Answer:
Step-by-step explanation:
a) Sample statistics are used to estimate population value. Since 48% is a sample proportion, therefore, it is a sample statistic.
b) For 95% confidence level, z* = 1.96.
\hat{p}\pm z^* \sqrt{\frac{\hat{p}(1-\hat{p})}{n}}= 0.61\pm 0.61\sqrt{\frac{0.61(1-0.61)}{1578}}=0.61\pm 0.024 \ or (0.586, 0.634).
We are 95% confident that the true proportion of US residents who think marijuana should be made legal lies between 58.6% and 63.4%.
c)
\\np=1578(0.61)=962.58
\\n(1-p)=1578(1-0.61)=615.42
Since both np and n(1-p), are at least 10, the normal model is a good approximation for these data.
d) As the lower limit of confidence interval is less than 0.5, less than 50% population is also a plausible value of true proportion. This means the statement "Majority of Americans think marijuana should be legalized" is not justified.
12x50=600 so 60 left
15x50=750 so 60 left
so the administration fee is 60
Answer:
amount of pepper required= 7.5 tsp
amount of garlic powder required = 30 tsp
Step-by-step explanation:
Given,
amount of salt used for small batch of the recipe = 2 tsp
amount of pepper used for small batch of the recipe = 1 tsp
amount of garlic powder used for small batch of the recipe = 4 tsp
amount of salt used for the larger batch = 15 tsp
= 2 x 7.5 tsp
= amount of salt used for small batch the recipe x 7.5
So,
the amount of pepper needed for the larger batch= 7.5 x amount of pepper used for the small batch of recipe
= 7.5 x 1 tsp
= 7.5 tsp
the amount of garlic powder needed for the larger batch= 7.5 x amount of garlic powder used for the small batch of recipe
= 7.5 x 4 tsp
= 30 tsp
Square.
A square is a rectangle, so rectangle.
A rectangle is a parallelogram, so parallelogram.
Equilateral.
Also Rhombus.
(I think there may be others but these are the few I know)
Answer:
a. z = 2.00
Step-by-step explanation:
Hello!
The study variable is "Points per game of a high school team"
The hypothesis is that the average score per game is greater than before, so the parameter to test is the population mean (μ)
The hypothesis is:
H₀: μ ≤ 99
H₁: μ > 99
α: 0.01
There is no information about the variable distribution, I'll apply the Central Limit Theorem and approximate the sample mean (X[bar]) to normal since whether you use a Z or t-test, you need your variable to be at least approximately normal. Considering the sample size (n=36) I'd rather use a Z-test than a t-test.
The statistic value under the null hypothesis is:
Z= X[bar] - μ = 101 - 99 = 2
σ/√n 6/√36
I don't have σ, but since this is an approximation I can use the value of S instead.
I hope it helps!
