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1 answer:
Answer (numbers needed in boxes, going from top to bottom):
1
-1
-3
3
Step-by-step explanation:
f(x) is another way of saying y. So, the table is asking, "when substituting these x values for the x's in the function, what does y equal?" So, to answer the question, substitute each x value into the equation and solve.
1) Start with the x value of 1. Substitute 1 for x in y = 2x - 1 and solve:
So, when x equals 1, y equals 1. Therefore, the first box on the top must be filled out with the number 1.
2) Do the same with the rest of the x values. Here are the steps to solve each one, going in order from the top towards the bottom:
x = 0
x = -1
x = 2
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Answer:
3
Step-by-step explanation:
Drink mix ratio:
Lemonade : Orange : Cranberry
6 : 3 : C
Fraction of Cranberry juice =
Sum of the ratio = 6 + 3 + C = 9 + C
Fraction of Cranberry;
=
3(9 + C) = 12C
27 + 3C = 12C
27 = 12C - 3C
9C = 27
C = 3
The missing number will be 3
Answer:
0.8926 = 89.26% probability that the mean weight of the sample of horses would differ from the population mean by less than 15lbs if 31 horses are sampled at random from the stable
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal probability distribution
Problems of normally distributed samples are solved using the z-score formula.
In a set with mean and standard deviation
, the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
In this problem, we have that:
What is the probability that the mean weight of the sample of horses would differ from the population mean by less than 15lbs if 31 horses are sampled at random from the stable?
pvalue of Z when X = 975 + 15 = 990 subtracted by the pvalue of Z when X = 975 - 15 = 960. So
X = 990
By the Central Limit Theorem
has a pvalue of 0.9463
X = 960
has a pvalue of 0.0537
0.9463 - 0.0537 = 0.8926
0.8926 = 89.26% probability that the mean weight of the sample of horses would differ from the population mean by less than 15lbs if 31 horses are sampled at random from the stable