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STA30305: QUANTITATIVE TECHNIQUE

Objective:

Upon successful completion of this assignment, students will be able to:

✓ Use Excel spreadsheet to analyze data.

✓ Plot appropriate charts and diagram using Excel

✓ Interpret computer generated output.

✓ Counting probabilities.

Instructions:

This assignment will be assessed over 70 marks and is worth 35% of the whole module coursework. Work that does not comply with the instructions below will be severely penalized by up to 20% of the total marks.

1. This assignment will be done by group of 4 students.
2. The assignment should be submitted in soft copy.
3. Use the cover page and feedback form uploaded on TIMES.
4. The assignment requires using a set of secondary data. Students are required to use

appropriate statistical techniques to analyze and interpret the findings.

1. The report must consist of the solutions to Part A, B and C Questions
2. Please use Times New Roman with a font size of 12. The line spacing should be 1.5 and every page should be numbered.
1. All answers must be typed. No handwritten answers will be accepted.
2. All table, charts/graphs and output MUST be proper generated by Microsoft Excel.
3. Assignment submitted should be presentable, neat, and organized in Microsoft Words.

10.The assignment should be submitted latest by 12noon on 24TH JUNE 2022 (FRIDAY) at the drop box at TEAMS.

11.The late penalty will take the form of a deduction of 5% of the total marks. While assignments will not be accepted after the 24 hours window and will be recorded as a nonsubmission. A mark of ZERO will be awarded.

CASE STUDY:

A large Toyota car dealership offers purchasers of new Toyota cars the option to buy their used car as part of a trade-in. A new promotion promises to pay high prices for used Toyota cars for purchasers of a new car. The dealer then sells the used cars for a small profit. To ensure a reasonable profit, the dealer needs to be able to predict the price that the dealership will get for the used cars. For that reason, data were collected on all previous sales of used Toyota cars at the

dealership. Detail of data description are given as below:

❖ Toyota car model.

❖ Car registration year.

❖ Sales Price in Euros.

❖ Transmission type of gear box.

❖ Mileage distance used.

❖ Fuel type engine fuel.

A data set on Toyota used cars is provided in the excel file Toyota.xls, which is attached to the

Group Assignment folder in TIMES. A data set of 425 is provided, and you must choose any 100

data at random from the given data set.

Answer all questions in Parts A, B, and C using the selected 100 data.

Part A: (35 marks)

1. You need to attach 100 data used in your study (appendix). [2 marks]
2. Identify whether the analysis you were considering in this survey is a population or sample.

Provide a relevant reason. [2 marks]

1. Identify the type of each variable and indicate whether it is qualitative or quantitative and

state the level of measurement. [6 marks]

1. Draw an appropriate graph for car registration year and explain the graph briefly. [5 marks]
2. By using Excel, organize the Sales Price of the car into group frequency distribution. [4 marks]
1. By using Excel, construct a descriptive statistics table for Sales Price and Mileage distance used which include the FIRST & THIRD QUARTILES and IQR. [6 marks]
1. Based on the above descriptive table of in Q (6), explain the following analysis for EACH variable. [10 marks]

❖ Measure of location

❖ Measure of dispersion

❖ Shape of distribution

Units must be specified clearly in the report (marks will be deducted otherwise).

Part B: (20 marks)

Carry out the following correlation and regression analysis using the dataset of Sales Price and mileage distance used.

1. Use Excel to generate a scatterplot of Sales Price and Mileage distance used. Add a trend line and display its equation and coefficient of determination to the scatter plot. Briefly explain the graph. [6 marks]
1. Use Excel to generate a summary output for regression analysis. From the output, determine the regression equation. [3 marks]
1. Interpret the results from Q2 above by explaining the following values: [9marks]

❖ the value of y-intercept

❖ the slope

❖ the coefficient of correlation value

❖ the coefficient of determination value

Units must be specified clearly in the report (marks will be deducted otherwise)

1. Would you recommend using the regression equation to predict the Sales Price? Explain your reasons. How reliable is this prediction? [2 marks]

Part C: (15 marks)

1. Develop a contingency table using these variables: Toyota car model and Car registration year which includes the total for each column and row. [5 marks]

[For the following questions, ALL working must be shown clearly and round up your answers to three (3) decimal places.]

1. What is the probability that a randomly selected car model is Aygo or in year 2017? [3 marks]
1. Suppose that the car registered in year 2019, what is the probability that the car model is Corolla? [2 marks]
1. What is the probability that a randomly selected car model is Prius registered in year of 2018? [2 marks]
1. Suppose that 3 cars were selected at random. What is the probability that all three cars were Yaris register in 2017? [3 marks]

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