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AFE135 Business Data Analysis

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  • Course Code: AFE135
  • University: Griffith University
  • Country: Australia

Question:

Briefly explain (using no more than 250 words in total for this Question 1)
(a) What type of survey method the researcher could use and why
(b) What sampling method could the researcher use to select his/her sample and why
(c) What are the two main variables the researcher should consider collecting data for the purpose of the above analysis and why? Identify the data type(s) for the variables.
(d) What kind of issues the researcher may face in this data collection

Suppose a researcher has collected data form a sample of 150 individuals using the sampling method you have proposed in (b). For each individual, the weekly take-home pay and weekly food expenditure were recorded. The data are stored in file FOODEXP.XLSX which is available in the “Assessment>>Assessment 2 - Assignment - Computer Application Project” in the unit website. Using this data set and EXCEL, answer the questions below.

QUESTION 2 
First, the researcher is interested in presenting the data on weekly take-home pay and food expenditure graphically. For this purpose, the researcher categorised data on take-home pay nd food expenditure into 6 groups and calculated.

Using the data in the above frequency distribution tables and using EXCEL, answer the following questions.
(a) Which graphical technique or chart should be used if the researcher is interested in comparing the number of individuals in each weekly take-home pay category? Explain the reason for the selection of this graphical chart. Construct the chart and describe what you can observe about the number of individuals belong to each take-home pay category
(b) Which graphical technique or chart should be used if the researcher is interested in describing the proportion of the individuals in each food expenditure category Explain the reason for the selection of this graphical chart. Construct the chart and describe what you can observe about the proportion of individuals belong to each food expenditure category.

QUESTION 3
Second, researcher wishes to use graphical descriptive methods to present a summary of the data.
(a) The number of observations (N) is 150 individuals. The researcher suggests using 8 class intervals to construct a histogram for each variable. Explain how the researcher would have decided on the number of class intervals (K) as 8.
(b) The researcher suggests using class intervals as 100-225, 225-350, 350-475, ….., 975-1100 for Weekly take-home pay variable and class intervals 0-50, 50-100, 100- 150, …. , 350-400 for the Food expenditure variable. Explain how the researcher would have decided the width of the above class intervals (or class width).
(c) Draw a histogram for each variable using appropriate BIN values from part (b) and comment on the shape of the two distributions.

QUESTION 4
Third, the researcher wishes to use numerical descriptive measures to summarize the data.
(a) Prepare a numerical summary report for the two variables; weekly take-home pay and food expenditure by including summary measures such as mean, median, range, variance, standard deviation, smallest and largest values and the three quartiles, for each variable.
(b) Compute the correlation coefficient to measure the direction and strength of the linear relationship between the two variables. Interpret this value.

QUESTION 5
Finally, the researcher considers using regression analysis to establish a linear relationship between the two variables food expenditure and weekly take-home pay.
(a) What is the dependent variable and independent variable for this analysis Why
(b) Use an appropriate plot to investigate the relationship between the two variables. On the same plot, fit a linear trend line including the equation and the coefficient of determination R.
(c) Estimate a simple linear regression model and present the estimated linear equation.Display the regression summary table and interpret the intercept and slope coefficient estimates of the linear model.
(d) Find and interpret the value of the coefficient of determination, R-squared (R2 ).
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