One Sample Hypothesis Testing
I am working on a problem in Excel but I am having trouble with my T- Distribution. I am using the TDIST function but have been unsucessful in my calculations.

Here is the case scenario:

One hundred customers at the Mall of Elbonia (MoE) were given a brief interview as they concluded their shopping trips. Examine the resulting data in the Mall of Elbonia Interview Results file. For each customer (by row), the spreadsheet contains data on:

The customer's gender.
How long the customer spent in the mall.
How much he or she spent on food and clothing purchases.
The customer's rating of the mall's friendliness and attractiveness.

A.) MoE's concessions manager believes the average amount that mall customers spend on food during a visit has increased over the historical average of $18.75, due to the opening of some new upscale restaurants in the mall. Use the data in the file to test his hypothesis. Answers

• What is the null hypothesis?
The null hypothesis tested is
H0: The average amount that mall customers spend on food during a visit ≤ $18.75 (µ ≤ 18.75) • Would you reject it at alpha = .05?
The alternative hypothesis is
H1: The average amount that mall customers spend on food during a visit > $18.75 (µ > 18.75) Significance level = 0.05
Test Statistic used is , where = 19.932478964, n = 100, s = 4.254541656 (Please see the excel spreadsheet) Therefore, = 2.779333379
Decision rule: Reject the null hypothesis, if the calculated value of test statistic is greater than the critical value of t with 99 d.f. at the significance level 0.05. Upper critical value = 1.660391157

Conclusion: Reject the null hypothesis, since the calculated value of test statistic is greater than the critical value. The sample provides enough evidence to conclude that the average amount that mall customers spend on food during a visit has increased over the historical average of $18.75. Details

...OneSampleHypothesisTesting
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...HypothesisTesting I
Pat Obi
What is a “Hypothesis?”
A statement or claim about the value of a
population parameter: μ, σ2, p
Pat Obi, Purdue University Calumet
2
Decision Rule
1.
x 0
Z
s
n
Compare calculated Z value to Z value from
Table (critical Z value)
Reject H0 if calculated Z value lies in the
rejection/significance region (i.e. region)
ALTERNATIVELY:
2.
Compare p-value to
Reject H0 if p-value <
Pat Obi, Purdue...

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