Answer:
Step-by-step explanation:
We would set up the hypothesis test. This is a test of a single population mean since we are dealing with mean
For the null hypothesis,
H0: µ = 5000
For the alternative hypothesis,
H1: µ > 5000
Since the population standard deviation is given, z score would be determined from the normal distribution table. The formula is
z = (x - µ)/(σ/√n)
Where
x = sample mean
µ = population mean
σ = population standard deviation
n = number of samples
From the information given,
µ = 5000
x = 5430
σ = 600
n = 40
z = (5430 - 5000)/(600/√40) = 4.53
Looking at the normal distribution table, the probability corresponding to the z score is < 0.0001
Since alpha, 0.05 > than the p value, then we would reject the null hypothesis. Therefore, at a 5% level of significance, it can be concluded that they walked more than the mean number of 5000 steps per day.
Since the margin of error is 0.11, it can't be concluded that they walked more than the mean number of 5000 steps per day.
Given that it was found that a random sample of 40 walkers took an average of 5430 steps per day, and the population standard deviation is 600 steps, to determine if at = 0.05 can it be concluded that they walked more than the mean number of 5000 steps per day the following calculation must be made:
Therefore, since the margin of error is 0.11, it can't be concluded that they walked more than the mean number of 5000 steps per day.
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