QAB105 Quantitative Analysis for Business

A sociologist theorised that people who watch television frequently are exposed to many commercials, which in turn lead them to buy, resulting in increasing debt. To test this belief, a researcher plans to survey a sample of families across the country.

Part 1

Briefly explain

(a) What type of survey method could the researcher use and why?
(b) What sampling method could the researcher use to select his/her sample and why?
(c) What kind of issues the researcher may face in this data collection?
Suppose the researcher collected data from 400 randomly selected families. For each family, the total debt (in $) and the number of hours the television is turned-on per week (TV hours) were recorded. The data are stored in file Assignment Dataset_TVDEBT.XLS available in the Written Assignment folder. Using this data and EXCEL, answer the questions below.

Part 2

Firstly, the researcher wishes to use the graphical descriptive methods and numerical descriptive measures to present the data for the two variables.
(a) He/she decides to use 10 class intervals, such as 0<X≤6, 6<X≤12, 12<X≤18, .... for the TV Hours variable and class intervals 0<X≤30000, 30000<X≤60000, 60000<X≤90000, .... for the Total Debt variable. Explain how he/she could have decided on the number of classes as 10.
(b) Draw two histograms for the two variables using appropriate BIN values.
(c) Prepare a numerical summary report for the two variables; the total debt and the TV hours by including the summary measures, such as mean, median, variance, standard deviation, smallest and largest values, and the three quartiles, for each variable.
Notes: Use QUARTILE.EXC command to generate the three quartiles
(d) Based on your histograms in part (b) and descriptive summary measures in part (c), comment on the shape of the distribution of the two variables.

Part 3

Secondly, the researcher wishes to investigate the association between the two variables.

(a) Explain what could be the independent variable (X) and the dependent variable (Y).
(b) Using an appropriate plot, investigate the relationship between total debt and TV hours. On the same plot, fit a linear trend line.
(c) Using Excel, compute a numerical measure that measures the direction and strength of the linear relationship between the total debt and TV hours. Interpret this value.
(d) Display the regression summary table. Using the summary results, estimate the Least Squares Regression equation and interpret the intercept and slope coefficient estimates of the estimated linear regression model.
(e) Comment on the fitness of the estimated model.
(f) Using the information in the regression summary output, conduct a hypothesis testing to conclude whether there is a linear relationship between Total debt and TV hours. Use

Part 4

(a) Based on your answers above, write a brief research report on the relationship between total debt and TV hours.