Programming Assignment 2

CSC 323 - Data Analysis and Statistical Software

Due: 10/28/99

A local company that develops touch screen interfaces for ATM machines has hired you as a software engineer. The team that you have been assigned to is interested in evaluating a newly designed interface that they think is more intuitive than the currently available interface and so should allow users to complete tasks more quickly.

Proposed interfaces will only be considered if they exceed several defined performance standards. One of these standards states that novice users should, on average, complete a standard transaction suite in forty seconds. Your team believes that their proposed interface will exceed this standard and design an experiment involving twenty six novice users to evaluate the interface against this standard.

You have been presented with the data collected for this experiment. Each observation in the file consists of the following values:

• Observer ID; 1-3
• User ID; 4-5
• User Age; 6-7
• Workstation ID; 8-12
• Transaction Time (milli-seconds); 13-17
• Error Count; 18-19

Conduct a thorough analysis of these data. You will need to conduct a test of hypotheses and submit a report summarizing your findings. See additional details below.

1. Write a SAS program to analyze this dataset. Your program should do the following:
1. Read your data from an external file.
2. Execute the PRINT procedure.
3. Use the appropriate SAS procedures to produce the statistics and p-values to test your hypotheses.

Note: For PROC PRINT, be sure to use labels for column headings rather than variable names. Use names for data sets and variables that are meaningful. You should generate an appropriate title for the output of these procedures.

2. Write a short analysis (no more than two pages) of the output of your SAS program. Your analysis should at least address the following:
1. State the primary hypotheses. That is, the NULL and ALTERNATIVE hypotheses for the experiment described above.
2. State and address any other hypotheses needed for your analysis.
3. Discuss the significance of the p-value obtained for the primary hypotheses.
4. Given your findings, briefly explain why you should (or should not) provide a point estimate for the parameter in question. If you argue that a point estimate for the parameter is appropriate you must provide it as well as a 95% confidence interval for the parameter (with an interpretation).