You can choose from 20 students for the first student, 19 for the second, 18 for the third, ..., 14 for the seventh student.
That gives you 20 * 19 * 18 * 17 * 16 * 15 * 14.
That number would allow you to write the students in different order. Since order here does not matter, any group with the same students in any order is the same group, you need to divide by the number of way you can order 7 items. Divide by 7 * 6 * 5 * 4 * 3 * 2 * 1
(20 * 19 * 18 * 17 * 16 * 15 * 14)/(7 * 6 * 5 * 4 * 3 * 2 * 1) = 77,520
Answer: 77,520
Answer:
Explanation:
The standard form of an equation is expressed as y = mx+b
m is the slope
Given the equation x - y = 6
Rewrite in standard form;
-y = -x + 6
Multiply through by -1
-(-y) = -(-x) - 6
y = x - 6
Compare with the standard equation
mx = 1x
mx+b
m is the slope
Given
Answer:
Step-by-step explanation:
Remark
The rate is going to be the same as the distance travelled in 1 hour. The units will be different.
Formula
d = r * t
Givens
d = 558 miles
t = 3 hours
Problem A
r = d / t
r = 558/ 3 = 186 miles / hr
Problem B
Givens
r = 186 miles / hour
t = 1 hour
d = ?
Solution
d = 186 mi/hr * 1 hr
d = 186 miles
<u>Note</u>
This looks really trivial, but it's not. You have to learn to see the difference between a number and its units. It's not very often that the numbers will be the same, but if the units differ, then it is an entirely different question.
Answer:
Option B - False
Step-by-step explanation:
Critical value is a point beyond which we normally reject the null hypothesis. Whereas, P-value is defined as the probability to the right of respective statistic which could either be Z, T or chi. Now, the benefit of using p-value is that it calculates a probability estimate which we will be able to test at any level of significance by comparing the probability directly with the significance level.
For example, let's assume that the Z-value for a particular experiment is 1.67, which will be greater than the critical value at 5% which will be 1.64. Thus, if we want to check for a different significance level of 1%, we will need to calculate a new critical value.
Whereas, if we calculate the p-value for say 1.67, it will give a value of about 0.047. This p-value can be used to reject the hypothesis at 5% significance level since 0.047 < 0.05. But with a significance level of 1%, the hypothesis can be accepted since 0.047 > 0.01.
Thus, it's clear critical values are different from P-values and they can't be used interchangeably.
