Monash College Unit Guide

DATA ANALYSIS (MCD1110)

Purpose

The intention of this unit is to promote students’ awareness of the importance of mathematics/statistics in everyday life and to build up confidence in making effective use of mathematical/statistical ideas, techniques and processes. This unit aims to provide students with the knowledge and skills to make effective use of methods of analysing quantitative data by the use of graphical and numerical method, interpretation of results and making decision in both business and everyday life.

Prerequisites

MCD1550 Introductory Mathematics for Business

Learning outcomes

On completion of this unit, students should be able to:

1. Arrange data into pictorial and tabular formats for presentation and interpretation purposes.
2. Calculate, compare and interpret the three measures of central tendency - mean, median and mode - for both ungrouped and grouped data.
3. Calculate, compare and interpret range, quartile deviation, standard deviation and co-efficient of variation - for both ungrouped and grouped data.
4. Understand the elementary counting techniques, axioms, interpretation and properties of probability, conditional probability and independence, apply probability tree in probability computation, draw Venn diagrams.
5. Draw XY-scatter plot, assess the strength of linear relationship visually, calculate and interpret Pearson product-moment correlation coefficient.
6. Understand the meaning of the least square regression line, calculate the least squares regression line equation, interpret the slope and intercept, use the least square regression line for estimation, assess validity of estimates.
7. Goodness of fit, computation and interpretation of coefficient of determination, draw the least squares regression line into XY-scatter plot.
8. Perform other forms of nonlinear regression and transformations into linear form by one of the axes scales using a square, log or reciprocal transformation.
9. Apply basic residual analysis with residual plots such as: residuals on the vertical axis versus on the horizontal axis, residuals on the vertical axis versus on the horizontal axis, on the vertical axis versus on the horizontal axis.
10. Recognise the four components of time series such as trend, seasonal, cyclical and random by a visual inspection of time series plot. Compute and apply seasonal indices, perform seasonal adjustments. Apply smoothing with moving averages with or without centring. Modelling the linear trend with linear regression.

Assessment

Tests: 40%

Assessment task 1 (class or on-line test(s)): 20%

Assessment task 2 (one of the following - class or on-line test(s), extended task, research, negotiated assignment, student design): 20 %

Test consists of the combination of multiple choice, short answer and analytical questions.

Examination: 60% closed book exam in duration of 3 hours plus 10 minutes reading time.

Exam consists of the combination of multiple choice, short answer and analytical questions with percentage component 30 + 50 + 20.

A scientific or graphics calculator is allowed for all assessments.

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