolet has experienced much technological change in the past 104 years. Although it, Chevrolet, is a French name, it is an American car company. It was primarily founded by William C, Durant, along with Louis Chevrolet, on November 3, 1911. It wasn’t until six years of existence that it became part of the Automotive Division at General Motors, otherwise known as GM. Durant had previously tried to buy out Ford and failed. This caused him to resort to co-founding Chevrolet. The first car sold by the company commonly called Chevy was the Classic Six, at the price of 2,500 dollars. Chevy started producing these vehicles in 1912-1913. The car’s value may seem like pocket change but that is the common day equivalent of roughly 57,000
Noticeable indications of deterioration have been shown in numerous patients few hours prior to a critical condition (Jeroen Ludikhuize, et al.2012). Critical condition can be prevented by recognizing and responding to early indications of clinical and physiological deterioration ( kyriacosu, jelsma,&jordan (2011). According to NPSA (2007) delay in responding to deteriorating vital signs have been defined as an complication resulting in prolonged length of stay, disability or death, not attributed to the patient's underlying illness procedure along but by their health-care management ( Baba-Akbari Sari et al. 2006; Helling, Martin, Martin, & Mitchell, 2014). A number of studies demonstrate that changes or alterations in a patient’s
This however is not always the case as many studies have failed to validate these systems, some revealing poor sensitivity, poor positive predictive value and low reproducibility (Gao et al 2007; Smith et al 2008; Subbe et al 2007; Jansen et al 2010).
Discussion: The percent of errors is 59.62%. Several errors could have happened during the experiment. Weak techniques may occur.
Accuracy: This paper demonstrates much accuracy, this is proven through the subtitles, statistics and in text citations for
Bruce Cherne,” Ford of Canada plant — 150 Model Ts were produced daily in company’s
The costs of car ownership concern motorists greatly, so it isn't difficult to find information.
You can use the set of six questions, below, to investigate this. Before describing the false
· When I have collected my results I will place them in a table like
Before learning the methods from the computer tutorial, I was confused about certain test. B...
.... Without knowledge of the reliability and validity of these two instruments we are unable to know if the instruments are consistent or if they measure what they intend to measure.
There is also the potential of human error within this experiment for example finding the meniscus is important to get an accurate amount using the graduated pipettes and burettes. There is a possibility that at one point in the experiment a chemical was measured inaccurately affecting the results. To resolve this, the experiment should have been repeated three times.
Possible sources of error in this experiment include the inaccuracy of measurements, as correct measurements are vital for the experiment.
There is a very small risk that some of the data I collected could be
ton mileage over the past 30 years. This is mostly due to the increase in truck