Application of Number Assignment
Task One: Gather, present and interpret data for a purpose
The purpose of my task is to compare daily website traffic to the daily sales conversion rate over the month of June for a newly established sales campaign. With this information I can identify whether the projected conversion rate percentage has been forecast accurately. This information will also be used as the control sample data to base future sale trends on.
w/c |Visitors / Sales |Mon |Tues |Wed |Thurs |Fri |Sat |Sun |Week Total | |01/06/11 |V |- |- |5 |1 |4 |1 |4 |15 | | |S |- |- |2 |0 |1 |0 |2 |5 | |06/06/11 |V |3 |2 |1 |5 |1 |1 |1 |14 | | |S |2 |1 |0 |2 |0 |0 |0 |5 | |13/06/11 |V |5 |2 |4 |3 |1 |2 |0 |17 | | |S |2 |0 |2 |1 |0 |1 |0 |6 | |20/06/30 |V |3 |3 |7 |6 |4 |4 |0 |27 | | |S |1 |2 |3 |2 |0 |0 |0 |8 | |27/06/11 |V |1 |4 |6 |4 |- |- |- |15 | | |S |0 |2 |3 |0 |- |- |- |5 | | | | | | | |Total visitors |88 | | | | | | | |Total Sales |29 | |
Mean:
The average (mean) number of daily visitor traffic is 3
(total amount of data adds up to 88, then divided this total by the number of data sets, 30. 88 divided by 30, equals 2.93, which I rounded up to 3.)
The average (mean) number of daily sales is 1
(total amount of sales data adds up to 29, then divided this total by the number of data sets, 30. 29 divided by 30, equals 0.96, which I rounded up to 1.)
Median:
The average (median) number of daily visitor traffic is 3
0 |0 |1 |1 |1 |1 |1 |1 |1 |1 |2 |2 |2 |3 |3 |3 |3 |4 |4 |4 |4 |4 |4 |4 |5 |5 |5 |6 |6 |7 | |(Values arranged in ascending order, 3 is the value in the middle of the series)
The average (median) number of daily sales is 1
0 |0 |0 |0 |0 |0 |0 |0 |0 |0 |0 |0 |0 |0 |1 |1 |1 |1 |1 |2 |2 |2 |2 |2 |2 |2 |2 |2 |3 |3 | |(As there is an even number of data (30) there is not one number which falls exactly in the middle, so I take the two middle numbers 0 and 1, add them together, equals 1, which is the divided by two. In this case we get a median of 0.5, which I
The purpose of my task is to compare daily website traffic to the daily sales conversion rate over the month of June for a newly established sales campaign. With this information I can identify whether the projected conversion rate percentage has been forecast accurately. This information will also be used as the control sample data to base future sale trends on.
w/c |Visitors / Sales |Mon |Tues |Wed |Thurs |Fri |Sat |Sun |Week Total | |01/06/11 |V |- |- |5 |1 |4 |1 |4 |15 | | |S |- |- |2 |0 |1 |0 |2 |5 | |06/06/11 |V |3 |2 |1 |5 |1 |1 |1 |14 | | |S |2 |1 |0 |2 |0 |0 |0 |5 | |13/06/11 |V |5 |2 |4 |3 |1 |2 |0 |17 | | |S |2 |0 |2 |1 |0 |1 |0 |6 | |20/06/30 |V |3 |3 |7 |6 |4 |4 |0 |27 | | |S |1 |2 |3 |2 |0 |0 |0 |8 | |27/06/11 |V |1 |4 |6 |4 |- |- |- |15 | | |S |0 |2 |3 |0 |- |- |- |5 | | | | | | | |Total visitors |88 | | | | | | | |Total Sales |29 | |
Mean:
The average (mean) number of daily visitor traffic is 3
(total amount of data adds up to 88, then divided this total by the number of data sets, 30. 88 divided by 30, equals 2.93, which I rounded up to 3.)
The average (mean) number of daily sales is 1
(total amount of sales data adds up to 29, then divided this total by the number of data sets, 30. 29 divided by 30, equals 0.96, which I rounded up to 1.)
Median:
The average (median) number of daily visitor traffic is 3
0 |0 |1 |1 |1 |1 |1 |1 |1 |1 |2 |2 |2 |3 |3 |3 |3 |4 |4 |4 |4 |4 |4 |4 |5 |5 |5 |6 |6 |7 | |(Values arranged in ascending order, 3 is the value in the middle of the series)
The average (median) number of daily sales is 1
0 |0 |0 |0 |0 |0 |0 |0 |0 |0 |0 |0 |0 |0 |1 |1 |1 |1 |1 |2 |2 |2 |2 |2 |2 |2 |2 |2 |3 |3 | |(As there is an even number of data (30) there is not one number which falls exactly in the middle, so I take the two middle numbers 0 and 1, add them together, equals 1, which is the divided by two. In this case we get a median of 0.5, which I