Answer:
Decreased
Strong negative
Step-by-step explanation:
The correlation Coefficient is used to show the strength and type of relationship which exists between the dependent and independent variable. The correlation Coefficient value ranges from - 1, to 1. With values closer to either - 1 or 1 depicting a strong relationship while those closer to 0 represents weak relationship. And correlation Coefficient of 0 indicates that no relationship exiata at all. Depending in the sign, that is positive or negative, positive sign means positive relationship while a negative sign represents a negative association. Positive association is interpreted as, for every increase in A, Variable B also increase and vice versa. For negative association, When A increases, B decreases and vice versa
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
Step-by-step explanation:
When a number is grouped with the x in this problem it will move the graph right (if it is is minus) and it will
move it left ( if it is plus), therefore the original graph will be move to the left 5 units.
Answer:
t-5=12
Step-by-step explanation:
Answer:
$7,000
Step-by-step explanation:
1800 = 1450 + 0.05X
0.05X = 350
X = 7000
