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Which phrase correctly represents the algebraic expression 3t?
1 answer:
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Answer:
0.2857
Step-by-step explanation:
Given that a company introduced a much smaller variant of its tablet, known as the tablet junior.
The weight was less than 11 oz. i.e. 50% lighter than std.
Let X be the battery life of the tablet junior
Then X is U(8.5,12)
Mean of X =10.25 hrs
the probability that the battery life for a tablet junior will be 9.5 hours or less
=
Answer:
a) For this case we can use the following R code to construct the qq plot
> data<-c(28.8, 24.4, 30.1, 25.6, 26.4, 23.9, 22.1, 22.5, 27.6, 28.1, 20.8, 27.7, 24.4, 25.1, 24.6, 26.3, 28.2, 22.2, 26.3, 24.4)
# The above line is in order to store the data in a vector
> qqnorm(data, pch = 1, frame = FALSE)
# The line above is in order to calculate the quantiles from the data assumin Normal distribution
> qqline(data, col = "steelblue", lwd = 2)
# The line above is in order to put a line for the theoretical dsitribution
The result is on the figure attached.
b) For this case as we can see on the figure attached the calculated quantiles are not far from the theorical quantiles given byt the straaigth blue line so then we can conclude that the distribution seems to be normal.
Step-by-step explanation:
For this case we have the following data:
28.8, 24.4, 30.1, 25.6, 26.4, 23.9, 22.1, 22.5, 27.6, 28.1, 20.8, 27.7, 24.4, 25.1, 24.6, 26.3, 28.2, 22.2, 26.3, 24.4
The quantile-quantile or q-q plot is a graphical procedure in order to check the validity of a distributional assumption for a data set. We just need to calculate "the theoretically expected value for each data point based on the distribution in question".
If the values are asusted to the assumed distribution, we will see that "the points on the q-q plot will fall approximately on a straight line"
For this case our distribution assumed is normal.
Part a
For this case we can use the following R code to construct the qq plot
> data<-c(28.8, 24.4, 30.1, 25.6, 26.4, 23.9, 22.1, 22.5, 27.6, 28.1, 20.8, 27.7, 24.4, 25.1, 24.6, 26.3, 28.2, 22.2, 26.3, 24.4)
# The above line is in order to store the data in a vector
> qqnorm(data, pch = 1, frame = FALSE)
# The line above is in order to calculate the quantiles from the data assuming Normal distribution (0,1)
> qqline(data, col = "steelblue", lwd = 2)
# The line above is in order to put a line for the theoretical distribution
The result is on the figure attached.
Part b
For this case as we can see on the figure attached the calculated quantiles are not far from the theorical quantiles given byt the straaigth blue line so then we can conclude that the distribution seems to be normal.
