Histograms are useful when we have data which can be divided into several classes or groups. The histogram shows the trend of each class and the trend among the different classes. For example when we have about 50 different values ranging from 1 to 20, it will be a better approach to draw a histogram in this case by dividing the data into small ranges e.g 1 to 4, 5 to 9 and so on and counting the frequency for each class.
Dot plot is useful when we have a small number of individual values. In this case we can visualize how many times each individual value occurred in the data. This is useful when the number of values in the data is less.
In the given scenario, we have 12 values in total ranging from 1 to 5. So making a dot plot would be the best choice. A histogram would not be useful in this case.
Therefore, the correct answer is option D. Dot plot, because a small number of scores are reported individually
The correct answer is 42x^4-24x^3+12x^2
Answer:
x = 15
Step-by-step explanation:
We are told that a right angle is divided into two parts
A right angle = 90°
Part A = 30°
Part B = 4x
Hence:
30° + 4x = 90°
Collect like terms
4x = 90° - 30°
4x = 60°
4x = 60/4
x = 15
Therefore, the value of x = 15
Answer:
So to graph using a table, the first step is...well... make a table. so you have a column of x and y. under the x column write down a bunch of values you would like to test. I am going to test -2 through 2.
x | y
-2|
-1|
0 |
1 |
2 |
Next, we have to plug each of those values into the equation y=2x to see what the corresponding y value is.
when x=-2 y=2(-2)=-4, when x=-1 y=2(-1)=-2, and so on...
x | y
-2|-4
-1|-2
0 |0
1 |2
2 |4
Next, graph those points on a coordinate plane. Each row on the table is a point on the graph, (x,y). Hope that helps!
the probability that the sample mean will be smaller than m = 22 is 0.02275.
For the given question,
A z-score measures exactly how many standard deviations a data point is above or below the mean. It allows us to calculate the probability of a score occurring within our normal distribution and enables us to compare two scores that are from different normal distributions.
Here sample size, n = 4
mean, μ = 30
standard deviation, σ = 8
The probability that the sample mean will be smaller than m = 22 is
z = 
⇒ z =
⇒ z = 
⇒ z = 
⇒ z = -2
Refer the Z table for p value,
Thus for P(z < -2) is 0.02275.
Hence we can conclude that the probability that the sample mean will be smaller than m = 22 is 0.02275.
Learn more about probability of the sample mean here
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