What is the slope and the y-intercept of the line on the graph below? On a coordinate plane, a line goes through points (0, 1) a
2 answers:
You might be interested in
Answer:
Originally there were 30, 25 cents stamps and 20, 15 cent stamps.
Step-by-step explanation:
We are given the following in the question;
Let x be the number of 25 cents stamps and y be the number of 15 cents stamps.
Marci has a total 50 stamps.
Thus, we can write
Also,
Total cost = $16.50
Thus, we can write the equation:
Solving the two equations:
Originally,
Thus, originally there were 30, 25 cents stamps and 20, 15 cent stamps.
Answer:
a)
b)
Since 25 and 35 are repeated 4 times, so then the distribution would be bimodal.
c)
d)
e) Min = 13 , Q1 = 20.5, Median=25, Q3= 35, Max = 70
f) Figura attached.
g) When we use a quantile plot is because we want to show the percentage or the fraction of values below or equal to an specified value for the distribution of the data.
By the other hand the quantile-quantile plot shows the quantiles of the distribution values against other selected distribution (specified, for example the normal distribution). If the points are on a straight line we assume that the data values fit very well to the hypothetical distribution selected.
Step-by-step explanation:
For this case w ehave the following dataset given:
13, 15, 16, 16, 19, 20, 20, 21, 22, 22, 25, 25, 25, 25, 30,33, 33, 35, 35, 35, 35, 36, 40, 45, 46, 52, 70.
Part a
The mean is calculated with the following formula:
The median on this case since we have 27 observations and that represent an even number would be the 14 position in the dataset ordered and we got:
Part b
The mode is the most repeated value on the dataset on this case would be:
Since 25 and 35 are repeated 4 times, so then the distribution would be bimodal.
Part c
The midrange is defined as:
And if we replace we got:
Part d
For the first quartile we need to work with the first 14 observations
13, 15, 16, 16, 19, 20, 20, 21, 22, 22, 25, 25, 25, 25
And the Q1 would be the average between the position 7 and 8 from these values, and we got:
And for the third quartile Q3 we need to use the last 14 observations:
25, 30,33, 33, 35, 35, 35, 35, 36, 40, 45, 46, 52, 70
And the Q3 would be the average between the position 7 and 8 from these values, and we got:
Part e
The five number summary for this case are:
Min = 13 , Q1 = 20.5, Median=25, Q3= 35, Max = 70
Part f
For this case we can use the following R code:
> x<-c(13, 15, 16, 16, 19, 20, 20, 21, 22, 22, 25, 25, 25, 25, 30,33, 33, 35, 35, 35, 35, 36, 40, 45, 46, 52, 70)
> boxplot(x,main="boxplot for the Data")
And the result is on the figure attached. We see that the dsitribution seems to be assymetric. Right skewed with the Median<Mean
Part g
When we use a quantile plot is because we want to show the percentage or the fraction of values below or equal to an specified value for the distribution of the data.
By the other hand the quantile-quantile plot shows the quantiles of the distribution values against other selected distribution (specified, for example the normal distribution). If the points are on a straight line we assume that the data values fit very well to the hypothetical distribution selected.
