Okay.
Well, first of all you need to know what an x-intercept is.
It's the point of when the line crosses over the x-axis. For this, situation it crosses twice. An x-intercept written out is normally written out as (#, 0)
Out of that table you have two that apply to (#, 0)
(-6, 0) and (11,0)
the question is asking for a positive x-intercept. I'm guessing you know the difference. between negative and positive. but just in case, I'll use the number 5. As a positive: 5 As a negative: -5
So, you have -6 and 11.
the 6 is negative(-) the 11 is positive(+).
So your answer would be (11,0)
I hope this helped! :)
Answer:
Table C
Step-by-step explanation:
we know that
A relationship between two variables, x, and y, represent a proportional variation if it can be expressed in the form
or 
Find the value of the constant of proportionality in each table
Table A
For
------>
For
------>
This table has different values of k
therefore
the table A does not represent a proportional relationship
Table B
For
------>
For
------>
For
------>
This table has different values of k
therefore
the table B does not represent a proportional relationship
Table C
For
------>
For
------>
For
------>
For
------>
This table has the same value of k
therefore
the table C represent a proportional relationship
Table D
For
------>
For
------>
For
------>
For
------>
This table has different values of k
therefore
the table D does not represent a proportional relationship
Answer:
D? maybe, I'm not sure. it jsut makes the most sense.
Answer:
C
Step-by-step explanation:
6*12=72
12*8=96
10*12=120
8*6*2/2=48
72+48+96+120=336
Answer:
a) H0:
H1:
b) 
And the critical values with
on each tail are:

c)
d) For this case since the critical value is not higher or lower than the critical values we have enough evidence to FAIL to reject the null hypothesis and we can conclude that the true deviation is not significantly different from 1.34
Step-by-step explanation:
Information provided
n = 10 sample size
s= 1.186 the sample deviation
the value that we want to test
represent the p value for the test
t represent the statistic (chi square test)
significance level
Part a
On this case we want to test if the true deviation is 1,34 or no, so the system of hypothesis are:
H0:
H1:
The statistic is given by:
Part b
The degrees of freedom are given by:

And the critical values with
on each tail are:

Part c
Replacing the info we got:
Part d
For this case since the critical value is not higher or lower than the critical values we have enough evidence to FAIL to reject the null hypothesis and we can conclude that the true deviation is not significantly different from 1.34