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Answer</h2>
The equation is y = 2x - 12
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Explanation</h2>
Equation in slope intercept form is
Where,
m = slope
b = y-intercept
Putting the value of slope in this equation:
From this we can solve the equation for b
Now, the equation of y-intercept becomes
You start by looking at what number can divide evenly into both 16 and 48. Both numbers are divisible by 16. 16 goes into 16 once and 16 goes into 48 three times. So you divide each term by 16 and your expression should look like this: 16 (p+3)
3 blue + 3 yellow = 6 total marbles.
The probability of picking a blue one first would be 3/6 ( 3 blue out of 6 total marbles).
3/6 reduces to 1/2.
After picking the first marble, there would be 5 marbles left in the bag.
The probability of picking a yellow one would be 3/5 ( 3 yellow and 5 total marbles left).
The probability of picking a blue then a yellow then becomes:
1/2 x 3/5 = 3/10 = 0.30 = 30%
Answer:
The distribution is
b) skewed.
The sum of the probabilities is:
1
Step-by-step explanation:
In a binomial distribution, p represents the probability of success. Success in the sense that the event of interest happens. In the model presented, the probability of success p is 0.4 since we are informed that 40% of adults watch a particular television show.
The next quantity of significance in a binomial model is the number of independent trials, n. In our case there are 6 independent trials since we are told that 6 adults were selected at random. If we let the random variable K denote the number of adults out of the 6 who watch the television show, then K is a binomial random variable with parameters;
n = 6 and p = 0.4
A binomial distribution is only symmetric when either p is 0.5 or n is large. In the presented scenario none of this conditions is met since p is 0.4 while n is just 6 which is relatively small. Thus we conclude that the distribution is not symmetric but rather skewed.
The sum of the probabilities is any discrete probability distribution such as the bernoulli, binomial, negative binomial, poisson, or the geometric distribution is always equal to 1. That's a rule of thumb.
