## Monday, July 29, 2019

### Applewood auto group Coursework Example | Topics and Well Written Essays - 1000 words

Applewood auto group - Coursework Example The range for profits was calculated as a difference between the maximum and the minimum profit for each location. The results are presented in the table below. The last row presents the results for all sold vehicles (Black, 2012:52). 2. a. To construct the histogram for the profits, the Data Analysis toolkit is used. The option Ã¢â‚¬Å"HistogramÃ¢â‚¬  permits to create the table and the graph for the distribution of profits (Anderson, Sweeney and Williams, 2014:106-180). b. The results show that the data is normally distributed with the small sqewness. The most frequently obtained profit is between \$ 1,800 and \$ 2,000. The rarest profits are within the range between \$ 294 and \$ 900. The profits of more than \$ 3,100 are also very rare. More than 70 % of profits are within the range of \$ 1,200 and \$ 2,800. 3. a. To build the boxplot for variable age, the option Ã¢â‚¬Å"HistogramÃ¢â‚¬  in the Excel Data Analysis Toolkit can be used (Anderson, Sweeney and Williams, 2014:106-180). The results are given in the table and in the graph below. The boxplot shows that the variable age is normally distributed. The mean and the median are almost equal. The average age of the buyer is 46 years. The most of the buyers are in the age between 33 and 60 years. The youngest buyer has 21 year and the oldest buyer is 73 years old. b. The data on the graph does not support the idea that the older buyers purchase cars on which the higher profits can be earned. It is seen from the scatterplot that buyers purchasing vehicles on which the high profits can be earned are in every age group. The scatterplot does not show the presence of the relationship between the age of the buyer and the earned profit. c. The option Ã¢â‚¬Å"Add Trend LineÃ¢â‚¬  in Excel can be used to get the trend line and the coefficient of determination. The coefficient of determination R2 is equal 0.0684. The correlation coefficient is the square root of the coefficient of determination R = 0.2615. The results