There is a 60 minute gap between the two clocks.
These 60 minutes result of a 1 min advance in one for each hour and a 2 min loss in the other.
if we are going 2 mins back and 1 min in
We have a 3 min gap/hour
then to reach a 1 hour gap we would need to go for 2+1+2+1+2+1+2....(20 hours)
since each 3 represent an hour,
to get 60 min gap>60/3=20 hours
Take clock 1 for example, which read 12:00, in reality the time is (12:00-20 minutes)=11:40
or
Take clock 2 for example, which read 11:00, in reality the time is (11:00+20×2 minutes)=11:40
Now go back 20 hours from that;
11:40-20=00:40-9=15:40
There's ur answer 15:40 :)
Answer: ![sds\\ \\ x^{2} \geq \int\limits^a_b {x} \, dx \lim_{n \to \infty} a_n \geq \left[\begin{array}{ccc}1&2&3\\4&5&6\\7&8&9\end{array}\right] \pi \left[\begin{array}{ccc}1&2&3\\4&5&6\\7&8&9\end{array}\right] \lim_{n \to \infty} a_n \int\limits^a_b {x} \, dx \left \{ {{y=2} \atop {x=2}} \right. x^{2} \lim_{n \to \infty} a_n \pi \neq \sqrt{x} \neq](https://tex.z-dn.net/?f=sds%5C%5C%20%5C%5C%20x%5E%7B2%7D%20%5Cgeq%20%5Cint%5Climits%5Ea_b%20%7Bx%7D%20%5C%2C%20dx%20%20%5Clim_%7Bn%20%5Cto%20%5Cinfty%7D%20a_n%20%5Cgeq%20%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D1%262%263%5C%5C4%265%266%5C%5C7%268%269%5Cend%7Barray%7D%5Cright%5D%20%5Cpi%20%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D1%262%263%5C%5C4%265%266%5C%5C7%268%269%5Cend%7Barray%7D%5Cright%5D%20%20%5Clim_%7Bn%20%5Cto%20%5Cinfty%7D%20a_n%20%5Cint%5Climits%5Ea_b%20%7Bx%7D%20%5C%2C%20dx%20%5Cleft%20%5C%7B%20%7B%7By%3D2%7D%20%5Catop%20%7Bx%3D2%7D%7D%20%5Cright.%20x%5E%7B2%7D%20%20%5Clim_%7Bn%20%5Cto%20%5Cinfty%7D%20a_n%20%5Cpi%20%5Cneq%20%5Csqrt%7Bx%7D%20%5Cneq)
Step-by-step explanation:i need the think points
12 ÷ 75 = 0.16.
So she runs 0.16 miles per minute.
Hope it helps!
Answer:
b. As the sample size â increases, the variance of decreases. â So, the distribution of becomes highly concentrated around.
Step-by-step explanation:
Let : Yi,.... Yn are = i.i.d are random variables. The probability density of the distribution varies along with the sample size. When the sample size changes, the probability density of
also changes.
The probability distribution may be defined as the statistical expression which defines the likelihood of any outcome for the discrete random variable and it can be opposed to the continuous random variable.
In the context, when the size of the sample of the distribution size increases, it causes a decrease in the variance and so the distribution becomes highly concentrated around.
Answer:
C. -4x - 1
Step-by-step explanation:

Distribute the term outside of the parenthesis, Multiply each term in the parenthesis by the term outside (do not forget to include the negative sign when multiplying);

Simplify,
