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:
Function 2 has a greater initial valueStep-by-step explanation:An initial value of a function, aka y-intercept, is obtained by using x=0 and evaluating the function at that point. Evaluating the two functions given:Function1: Function2 has value 3 for x=0So, Function 2 has a greater initial valueFunction 2 has a greater initial valueStep-by-step explanation:An initial value of a function, aka y-intercept, is obtained by using x=0 and evaluating the function at that point. Evaluating the two functions given:Function1: Function2 has value 3 for x=0So, Function 2 has a greater initial value
Step-by-step explanation:
The answer to this particular problem is 32.
Answer:
Proved
Step-by-step explanation:
Given
Required
Prove
On the right hand side, we have:
Rewrite:
Apply law of indices
Express 6 as 3.5 + 2.5
Open bracket
Proved