Answer:
Italy - 6am
Taiwan - 1pm
Peru-12am
Turkey-8am
Laos-12pm
Step-by-step explanation:
Ok, so:
For Part A, we have: P(Z|A)=P(Z and A)/P(A)
And if we replace, we got:
P(Z|A) = (0.15)/(0.25) and this is equal to 0.6.
For Part B, we have: P(A|Z)=P(Z and A)/P(Z)
P(A|Z) = (0.15)/(0.73) and this is equal to 0.205.
Answer: 1.53
Step-by-step explanation:
The given data : 4, 4, 4, 4, 6, 8
Number of data values : n= 6
The mean value of the given data will be :-

The formula to find standard deviation:_
![\sqrt{\dfrac{\sum(x-\overline{x})^2}{n}]](https://tex.z-dn.net/?f=%5Csqrt%7B%5Cdfrac%7B%5Csum%28x-%5Coverline%7Bx%7D%29%5E2%7D%7Bn%7D%5D)
Now,

The standard deviation will be :-

Step-by-step explanation:
Regression analysis is used to infer about the relationship between two or more variables.
The line of best fit is a straight line representing the regression equation on a scatter plot. The may pass through either some point or all points or none of the points.
<u>Method 1:</u>
Using regression analysis the line of best fit is: 
Here <em>α </em>= intercept, <em>β</em> = slope and <em>e</em> = error.
The formula to compute the intercept is:

Here<em> </em>
and
are mean of the <em>y</em> and <em>x</em> values respectively.

The formula to compute the slope is:

And the formula to compute the error is:

<u>Method 2:</u>
The regression line can be determined using the descriptive statistics mean, standard deviation and correlation.
The equation of the line of best fit is:

Here <em>r</em> = correlation coefficient = 
and
are standard deviation of <em>x</em> and <em>y</em> respectively.

Sum is addition, less than is subtraction, equals is is, division is of and multiplication is per