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Bayesian Confidence Interval for Proportions
The purpose of this tool is to construct a 95% confidence interval in which an average value (such as average daily sales) can be reasonably expected to fall. It also allows you to test if it is reasonable to expect a certain average.
Take the following example.
Suppose you are a new store. In your first day of operations, you have 8 sales. The average is $100.49 and the standard deviation is $10.79. In what range can you expect average daily sales to fall 95% of the time? Also, is it reasonable to expect average daily sales of $100?
The tool calculates that the range of expected values ranges from 91.47 to 109.51. This means that 95% of the time, average daily sales will be between $91.47 and $109.51.
Since the hypothesis mean of 100 falls in the range of expected values, it is reasonable to conclude that average daily sales would be $100.
The purpose of this tool is to help you construct a 95% confidence interval of proportions such as sales rates.
Take the following examples.
A website wants to estimate its sales rate for a new product. In its first week, of the 10 visits to the information page of this product, there were 2 sales. The range of expected average values ranges from 6% to 51.8%
In the year-to-date (the end of the previous month), a commission salesperson has had 50 sales calls, resulting in 8 sales. The range of expected average values ranges from 8.4% to 28.6%.
This tool calculates the odds of surpassing a target percentage based on prior sales history and current sales.
Take the following examples.
A website estimates its sales rate for a new product will be 10% (1 sale per 10 visits). In its first week, of the 10 visits to the information page of this product, there were 2 sales. The sales percentage macro calculates the odds of surpassing the target sales rate of 10% as 0.5 to 1. The corresponding probability is 32.2%. The range of expected average values ranges from 6% to 51.8%
In the year-to-date (the end of the previous month), a commission salesperson has had 40 sales calls, resulting in 6 sales. The target rate is 10%. In the current month, the salesperson has had 10 sales calls, resulting in 2 sales. The sales percentage macro calculates the odds of surpassing the target sales rate of 10% as 0.1 to 1. The corresponding probability is 10%. The range of expected average values ranges from 8.4% to 28.6%.
The purpose of this tool is to help you set realistic sales targets.
This tool calculates the odds of surpassing an average sales amount based on prior sales history and current sales.
Take the following example.
A store is looking for an average sale to exceed $90. In sales from the previous two weeks, the average was $99.28. For the current week, the average is $100.49. The sales amount macro gives the odds of exceeding an average of $90 as 3.6 to 1 with a corresponding probability of 78.3%. The range of expected average values ranges from $96.82 to $104.17.
If this were a new store with no prior data, using just the data from the current week, the odds would be 0.1 to 1 with a corresponding probability of 6.4%. The range of expected average values ranges from $91.47 to $109.52.