An accountant for a large department store has the business objective of developing a model to predict the amount of time it takes to process invoices using the number of invoices processed. Data are collected from the past 32 working days, the number of invoices processed and completion time (in hours) are stored, and statistical analysis showed that the p-value of the test statistics was 0.46. What will be your null and alternative hypotheses

Null hypothesis: There is no relationship between the amount of time it takes to process invoices and the number of invoices processed.

Alternate hypothesis: There is a relationship between the amount of time it takes to process invoices and the number of invoices processed.  

Step-by-step explanation:

In statistics, the null hypothesis is used to state there is no relationship between two variables of interest. The implication of the null hypothesis in this question is that the amount of time it takes to process invoices cannot be predicted from the number of invoices processed.

In statistics, the alternate hypothesis is used to state there is a relationship between two variables of interest. Alternate hypothesis is the hypothesis that is accepted when the null hypothesis is rejected. The implication of the alternate hypothesis in this question is that the amount of time it takes to process invoices can be predicted from the number of invoices processed.

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