Answer:
Depends
Step-by-step explanation:
If n is 1n then he have 20 dollars left but if we don't know about the value of n the it is still 20
Answer:
I don't know but if you want to me follow please follow me
Answer:
z (min) = 705
x₁ = 10
x₂ = 9
Step-by-step explanation:
Let´s call x₁ quantity of food I ( in ou ) and x₂ quantity of food II ( in ou)
units of vit. C units of vit.E Cholesterol by ou
x₁ 32 9 48
x₂ 16 18 25
Objective function z
z = 48*x₁ + 25*x₂ To minimize
Subject to:
1.-Total units of vit. C at least 464
32*x₁ + 16*x₂ ≥ 464
2.- Total units of vit. E at least 252
9*x₁ + 18*x₂ ≥ 252
3.- Quantity of ou per day
x₁ + x₂ ≤ 35
General constraints x₁ ≥ 0 x₂ ≥ 0
Using the on-line simplex method solver (AtoZmaths) and after three iterations the solution is:
z (min) = 705
x₁ = 10
x₂ = 9
Answer:
C) The Spearman correlation results should be reported because at least one of the variables does not meet the distribution assumption required to use Pearson correlation.
Explanation:
The following multiple choice responses are provided to complete the question:
A) The Pearson correlation results should be reported because it shows a stronger correlation with a smaller p-value (more significant).
B) The Pearson correlation results should be reported because the two variables are normally distributed.
C) The Spearman correlation results should be reported because at least one of the variables does not meet the distribution assumption required to use Pearson correlation.
D) The Spearman correlation results should be reported because the p-value is closer to 0.0556.
Further Explanation:
A count variable is discrete because it consists of non-negative integers. The number of polyps variable is therefore a count variable and will most likely not be normally distributed. Normality of variables is one of the assumptions required to use Pearson correlation, however, Spearman's correlation does not rest upon an assumption of normality. Therefore, the Spearman correlation would be more appropriate to report because at least one of the variables does not meet the distribution assumption required to use Pearson correlation.
Answer: 9.8 inches
Step-by-step explanation:
Since x = 2 inches
Rainfall in April = x inches = 2 inches
Rainfall in May = x + 1.3 = 2 + 1.3 = 3.3 inches
Rainfall in June = 2x + 0.5 = 2(2) + 0.5 = 4.5
Total rainfall = 2 + 3.3 + 4.5 = 9.8 inches
