Answer:
25
Step-by-step explanation:
that what i got
Answer:
72
Step-by-step explanation:
<1 and <2 are not equal to each other
Let the angle directly above angle 2 (on the right side of the line) be angle 3
<1 and <3 are corresponding angle, which means they are equal
<2 and <3 are supplementary angles since the form a line
<2 + <3 = 180
We know <1 = <3
<1 + <3 = 180
We are given <1 = 2x+12 and <2 = 3x+18
2x+12 + 3x+18 = 180
Combine like terms
5x+30 = 180
Subtract 30 from each side
5x+30-30 = 180-30
5x= 150
Divide each side by 5
5x/5 = 150/5
x=30
<1 = 2x+12
Substitute 30 in for x to find angle 1
= 2*30 +12
=60+12
= 72
Answer:
17.38*10^8
Step-by-step explanation:
Step one:
given data
The dividend is 2.26*10^8 (i rewrote the given data, i hope it was mearnt to be so)
divisor is 0.013.
Step two:
Hence the quotient is the whole number gotten when the dividend is divided by the divisor
quotient= 2.26*10^8/0.013.
quotient= 17.38*10^8
Answer:
2nd option
Step-by-step explanation:
- 5 =
← in the form 
Answer:
a)Null hypothesis:
Alternative hypothesis:
b) A Type of error I is reject the hypothesis that
is equal to 40 when is fact
, is different from 40 hours and wish to do a statistical test. We select a random sample of college graduates employed full-time and find that the mean of the sample is 43 hours and that the standard deviation is 4 hours. Based on this information, answer the questions below"
Data given
represent the sample mean
population mean (variable of interest)
s=4 represent the sample standard deviation
n represent the sample size
Part a: System of hypothesis
We need to conduct a hypothesis in order to determine if actual mean is different from 40 , the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
Part b
In th context of this tes, what is a Type I error?
A Type of error I is reject the hypothesis that
is equal to 40 when is fact [tex]\mu is equal to 40
Part c
Suppose that we decide not to reject the null hypothesis. What sort of error might we be making.
We can commit a Type II Error, since by definition "A type II error is the non-rejection of a false null hypothesis and is known as "false negative" conclusion"