Answer:
Step-by-step explanation:
If u = 6 then substitute so
6(6+6)=6 know solve but this isn't going to be correct because 6 plus 6 is 12 times 6 isn't 3
So your answer isn't correct. I think it would be a negative number or decimal because 6 is larger than 3. Hope this helps!
it is u(u+6)=3
I got u=6
Answer:
below in bold
Step-by-step explanation:
f(x) = 2x - 7 - 3
~Combine like terms
f(x) = 2x - 10
When x = 2...
f(x) = 2(2) - 10
f(x) = 4 - 10
f(x) = -6
When x = 3...
f(x) = 2(3) - 10
f(x) = 6 - 10
f(x) = -4
When x = 4...
f(x) = 2(4) - 10
f(x) = 8 - 10
f(x) = -2
Best of Luck!
This question is incomplete, the complete question is;
Let X denote the time in minutes (rounded to the nearest half minute) for a blood sample to be taken. The probability mass function for X is:
x 0 0.5 1 1.5 2 2.5
f(x) 0.1 0.2 0.3 0.2 0.1 0.1
determine;
a) P( X < 2.5 )
B) P( 0.75 < X ≤ 1.5 )
Answer:
a) P( X < 2.5 ) = 0.9
b) P( 0.75 < X ≤ 1.5 ) = 0.5
Step-by-step explanation:
Given the data in the question;
The probability mass function for X is:
x 0 0.5 1 1.5 2 2.5
f(x) 0.1 0.2 0.3 0.2 0.1 0.1
a) P( X < 2.5 )
P( X < 2.5 ) = p[ x = 0 ] + p[ x = 0.5 ] + p[ x = 1 ] + p[ x = 1.5 ] + p[ x = 2 ]
so
P( X < 2.5 ) = 0.1 + 0.2 + 0.3 + 0.2 + 0.1
P( X < 2.5 ) = 0.9
b) P( 0.75 < X ≤ 1.5 )
P( 0.75 < X ≤ 1.5 ) = p[ x = 1 ] + p[ x = 1.5 ]
so
P( 0.75 < X ≤ 1.5 ) = 0.3 + 0.2
P( 0.75 < X ≤ 1.5 ) = 0.5
Answer:
D. If the P-value for a particular test statistic is 0.33, she expects results at least as extreme as the test statistic in exactly 33 of 100 samples if the null hypothesis is true.
D. Since this event is not unusual, she will not reject the null hypothesis.
Step-by-step explanation:
Hello!
You have the following hypothesis:
H₀: ρ = 0.4
H₁: ρ < 0.4
Calculated p-value: 0.33
Remember: The p-value is defined as the probability corresponding to the calculated statistic if possible under the null hypothesis (i.e. the probability of obtaining a value as extreme as the value of the statistic under the null hypothesis).
In this case, you have a 33% chance of getting a value as extreme as the statistic value if the null hypothesis is true. In other words, you would expect results as extreme as the calculated statistic in 33 about 100 samples if the null hypothesis is true.
You didn't exactly specify a level of significance for the test, so, I'll use the most common one to make a decision: α: 0.05
Remember:
If p-value ≤ α, then you reject the null hypothesis.
If p-value > α, then you do not reject the null hypothesis.
Since 0.33 > 0.05 then I'll support the null hypothesis.
I hope it helps!
