Statistical Hypothesis Testing and Key Performance Indicators
Executive summary
The following report aims to analyse and interpret the data set of 200 records regarding the CCResort. The given information includes booking identification number, income, number of people per booking, length of stay, age and overall expenditure.
From the booking ID it can be assumed that the selection of data is random, however as it is only partial information and not the population, the period of time in which the data is selected from would affect the end results of analysis.
The report is divided into two sections outlining the statistical analysis of data and hypothesis testing to observe if CCResort have met their 2 major key performance indicators (KPIs)
1 More than 40% of their customers stay for a full week (i.e. seven nights);
2 The average customer spends more than $255 per day in excess of accommodation costs.
Figures at a glance
This section of the report aims to give users a better understanding of the data through statistical data analysis of investigation categories including family income, expenditure habits, age distribution, the number of people per booking and their length of stay. These analysis are meaningful in giving users a better understanding of the customer base in relation to the key performance indicators.
1. Family income distribution
From the data collected, 62 families (31% of the sample) earn an income of more than $100,000 while 69% of the sample (138 bookings) had income less than $100,000. From the group that had an income of less than $100,000, the average number of people per booking is 3.2581, the average age of the group is 40.9032, the average length of stay is 2.5806 and the average expenditure per day is calculated to be $208.9798. From the group with income more than $100,000, the average number of people per booking is 3.6232, the length of stay is 5.7754, the average age is 48.0217 and the average expenditure is $248.3643 per day.
2.
The following report aims to analyse and interpret the data set of 200 records regarding the CCResort. The given information includes booking identification number, income, number of people per booking, length of stay, age and overall expenditure.
From the booking ID it can be assumed that the selection of data is random, however as it is only partial information and not the population, the period of time in which the data is selected from would affect the end results of analysis.
The report is divided into two sections outlining the statistical analysis of data and hypothesis testing to observe if CCResort have met their 2 major key performance indicators (KPIs)
1 More than 40% of their customers stay for a full week (i.e. seven nights);
2 The average customer spends more than $255 per day in excess of accommodation costs.
Figures at a glance
This section of the report aims to give users a better understanding of the data through statistical data analysis of investigation categories including family income, expenditure habits, age distribution, the number of people per booking and their length of stay. These analysis are meaningful in giving users a better understanding of the customer base in relation to the key performance indicators.
1. Family income distribution
From the data collected, 62 families (31% of the sample) earn an income of more than $100,000 while 69% of the sample (138 bookings) had income less than $100,000. From the group that had an income of less than $100,000, the average number of people per booking is 3.2581, the average age of the group is 40.9032, the average length of stay is 2.5806 and the average expenditure per day is calculated to be $208.9798. From the group with income more than $100,000, the average number of people per booking is 3.6232, the length of stay is 5.7754, the average age is 48.0217 and the average expenditure is $248.3643 per day.
2.