Answer:
Step-by-step explanation:
Hello!
So you have a new type of shoe that lasts presumably longer than the ones that are on the market. So your study variable is:
X: "Lifetime of one shoe pair of the new model"
Applying CLT:
X[bar]≈N(μ;σ²/n)
Known values:
n= 30 shoe pairs
x[bar]: 17 months
S= 5.5 months
Since you have to prove whether the new shoes last more or less than the old ones your statistical hypothesis are:
H₀:μ=15
H₁:μ≠15
The significance level for the test is given: α: 0.05
Your critical region will be two-tailed:
So you'll reject the null Hypothesis if your calculated value is ≤-1.96 or if it is ≥1.96
Now you calculate your observed Z-value
Z=<u>x[bar]-μ</u> ⇒ Z=<u> 17-15 </u> = 1.99
σ/√n 5.5/√30
Since this value is greater than the right critical value, i.e. Zobs(1.99)>1.96 you reject the null Hypothesis. So the average durability of the new shoe model is different than 15 months.
I hope you have a SUPER day!
Answer:
60 x 90 = 5,400 cm^3 (cubed)
Step-by-step explanation:
Multiply them all together like, 90 x 20 x 30
Answer:
(5a+4c)(2a-b)
Explanation:
Given the expression:
First, group the expression into two:
• In the first group, 5a is a common factor.
,
• In the second group, 4c is a common factor.
Factor these out by dividing each term by the GCF of each group.
Since the terms inside the brackets are the same, combine:
CHECK
To check if your result is correct in cases like these, expand as follows:
Our result is the same as the original question, hence, the work is correct.
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