Answer:
The standard deviation for the distribution of scores is 6.
Step-by-step explanation:
We are given the following information in the question:
Mean, μ = 78
We are given that the distribution of score is a bell shaped distribution that is a normal distribution.
Empirical Formula:
- Almost all the data lies within three standard deviation from mean for a normal data.
- for this rule almost all the data lies within on tandard deviation from the mean.
68% of the scores fall between 72 and 84, thus, we can write:
Thus, the standard deviation for the distribution of scores is 6.
For an acute angled triangle
h^2 < x^2 + y^2 where h = longest side and x and y are the other 2 sides.
so here we have
15^2 < x^2 + (2x)^2
15^2 < 5x^2
x^2 > 15*3 = 45
x > sqrt 45 or x > 6.7
So smallest whole number value of x is 7
Answer:
- <em>Between which two tens does it fall?</em><em> </em><u>Between 25 and 26 tens</u>
<em><u /></em>
- <em>Between which two hundreds does it fall?</em> <u>Between 2 and 3 hundreds</u>
Explanation:
The place-value chart is:
Hundreds Tens Ones
2 5 3
<em><u /></em>
<em><u>a) Between which two tens does it fall? </u></em>
Using the place values you can write 253 = 25 × 10 + 3, i.e. 25 tens and 3 ones.
From that you can write:
Then, you conclude that 253 is between 25 and 26 tens.
<u><em>b) Between which two hundreds does it fall?</em></u>
Using the same reasoning:
- 253 = 2 × 100 + 5 × 10 + 3 = 253
Conclusion: 253 is between 2 hundreds and 3 hundreds.
Answer:
c. observed values of the independent variable and the predicted values of the independent variable
Step-by-step explanation:
This helps us, for example, find the values of y in a y = f(x) equation. y is dependent of x. So x is the independent variable and y the dependent. Obviously, this system is used for way more complex equations, in which is hard to find an actual pattern for y, so we use this method to compare the predicted values of y to the observed.
The correct answer is:
c. observed values of the independent variable and the predicted values of the independent variable
