Assignment - Quantitative Analysis - usability engineering

Introduction

We don't normally think of footwear as having user interfaces, and particularly, not audio interfaces. The data from this assignment is from an experiment with changing the audio interface of footwear and observing changes in user behaviour.

In this assignment you will analyse a dataset from a footwear user study. Participant gender, weight, height, and shoe size were collected. Participants experienced high frequency, low frequency and control audio feedback from walking while wearing the prototype shoes. For each of these states the researchers captured participant perceptions of their bodyweight, changes in their gait, and their mood, using the commonly used model of emotions consisting of the three dimensions: valence (positive/negative), arousal (calm/excited) and dominance (in control/overwhelmed).

Data Analysis

Your task is to analyse the quantitative data provided and write a report with your findings. You may use any tools you like for the analysis: Excel, SPSS, R, scripting languages, web-based tools such as the on-line Adjusted Wald calculator, etc.

Requirements for Data Analysis

The data has already been cleaned and encoded (although you may find some issues or wish to encode things, or re-organise the data for analysis, in which case you should document what you have chosen to do). For your research you will need to:

1. Make decisions regarding missing or mismatched data, if relevant;

2. Calculate descriptive statistics on at least 5 data fields or records;

3. Quantitatively analyse and calculate confidence intervals to compare galvanic skin response for the three different frequencies (control, low and high). Can you conclude anything from your analysis?

4. Quantitatively analyse and calculate confidence intervals for the proportion of participants who had a positive emotional valence for the three frequencies. (You will need to determine the proportion of responses that were positive, i.e. greater than five on the nine-point scale).

5. Quantitatively analyse the data to answer (at least) 3 other research questions that you want to answer from the data (for example, does perceived speed change with different audio frequencies?).

6. For maximum marks, at least one of the 3 other research questions that you choose should involve using data involving at least 3 variables.

Data Variables

The provided spreadsheet contains the following variables for each participant:

Requirements for your Report

You will need to:

1. describe what you did to clean and encode the data (if anything)

2. state your decisions regarding missing data or mismatched data

3. state your decisions regarding the choice of statistical analysis techniques and parameters (eg. method of calculating confidence intervals, confidence level)

4. report descriptive statistics about the data

5. report on the analysis of your questions

6. include appropriate graphs in your report

7. summarise the results

8. clearly state any limitations relating to the results

9. clearly separate observations from conclusions

10. critically evaluate the experiment.

Report Presentation

To achieve maximum marks your work must fulfil these criteria:
- Have good use of layout and space.
- Be a professional report using appropriate language.
- Have sensible colours, fonts, and sizes.
- Be a maximum of FOUR pages long (excluding graphs and appendices). There will be a penalty for excessively long reports.

You may choose an academic paper format (eg. IEEE} or an report layout.