The slope-intercept form:
m - slope
b - y-intercept → (0, b)
The formula of a slope:
We have the points (4, 3) and (0, 1) → b = 1.
Calculate the slope:
Answer:
Find the derivative of the vector function r(t)=ta×(b+tc), where a=⟨2,−3,4⟩, b=⟨−4,5,−1⟩, and c=⟨−2,−1,5⟩.
1 answer:
Answer:
derivative of the vector function given = ( -16-22t, 14-36t, -2-16t )
Step-by-step explanation:
given data:
vector function : r(t) = ta*(b+tc)
a = ( 2,-3.4) . b = (-4,5,-1). c = ( -2,-1,5)
to find the derivative of the vector function we will differentiate with respect to x attached below is the detailed solution
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Answer:
The probability that the mean amount of credit card debt in a sample of 1600 such households will be within $300 of the population mean is roughly 0.907 = 90.7%.
Step-by-step explanation:
To solve this question, we have 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 random variable X, with mean and standard deviation
, a large sample size can be approximated to a normal distribution with mean
and standard deviation
In this problem, we have that:
The probability that the mean amount of credit card debt in a sample of 1600 such households will be within $300 of the population mean is roughly
This probability is the pvalue of Z when X = 1600 + 300 = 1900 subtracted by the pvalue of Z when X = 1600 - 300 = 1300. So
X = 1900
By the Central Limit Theorem
has a pvalue of 0.9535.
X = 1300
has a pvalue of 0.0465.
0.9535 - 0.0465 = 0.907.
The probability that the mean amount of credit card debt in a sample of 1600 such households will be within $300 of the population mean is roughly 0.907 = 90.7%.