1305AFE Business Data Analysis

Question 1.

The following data are final marks for a Strategic Management Accounting course at a University.

30 74 41 65 51 54 36 56 68 57
70 64 76 67 83 61 81 77 60 38
84 68 72 94 71 86 71 75 91 55
90 82 83 54 79 62 68 58 41 49

a. Construct a frequency distribution and a relative frequency distribution for the data.
b. Construct a cumulative frequency distribution and a cumulative relative frequency distribution for the data.
c. Plot a relative frequency histogram for the data
d. Construct an ogive for the data
e. What proportion of the marks is less than or equal to 60?
f. What proportion of the marks is more than 70?

Use following class intervals to answer the above questions
Classes Frequency Relative
Frequency
Cumulative
Frequency
Cumulative
Relative
Frequency
Up to 40
Up to 50
Up to 60
Up to 70
Up to 80
Up to 90
Up to 100

Question 2

According to the Housing Mobility section of the General Social Survey, Victoria, 2006 (ABS, Catalogue Number: 4159.2.55.001), about 1494 thousand people aged 18 years or over moved in the last five years. Of these people, 758.4 thousand moved for housing reasons, 170.2 thousand moved for employment reasons, 398.6 thousand moved for family reasons and 167.2 thousand moved for other reasons.

a. Construct a pie chart.
b. Interpret your pie chart.

Question 3.

Assume you are a Data Analyst in an international economic consultancy firm. Your team leader has given you a research task to investigate the empirical relationship between China’s export volumes and per capita GDP (Gross Domestic Product).

Relevant Variables: China’s Export volume index and China’s GDP per capita (constant 2010 US$). (Annual time series data (for the period 1980 – 2018) from the World Bank - World development indicators database)

The data are stored in the file named “ASSIGNMENTDATA.XLSX” in the course website. Using EXCEL, answer below questions: 1. Using an appropriate graphical descriptive measure (relevant for time series data) describe the two variables
2. Use an appropriate plot to investigate the relationship between Export volume index and GDP per capita. Assume Export volume index as an independent variable. Interpret the plot.

3. Prepare a numerical summary report about the data on the two variables by including the summary measures, mean, median, range, variance, standard deviation, coefficient of variation, smallest and largest values, and the three quartiles, for each variable.

4. Calculate the coefficient of correlation (r) between Export volume index and GDP per capita. Then, interpret it.

5. Estimate a simple linear regression model and present the estimated linear equation. Then, interpret the coefficient estimates of the linear model.

6. Determine the coefficient of determination R2 and interpret it.

7. Test whether GDP per capita positively and significantly increases with export volume index at the 5% significance level.

8. What is the value of the standard error of the estimate (se). Then, comment on the fitness of the linear regression model?