Answer:
23/12 or 1 and 11/12
Step-by-step explanation:
Your first step is that you need to gain a common denomitor. In this scenario, this is 12. To get this, you can either go through the given factors such as 3 having the factors of 6, 9, and 12 and 4 having the factors of 8, and 12.
Another method is the multiply the two given denominators together, but there are certain instances where you shouldn't do that.
Now that you have a common denominator, you need to change the numerators to accomadate the denominators. For 3 to turn into 12, you need to multiply it by 4, thus you have to do the same to the numerator. For 4 to turn into 12, you need to multiply it by 3. This will give you these two new fractions:
8/12 + 15/12
Add the numerators to get 23/12 and then simplify the two numbers to get the mixed number of 1 and 11/12.
Hope this helps!
Answer:
a) 98.01%
b) 13.53\%
c) 27.06%
Step-by-step explanation:
Since a car has 10 square feet of plastic panel, the expected value (mean) for a car to have one flaw is 10*0.02 = 0.2
If we call P(k) the probability that a car has k flaws then, as P follows a Poisson distribution with mean 0.2,
a)
In this case, we are looking for P(0)
So, the probability that a car has no flaws is 98.01%
b)
Ten cars have 100 square feet of plastic panel, so now the mean is 100*0.02 = 2 flaws every ten cars.
Now P(k) is the probability that 10 cars have k flaws and
and
And the probability that 10 cars have no flaws is 13.53%
c)
Here, we are looking for P(1) with P defined as in b)
Hence, the probability that at most one car has no flaws is 27.06%
First you would have to find the third angle in the triangle which you would do by adding 63+61 and subtracting the resulting number from the total degrees in a triangle. From there, you would calculate x and y using the knowledge that angles on a line equal 180.
Answer:
the numerical value of the correlation between percent of classes attended and grade index is r = 0.4
Step-by-step explanation:
Given the data in the question;
we know that;
the coefficient of determination is r²
while the correlation coefficient is defined as r = √(r²)
The coefficient of determination tells us the percentage of the variation in y by the corresponding variation in x.
Now, given that class attendance explained 16% of the variation in grade index among the students.
so
coefficient of determination is r² = 16%
The correlation coefficient between percent of classes attended and grade index will be;
r = √(r²)
r = √( 16% )
r = √( 0.16 )
r = 0.4
Therefore, the numerical value of the correlation between percent of classes attended and grade index is r = 0.4
