Slope Formula: y2 - y1 / x2 - x1
(m and slope represent the same quantity)
m = 1 - - 5 / -4 - 0
m = 1 + 5 / -4
m = 6 / -4
m = -3/2
Now that we know the slope, we can plug the slope and one of our points into slope-intercept form (y = mx + b) and solve for b. I will be using the point (-4,1).
y = -3/2x + b
1 = -3/2(-4) + b
1 = 6 + b
b = -5
In point form, the y-intercept is (0, -5).
Therefore, to get the equation all we need to do is plug in our slope and b-value to slope-intercept form.
Equation: y = -3/2 x - 5
To check the point (-6, -14) we plug it into our equation and see if the two sides are equal.
-14 = -3/2(-6) - 5
-14 = 9 - 5
-14 = 4
-14 does not equal 4, therefore the point is NOT on the line.
Hope this helps!
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➷ It would be 121212/202020
This can be simplified to 3/5
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Given:
Find-:
Factorization of the equation.
Sol:
A simple method of factorization is to multiply in first and last order then break it down into parts to make the middle number then.
The factor of 99 is:
So take factor :
Factorization of the equation is:
Famous pa la playa pa curarte el some
Answer:
(1) Cluster sample
(2) Systematic sample
(3) Random sample
(4) Systematic sample
(5) Stratified sample
Step-by-step explanation:
A simple random sample is a part of a statistical population in which every individual of the population has an equal probability of being selected.
Assigning each individual of the population a unique number and using a computer or random number generator for selection is a procedure to select a simple random sample.
Stratified sampling is a kind of sampling in which whole-population is distributed into homogeneous subgroups before one takes a sample. These subgroups are called strata which is mutually exclusive or related.
In this process the population members cannot be excluded.
Cluster Sampling is a method to randomly select samples from a population that is too enormous for simple random sampling.
Using cluster sampling, the experimenter distributes the entire-population into distinct groups, called clusters. Then, a simple random sample of clusters is chosen from the population. Then the experimenter performs the analysis on data from the sampled clusters.
Systematic sampling is a kind of probability sampling method in which individuals from a larger population are nominated according to a random initial point and a static, periodic interval.
Consider all the definitions of different types of samples.
(1) Cluster sample
(2) Systematic sample
(3) Random sample
(4) Systematic sample
(5) Stratified sample
