Step-by-step explanation:
so, that means we want to find the time t (days) after which N = No/2
because "half-life" means the amount of time until half of the substance has disappeared (or transformed into something else).
so, we have
No/2 = No × e^(-0.1481×t)
No = 2× No × e^(-0.1481×t)
1 = 2×e^(‐0.1481×t)
1/2 = 0.5 = e^(-0.1481×t)
ln(0.5) = -0.1481×t
t = ln(0.5)/-0.1481 = 4.680264555... ≈ 4.7 days
There's more than one way to combine them really
but an obvious one will be
![\bf \begin{array}{llll} h(x)&=&(f\circ g)(x)\\\\ &&\sqrt[3]{7x+1}\\\\ &&\sqrt[3]{g(x)}\leftarrow \begin{array}{llll} f(x)=\sqrt[3]{x }\\\\ g(x)=7x+1 \end{array} \end{array}\\\\ -----------------------------\\\\ (f\circ g)(x)\iff f[\quad g(x)\quad ]=\sqrt[3]{g(x)}\implies f[\quad g(x)\quad ]=\sqrt[3]{7x+1}](https://tex.z-dn.net/?f=%5Cbf%20%5Cbegin%7Barray%7D%7Bllll%7D%0Ah%28x%29%26%3D%26%28f%5Ccirc%20g%29%28x%29%5C%5C%5C%5C%0A%26%26%5Csqrt%5B3%5D%7B7x%2B1%7D%5C%5C%5C%5C%0A%26%26%5Csqrt%5B3%5D%7Bg%28x%29%7D%5Cleftarrow%20%0A%5Cbegin%7Barray%7D%7Bllll%7D%0Af%28x%29%3D%5Csqrt%5B3%5D%7Bx%20%7D%5C%5C%5C%5C%0Ag%28x%29%3D7x%2B1%0A%5Cend%7Barray%7D%0A%5Cend%7Barray%7D%5C%5C%5C%5C%0A-----------------------------%5C%5C%5C%5C%0A%28f%5Ccirc%20g%29%28x%29%5Ciff%20f%5B%5Cquad%20g%28x%29%5Cquad%20%5D%3D%5Csqrt%5B3%5D%7Bg%28x%29%7D%5Cimplies%20%20f%5B%5Cquad%20g%28x%29%5Cquad%20%5D%3D%5Csqrt%5B3%5D%7B7x%2B1%7D)
Answer:
c
Step-by-step explanation:
plot your graph and then you will see there is no line which shows there is a correlation. they're too scattered
Answer:
Mean is greater
Step-by-step explanation:
For a skewed distribution, then the tail is longer to one side from the center than to the other. In a right skewed distribution, the tail is longer to the right.
When a distribution is skewed, the mean will be closer to the tail Than the median. Therefore. For a right skewed histogram, the mean is closer to the tail of the histogram and hence closer to the right. Once this happens, values closer to the right of a distribution are higher (number line). Thus the mean will be greater than the median.
