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Hypothesis Testing in Business Statistics: An Example from FLC - Prof. Eric L. Huggins, Exams of Business Statistics

An example of hypothesis testing in the context of business statistics using data from flc. The example involves testing the claim that the mean amount of time college students spend on a computer per day is 2 hours, and using statistical evidence to determine if this is also true for flc students. The steps of the hypothesis testing process, including calculating a confidence interval, formal hypothesis testing, and determining the p-value.

Typology: Exams

Pre 2010

Uploaded on 08/05/2009

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BA 253: Business Statistics 10/22/08
Today Friday
Return Exam2 More HT
Hypothesis Testing Start ICE 7
Return/Discuss Exam 2
Return/Discuss Project Proposals
Chapter 9: Hypothesis Testing
Use statistical evidence to answer questions.
Formal methodology.
Never “prove” or “disprove” a claim. Rather, show that statistical evidence either
supports or refutes the claim.
Ex A: A report states that typical college students spend about 2 hours per day working
on a computer. Is this true at FLC?
Claim: μ = 2 hours/day.
Collect data: If
x
= ½ or
x
= 3.5, obviously no.
Survey FLC students and find that
x
= 1.87 and s = 0.76.
Does the data support or refute the claim that the mean is 2 hours???
Confidence Interval Answer
Assume 95% confidence (5% chance of error)
CI = (1.66, 2.08). What does this tell us?
Since μ = 2 is in the interval, the evidence supports the claim. (But does not
“prove” it!)
Final answer: FLC students appear to spend about 2 hours per day on a computer,
same as the national average.
Formal Hypothesis Testing Answer
H0: μ = 2 (null hypothesis)
Ha: μ ≠ 2 (alternative hypothesis)
α = 5% (chance of error = 1 – confidence = 1 – 95%)
Need two things: Critical Value(s) and Test Statistic
Show how zcrit = ± 1.96 with table, accept, reject.
Calculate zstat = = -1.21
Since zstat is in acceptance region, accept H0, the mean appears to be 2 hours.
p-value
Calculate p-value = 22%.
If H0 is really true (μ = 2), then there is a 22% chance that we would see a sample
mean with
x
≤ 1.87 ( or
x
≥ 2.13). A 22% chance is not that unlikely, so accept
H0.
In other words, accept H0 if p-value ≥ α, reject H0 if p-value ≤ α.

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BA 253: Business Statistics 10/22/ Today Friday Return Exam2 More HT Hypothesis Testing Start ICE 7  Return/Discuss Exam 2  Return/Discuss Project Proposals Chapter 9: Hypothesis Testing  Use statistical evidence to answer questions.  Formal methodology.  Never “prove” or “disprove” a claim. Rather, show that statistical evidence either supports or refutes the claim. Ex A: A report states that typical college students spend about 2 hours per day working on a computer. Is this true at FLC?  Claim: μ = 2 hours/day.  Collect data: If x = ½ or x = 3.5, obviously no.  Survey FLC students and find that x = 1.87 and s = 0.76.  Does the data support or refute the claim that the mean is 2 hours??? Confidence Interval Answer  Assume 95% confidence (5% chance of error)  CI = (1.66, 2.08). What does this tell us?  Since μ = 2 is in the interval, the evidence supports the claim. (But does not “prove” it!)  Final answer: FLC students appear to spend about 2 hours per day on a computer, same as the national average. Formal Hypothesis Testing Answer  H 0 : μ = 2 (null hypothesis)  Ha: μ ≠ 2 (alternative hypothesis)  α = 5% (chance of error = 1 – confidence = 1 – 95%)  Need two things: Critical Value(s) and Test Statistic  Show how zcrit = ± 1.96 with table, accept, reject.  Calculate zstat = = -1.  Since zstat is in acceptance region, accept H 0 , the mean appears to be 2 hours. p-value  Calculate p-value = 22%.  If H 0 is really true (μ = 2), then there is a 22% chance that we would see a sample mean with x ≤ 1.87 ( or x ≥ 2.13). A 22% chance is not that unlikely, so accept H 0.  In other words, accept H 0 if p-value ≥ α, reject H 0 if p-value ≤ α.