Answer:
Quadratic
Step-by-step explanation:
This is because quadratic equations require a variable squared. Most numbers have two square roots, a positive and a negative. So, the implementation of (variable)² in an equation will most likely have x ± (variable) as an answer.
I got you bestie
So I don’t know the other 5 points because you didn’t give the data about the age and number of US states named in 60 seconds, but using the 5coordinate points you gave, I was able to make this line of best fit.
So basically the units are counting up by 5.
The x axis is age in years and y axis is the number of US states named in 60 seconds.
Since you didn’t give me the data to make the other 5 points, I can’t really answer the last question, but from the graph that I did make, there are no points that would be considered outliers, and there are no clusters in sight.
(BTW THIS IS IMPORTANT!! - when you use the data to add the other 5 points, there might be an outlier or more then one outlier. And there might be a cluster. Just look at it after you graph the last 5 and change the answer I gave you if there is an outlier or cluster)
GRAPH IS HERE:
Answer:
ŷ = 0.1286X - 123.2175 ;
r = 0.947
r² = 0.896
Step-by-step explanation:
Given the data:
Traffic Flow, X : ____Vehicke speed ;Y()
1257 ______________36
1329 ______________45
1227 ______________30
1336 ______________50
1349 ______________55
1124 ______________ 25
The estimated regression equation using a linear regression calculator based on the data given above is given thus:
ŷ = 0.1286X - 123.2175
Where ;
y = dependent variable (vehicle speed)
x = predictor variable (traffic flow)
Slope = 0.1286
Intercept = 123.2175
The correlation Coefficient, R, obtained using the correlation Coefficient calculator is 0.9465, This depicts a very strong positive relationship between traffic flow and vehicle speed.
The Coefficient of determination, R² which is the squared value of the correlation Coefficient = 0.9465² = 0.8958 gives the proportion of explained variance ; This means about 89.5% of variation in Vehicle speed can be explained by the regression line.
Answer:
y = -2
Step-by-step explanation:
using slope formula, you can create the following proportion:
<u>y-(-1) </u> = <u> 1 </u>
-5-(-1) 4
cross-multiply:
4(y+1) = -4
4y + 4 = -4
4y = -8
y = -2
Answer:
Tom = 5
Susan = 3
Step-by-step explanation:
FROM THE BOXPLOT :
Tom's IQR :
IQR = Q3 - Q1
Q3 = third quartile (value at the endpoint of the box)
Q1 = 1st quartile (value at the beginning of the box)
IQR = 9 - 4
IQR = 5
SUSAN :
IQR = Q3 - Q1
Q3 = third quartile (value at the endpoint of the box)
Q1 = 1st quartile (value at the beginning of the box)
IQR = 8 - 5
IQR = 3