<u>Correct Question</u>
In the table shown, the sum of each row is shown to the right of the row and the sum of each column is shown below the column. What is the value of L?

Answer:
L=7
Step-by-step explanation:
From the first row: 2J+K=5
Therefore: K=5-2J
From the second column, 2K+J=7
Substitute K derived above into 2K+J=7
2K+J=7
2(5-2J)+J=7
10-4J+J=7
-3J=7-10
-3J=-3
J=1
Recall: K=5-2J
K=5-2(1)=3
K=3
From the third column, J+2L=15
1+2L=15
2L=15-1=14
L=7
Therefore, the value of L=7
CHECK:

The area is 14! hope this helps
Answer:
2800 - 4000
Step-by-step explanation:
40 × 70 = 2800
50 × 80 = 4000
Answer:
1. x = independent variable: Age
y = dependent variable: Accidents
2. Age scale and Accidents scale
The scale for age ranges from 15 - 30 with the value of 5 difference between each number.
While the accidents scale ranges from 0 -1 with no difference in between.
3. In my opinion, the scatter plot looks as though it decreases in accidents once the age rises. As seen from the data shown.
Step-by-step explanation:
1) x is considered as the independent variable, while y is considered the dependent value.
2) There are two sets of scales, one for the x and the other for y. These scales are the values that are interpreted in order to show data of the graph, due to their number and various size(s).
3) If you were to draw a line through the graph, you can somewhat create the image that the line would go down into the right corner! Meaning that it is decreasing over time.
Answer:
c) Is not a property (hence (d) is not either)
Step-by-step explanation:
Remember that the chi square distribution with k degrees of freedom has this formula

Where N₁ , N₂m ....
are independent random variables with standard normal distribution. Since it is a sum of squares, then the chi square distribution cant take negative values, thus (c) is not true as property. Therefore, (d) cant be true either.
Since the chi square is a sum of squares of a symmetrical random variable, it is skewed to the right (values with big absolute value, either positive or negative, will represent a big weight for the graph that is not compensated with values near 0). This shows that (a) is true
The more degrees of freedom the chi square has, the less skewed to the right it is, up to the point of being almost symmetrical for high values of k. In fact, the Central Limit Theorem states that a chi sqare with n degrees of freedom, with n big, will have a distribution approximate to a Normal distribution, therefore, it is not very skewed for high values of n. As a conclusion, the shape of the distribution changes when the degrees of freedom increase, because the distribution is more symmetrical the higher the degrees of freedom are. Thus, (b) is true.