To determine when Mya will have both lessons again on the same day, you will list the multiples of each number of days because to show every 4 or 6 days, you will count by 4's and 6's.
When you get to the first number that is the same, that will be the next time she will have both lessons again. This is called the least common multiple (LCM).
4, 8, 12, 16, 20, ...
6, 12, 18, 24
In 12 days she will have both lessons again.
The slope of a line is always zero because the line does not move up or down on the y-axis.
Let's start with y = 4x + b (since 4 is the slope);
We need to find what number should be put instead of b;
Then, let's see what needs to be done;
Plug in the y and x values from the coordinate (22,12) into y=4x+b;
12 = 4(22) + b
Solve;
12 = 88 + b
12 - 88 = b
b = -76
Remember the equation y = 4x + b? Put the -76 instead of b:
y = 4x + -76
or: y = 4x - 76
That is the equation.
To make it standard form, put x and y both in the left side, with x first then y:
-4x + y = -76
^^Answer!
Answer:
2/5, 8/20, 4/10,16/40
Step-by-step explanation:
40%
Percent means out of 100
40/100 = 4/10 = 2/5
Lets look at the choices
8/100 =4/50 =2/25 not equal
2/5 equal
8/20 = 4/10 =2/5 = equal
4/10 = 2/5 = equal
16/40 = 4/10 = 2/5 equal
Complete Question:
A population proportion is 0.4. A sample of size 200 will be taken and the sample proportion p will be used to estimate the population proportion. Use z- table Round your answers to four decimal places. Do not round intermediate calculations. a. What is the probability that the sample proportion will be within ±0.03 of the population proportion? b. What is the probability that the sample proportion will be within ±0.08 of the population proportion?
Answer:
A) 0.61351
Step-by-step explanation:
Sample proportion = 0.4
Sample population = 200
A.) proprobaility that sample proportion 'p' is within ±0.03 of population proportion
Statistically:
P(0.4-0.03<p<0.4+0.03)
P[((0.4-0.03)-0.4)/√((0.4)(.6))/200 < z < ((0.4+0.03)-0.4)/√((0.4)(.6))/200
P[-0.03/0.0346410 < z < 0.03/0.0346410
P(−0.866025 < z < 0.866025)
P(z < - 0.8660) - P(z < 0.8660)
0.80675 - 0.19325
= 0.61351
B) proprobaility that sample proportion 'p' is within ±0.08 of population proportion
Statistically:
P(0.4-0.08<p<0.4+0.08)
P[((0.4-0.08)-0.4)/√((0.4)(.6))/200 < z < ((0.4+0.08)-0.4)/√((0.4)(.6))/200
P[-0.08/0.0346410 < z < 0.08/0.0346410
P(−2.3094 < z < 2.3094)
P(z < -2.3094 ) - P(z < 2.3094)
0.98954 - 0.010461
= 0.97908
