Testing a claim about a population mean: t-Test
You work for a steel company that produces "lag bolts". One product is a 10-inch lag bolt. A recent re-design of a machine involved in the production of these bolts has the company wondering whether the production still produces 10-inch lag bolts. You have gathered a random sample of bolts that have been produced with this new production process. Conduct an appropriate test, at a 5% significance level (tα/2=t0.025≈2.1314)(tα/2=t0.025≈2.1314), to determine if the overall mean for this process is 10 inches.
Data (lag bolt lengths, measured in inches):
9.97 | 9.93 | 10.02 | 9.97 | 10.06 | 9.95 | 10.04 | 9.93 |
10.00 | 10.02 | 10.10 | 10.02 | 9.98 | 9.96 | 10.01 | 9.98 |
Sample Statistics
n=16
¯x=9.99625
s=0.04674
Carry out the procedure ("crunch the numbers"):
null hypothesis: HO: μ | = | 10 | |
Alternate Hypothesis: Ha: μ | ≠ | 10 |
a)
from excel:
sample mean =average(Array) =9.99625
b)
sample size n= | 16 | |
std deviation s= | 0.0467 | |
std error ='sx=s/√n=0.04674/√16= | 0.01169 |
c)
test statistic t ='(x̄-μ)/sx=(9.99625-10)/0.012= | -0.3209 |
d)
p value = | 0.7527 | from excel: tdist(0.321,15,2) |
since p value is greater than level of significance, we fail to reject null hypothesis |
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