A ski company in Vail owns two ski shops, one on the west side and one on the east side of Vail. Ski hat sales data (in dollars) for a random sample of 5 Saturdays during the 2004 season showed the following results. Is there a significant difference in sales dollars of hats between the west side and east side stores at the 10 percent level of significance

If t(critical) < - 1.86 and t(critical) > + 1.86 we will have to reject the null.

Explanation:

What we actually want to know is the difference in the sales between the east and the west sides.

From the question, we are to work with a 10 percent level of significance that is 0.1 level of significance. Where the percent level of significance is represented by "h".

The Hypothesis for this is given in the question below;

Hj: μd = 0.

Hi: μd ≠ 0.

Or

Hj : μ(east) = μ(west).

Hi : μ(east) ≠ μ(west).

The value for t(critical) =+/- t(c/2) {df = n1 + n2 - 2 }.

[ Note that c/2) is a subscript of t and c = .1].

t(critical) = +/- t(0.O5) [ df = 5 + 5 - 2].

t(critical) = + 1.86 or - 1.86

being born in poverty would limit the people's chances, opportunities and benefits.

this happen because of several things, such as:

- poor people tend to gain less access to good education and nutrition. this mean that their chance to obtain high paying jobs would also be limited.

- poor people tend to socialize with other poor people while the rich tend to socialize with other rich people. this means that simply throguh their social circle, rich people would have more business opportunities compared to the poor people.

- rich people tend to have more capital in their disposal. this would benefit them in business since it is far easier for them to fund their business operation compared to poor people.

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explanation:

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