In terms of statistics please answer the following:

A company ran a survey, results of the survey show that, on average, staff who completed the survey spend 2.3 days a week working from home.

1) There is no way for John to know this, but the actual average number of days staff across the organisation spend working from home is 2.6. What are two possible explanations for the differences between these numbers?

John calculates that the standard deviation of the number of days working from home is 0.75 days. When he carried out the survey last year, he obtained the same mean of 2.3 days, but a standard deviation of 0.2 days.

2) Explain what the difference in standard deviations means in terms of staff working practices?

John developed a 95% confidence interval of the number of days staff work from home, getting the result 2.2 days to 2.4 days.

3) What does this result mean

The company also has an office in London. The London staff spend 2.8 days a week working from home. John wants to carry out a test to see if there is a statistically meaningful difference between the number found by his survey and the London figure.

4) What is the null hypothesis?

5) What is the alternate hypothesis?

6) Is this a one tailed test or two tailed test? Why?

7) What Type 1 error could arise from this test?