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valentinak56 [21]
3 years ago
7

Which answer best describes the shape of this distribution

Mathematics
2 answers:
Artist 52 [7]3 years ago
8 0

Answer:

B.. skewed left

Step-by-step explanation:

Lilit [14]3 years ago
3 0

Answer:

Option B. skewed left.

Step-by-step explanation:

In the figure attached maximum frequency of the data is at the 45. Distribution on the right side of the maximum frequency is upto 48 and in the left it is upto 36.

As we can see point 36 is more distant from peak point 45 as compared to point 48.

Therefore, distribution of the data is more in the left than in the right.

Therefore, the shape of this distribution is skewed left.

Option B. skewed left is the correct answer.

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Shawn picked some vegetables from his garden.he picked 2.234 pounds of corn 2.205 pounds of tomatoes and 2.25 pounds of potatoes
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Suppose you make hot chocolate. It's too hot to drink, so you put it in the freezer to cool it off. If the original temperature
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After your yearly checkup, the doctor has some bad news and some good news. The bad news is that you tested positive for a serio
Maru [420]

Answer:

0.009804

Step-by-step explanation:

We are given;

probability of testing positive given that you have the disease is 0.99

Also, probability of not testing positive and not having the disease is 0.99

We are also told that it is a rare disease and so strikes only 1 in 1000 people = 0.0001

Let's denote positive test by T+, negative test by T¯, having the disease by D+, not having the disease by D¯.

So, we can now denote all the values in probability we have written earlier.

Thus:

P(T+ | D+) = 0.99

P(T¯ | D¯) = 0.99

P(D+) = 0.0001

Thus, P(D¯) = 1 - P(D+) = 1 - 0.0001 = 0.9999

Now, let's find probability of testing positive;

P(T+) = (P(T+ | D+) × P(D+)) + (P(T+ | D¯) × P(D¯))

Now, (P(T+ | D¯) is not given but by inspection, we can infer from the values given that it is 0.01

Thus;

P(T+) = (0.99 × 0.0001) + (0.01 × 0.9999)

P(T+) = 0.010098

Chances that one has the disease would be gotten from Baye's theorem;

P(D+ | T+) = (P(T+ | D+) × P(D+))/P(T+) = (0.99 × 0.0001)/0.010098 = 0.009804

7 0
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