Answer : The p-value of 0.0743 is greater than alpha at 0.05; so we fail to reject the null hypothesis and conclude that there is no significant difference in the number of unique users before and after a change in policy.
In this question, the manager wants to know if the number of users has changed.
So, the null and alternate hypotheses are:
Null Hypothesis: 
Alternate Hypothesis : 
Type of test : Two-tailed test
The level of significance is 95%
We can calculate alpha (α) as follows:
The p value = 0.0743.
We use the following rules to arrive at a conclusion when p-values and alpha is given:
If 
, reject the null hypothesis
If 
, we don't reject the null hypothesis.
Since the p-value is greater than alpha, we don't reject the null hypothesis.
Answer:
Product A, then Product C and finally Product B
Explanation:
The unit profit = Selling price per unit - Variable cost per unit - Fixed cost per unit
Unit Profit of product A = $21 - $11 - $5 = $5
Unit Profit of product B = $12 - $7 - $3 = $2
Unit Profit of product C = $32 - $18 - $9 = $5
The profit of each product in 1 machine hour = 1 hour/ Machine hours per unit * Unit Profit
Profit of Product A in 1 hour using machine = 1/0.2 * $5 = $25
Profit of Product B in 1 hour using machine = 1/0.5*$2 = $4
Profit of Product C in 1 hour using machine = 1/0.2* $5 = $25
Product A & Product C have same profit in 1 hour machine, then we have to consider Direct labor hours per unit which product A is 0.4 while product C is 0.7. It means Product C is more costly in direct labour than Product A.
In short, then the ranking of the products from the most profitable to the least profitable use of the constrained resource is Product A, then Product C and finally Product B
Answer: To remove bias when estimating the proportion of working adults living in urban, suburban, and rural areas.
Explanation: In simple words, stratification refers to the process in which different sections of the society are grouped on the basis of one or more general factors.
In the given case, the company wants to estimate the minutes of working adults in the region and the region is grouped into urban, suburban and rural.
Thus, the random selection from different regions is done so that no bias takes place regarding the number of adult working in these three different areas.
