Answer:
No. The data in this study were not based on a random method. This is a key requirement for an inference to be made from the two-sample t-test.
Step-by-step explanation:
1. Hayden can use the two-sample t-test (also known as the independent samples t-test)to find out if there was a difference in the time spent in the checkout time between two grocery stores and to conclude whether the difference in the average checkout time between the two stores is really significant or if the difference is due to a random chance. There are three conditions to be met when using the two-sample t-test.
2. The first condition is that the sampling method must be random. This requirement was not met in this study. Each customer from each store should have an equal chance of being selected for the study. This was not achieved.
3. The distributions of the sample data are approximately normal. This is achieved with a large sample size of 30 customers selected for each study.
4. The last but not the least condition is the independence of the sample data. Sample data here is independent for both samples.
Answer:
Average: 3250
Step-by-step explanation:
Answer:
a) 
b) 334,858 bacteria
c) 4.67 hours
d) 2 hours
Step-by-step explanation:
a) Initial number of bacteria is the coefficient, that is, 250. And the growth rate is the coefficient besides “t”: 0.15. It’s rate of growth because of its positive sign; when it’s negative, it’s taken as rate of decay.
Another way to see that is the following:
Initial number of bacteria is N(0), which implies 
. And 
. The process is:
b) After 2 days means 
. So, we just replace and operate:
c) 
d) 
Answer:
1 4/5
Step-by-step explanation:
