There are a lot of things that are equivalent to 16/81.
16/81 = 0.197530864
Or we can keep multiplying 2 to the numerator and denominator:
16/81 = 32/162 = 64/324 = 128/648
Answer:
a)
b)
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Part a
Let X the random variable that represent the weights of a population, and for this case we know the distribution for X is given by:
Where and
We are interested on this probability
And the best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this:
And we can find this probability like this:
And in order to find these probabilities we can find tables for the normal standard distribution, excel or a calculator.
Part b
For this case we select a sample size of n =32. Since the distribution for X is normal then the distribution for the sample mean is given by:
And the new z score would be:
Answer:
Your answer will be D. He knows that 30 × 16 is 5 then multiples 5 by 5 to get 25.
Answer:
No.
Step-by-step explanation:
For polygon PQRST to be considered a scaled copy of polygon ABCDE, it means every segments of polygon ABCDE were increased proportionally by a scale factor.
The segments in polygon PQRST were not gotten using the same scale factor, hence, it is not a scaled copy of the original polygon, ABCDE.
Segment CD = 2 units, it corresponds to segment RS = 4 units. Scale factor = RS/CD = 4/2 = 2
Segment BC = 1 unit, it corresponds to segment QR = 1 unit. Scale factor = QR/BC = 1/1 = 1 units.
Varying scale factor shows polygon PQRST is not a scaled copy of polygon ABCDE.
Answer:
1) B. on, 2) D. 19.2, 3) C. 0
Step-by-step explanation:
1) The value of y according to the regression line is:
Hence, the point (8,19.2) is <em>on </em>the least-squares regression line.
2) The value of y according to the regression line is 19.2.
3) The residual is the difference between the value from the regression line and the real value. In this case, the residual value is 0.