Activity Data Sheet
Activity Data Sheet
The sample of the data collected is suitable quantitative data for the business scenario as it assists in pinpointing the actual period when the café should increase its staff to cater for the increased number of guest needs. Every business especially those in the hospitality industry need to collect data over time such as what has been done by The Littletown café to make predictions on the number of guests to be expected and required number of staff that can serve guests within minimum time possible. Those cafés that experience fluctuation in the number of guests visiting at any particular time of the year should be in a position to increase or decrease the number of employees to cut costs when there are fewer customers. On the other hand, the number of staff should also be increased with increasing number of clients in case the current number of staff cannot manage to serve all the guests within the shortest time possible. Increasing the number of employees during high guest turnover ensures that every guest is served increasing customer satisfaction. This is an indication that the café at this period will increase its profits.
Validity is used to represent the degree to which an instrument is measuring what it is supposed to measure. Some of the factors that might have affected the validity of the data set in our sample include elements that are test-related, reliability, the intervening events, and the criteria to which is used to make comparisons might be well established.
Reliability is the percentage to which the assessment tool used will produce consistent and stable results. Some of the factors that affect the reliability of the data set include firstly, the length of the test. The test data should be long enough to ensure that the results got will be reliable. For example, the data collected should have been more than two months to establish the trend of guests visit the café way before after the memorial day and way after the memorial day. Secondly, reliability is affected by validity. If validity is little among the test scores, the level of reliability of the data set will be low (Cohen & Spenciner, 2010).
A combined line graph was used to represent the data set. The reason for choosing this chart type is because it provides various benefits when compared to other forms of charts that can be used to represent data like pie charts or bar graphs. It is possible to use the longitudinal aptitude of the graph type selected to track the fall or rise of values in the data set. Therefore, it is easy to see trends or changes of the data quickly and easily. Another reason why the chart type was selected was to enable quick comparisons of the data sets to cross points for the three years. This permits for lesser anecdotal connection evidence. Lastly, the dataset can be represented differently in this chart type through the use of different colors, different types of lines can be used like dashed or dotted lines which are not the case in other types of chart types that can be in data representation.
Descriptive statistics
The following steps were followed to obtain descriptive statistics using Excel, which contain the measures of central tendency. The first step was to select the data for the three years that was collected for the two months. Then moving the pointer along the menu bar and selecting data. The next step was to click on data analysis and scrolling down to descriptive statistics. After selection, I clicked okay and selected the range which is the data collected in two months over the three months. I ticked labels by clicking on the box so that the software can exempt the three years which are 2012, 2013, and 2014. Lastly, under output options, I selected new worksheet ply so that the outputs would be displayed in a new worksheet and clicked okay. The results were shown in sheet2.
The table above containing the descriptive statistics results shows that the mean number of guests served in the hotel in 2012, 2013, and 2014 are for the two months is 86, 77, and 92 respectively. The mode of the customers served in 2012, 2013, and 2014 is 107, 94, and 91 respectively. The median for the data set collected for guests served is 91 for 2012, 81 for 2013 and 96 for 2014. The data collected in 2012 for guests served had the largest standard compared to other years meaning that its variability was high. The standard error for the dataset in 2012 is 5.12, 4.31 for 2013 data set, and 4.9 for 2014 data set. Data variability was lowest in 2013 compared to 2012 and 2014.
References
Cohen, L. & Spenciner, L. (2010). Factors That Influence Reliability. Education.com. Retrieved 13 May 2016, from http://www.education.com/reference/article/factors-influence-reliability/
