Answer:



.
Step-by-step explanation:
We use the Venn diagram to calculate the desired probabilities.
Note that there are 6 possible results in the sample space
S = {1, 2, 3, 4, 5, 6}
Then note that in the region representing the intercept of A and B there are two possible values.
So

In the region that represents event A there are 4 possible outcomes {4, 5, 1, 2}
So

In the region that represents event B there are 3 possible outcomes {1, 2, 6}
So
.
Now


In a dot plot, each one of the dots represents a value in the data set. When there are multiple values at a particular number, the dots just get stacked on top of each other. Using the dots in the plot, you can find the mean, median, mode or any other statistic that you need to summarize the data.
I think it’s 196? base 1 +base 2=28 radius is 7 but we need the whole thing so 7x2=14.
then multiply and then divide by 2 28X14= 392 divided by 2 = 196
Answer:
where is the clock?
Step-by-step explanation:
Answer:
Step-by-step explanation:
You need to assume that the slope between the dependent Varian and the numerical independent variable is zero.
In regression analysis, to find the effect of one independent variable on the dependent variable, there has to be no interference from the other independent variables whether they be categorical (dummy) or numerical independent variables.
A dummy variable is one which takes on the value of 0 or 1, to represent the absence or presence (respectively) of a given category which is expected to influence the dependent variable.
When a dummy independent variable is included in a regression model, to know the effect of that dummy or category (e.g. day =1, night =0) on the dependent variable, the influence of the numerical independent variable has to be removed temporarily.
In a regression equation,
Y=a+bX+cK
Y is the dependent variable
a is the intercept on the vertical axis on the graph
b is the slope between the dependent variable Y and the independent numerical variable X
c is the slope between the dependent variable Y and the dummy variable K