Data analysis, findings and managerial implications The LRT company have recently carried out a customer survey looking at opinions of the system amongst current users. Results were obtained from a sample of 200 adult travellers whilst they were on the system across a range of days (weekday or weekend day) and the following data collected from each: The respondent ID number, recorded as 1 to 200 inclusive; DAY of the week (0=Monday to Friday, 1=Saturday or Sunday) GENDER of the respondent (1=female, 2=male) TIME of day (1=morning: 6am-12noon, 2=afternoon: 12noon-4:30pm, 3=evening: 4:30pm-9pm, 4=late evening: after 9pm) Approximate TRAVEL time spent on the system (in minutes) TYPE of ticket used (1=single or return day ticket, 2=weekly pass, 3=monthly pass, 4=annual pass, 5=free pass for retired person) NUMBER of people travelling together (including the respondent) Rating for SAFETY on the system (1=not at all safe, 10=very safe) Rating for VALUE for money of the system (1=not at all good value, 10=very good value) Rating for CLEANLINESS of the system (1=very dirty, 10=very clean) Rating for RELIABILITY of the system (1=not at all reliable, 10=very reliable) OVERALL opinion of the system (1=very poor, 10=very good) The data collected in this study can be found in the Excel file BM0421_SEM1_2014_15.xls and the SPSS file BM0421_SEM1_2014_15.sav, both of which are available from the BM0421 module site on the e-learning portal (Blackboard). The capitalised words in bold above give the related column headings in the data. Note: The rating variables (those scored 1-10) should be treated as quantitative data in the analysis. Analysis required: In this section of the assignment, marks will be awarded for a justification of the displays, measures and tests undertaken, alongside their full interpretation. You should show the main results using Excel/SPSS tables and graphs, but these must be relevant and fully explained. You must include an explanation with your tables and graphs. Do not attempt Multiple Regression. It is recommended that you set out your answers as we have done in the workshops. Any very large tables or graphs should be placed in the appendices of your report. Where hypothesis tests are undertaken, you should state the significance level you have used. It is important that for each section, you should provide for your client a brief summary of the managerial implications of the results (this is particularly important when a null hypothesis has been rejected). You are required to carry out the following analysis: (i) Give a description of the following variables using appropriate graphical displays and summary statistics: gender; time; travel; type; number. Explain what these show about the typical travellers on the system. (ii) How safe do travellers feel? Use summary statistics and graphs to assess this, and also test whether the perception of safety on the system varies by gender or by the time of day when travel takes place. (iii) Investigate whether there are any links between day of the week and time, travel time and number of people traveling together. (iv) Provide a graph and summary statistics for the overall satisfaction. Does the level of overall satisfaction vary according to the type of ticket or time of day? (v) Investigate whether there are any associations between the overall satisfaction and the four rating scores for safety, value, cleanliness and reliability. Using the most strongly associated rating score, develop and interpret a simple regression model to predict overall satisfaction. Consider the following two cases: • one who gives scores of 4, 5, 7 and 10 for safety, value, cleanliness and reliability respectively. • one who gives scores of 1,2,3 and 1 for safety, value, cleanliness and reliability respectively. Use your regression model to predict their likely overall satisfaction and comment critically on the predictions made. This has to be done using the SPSS software.