triangle JKL is rotated 270 degrees counterclockwise about the origin to form triangle jkl what is the y-coordinate of point j
1 answer:
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Answer:
the rate is: 6 cups of flour per cup of water
Step-by-step explanation:
Recall that rate involve quotient of the two quantities in question:
Then cups of flour per cups of water is the quotient: 2 cups of flour divided by 1/3 cup of water:
this means 6 cups of flour per cup of water
Question:
A Sunday newspaper lists the 10 used car prices for a foreign compact, with age x measured in years and selling price y measured in thousands of dollars. A Sunday newspaper lists the 10 used car prices for a foreign compact, with age x measured in years and selling price y measured in thousands of dollars.
Picture of data can be found in the picture attached.
Answer:
Slope = -1.71
Intercept = 22.05
Step-by-step explanation:
Equation of a line usually takes the general form :
ŷ = mx + c
Where :
m = slope or gradient
c = intercept
Inputting the data into a linear regression calculator ;
The output is : ŷ = -1.70872X + 22.04985
Comparing the output to the general formula;
The slope (m):
m = -1.70872 = -1.71(2 decimal places).
The intercept (c):
c = 22.04985 = 22.05(2 decimal places).
Answer:
78.88% probability that the mean thickness in the sample of 100 points is within 0.1 mm of the target value
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 thickness in the sample of 100 points is within 0.1 mm of the target value?
This is the pvalue of Z when X = 2 + 0.1 = 2.1 subtracted by the pvalue of Z when X = 2 - 0.1 = 1.9. So
X = 2.1
By the Central Limit Theorem
has a pvalue of 0.8944
X = 1.9
has a pvalue of 0.1056
0.8944 - 0.1056 = 0.7888
78.88% probability that the mean thickness in the sample of 100 points is within 0.1 mm of the target value