
Stats-W6
Authored by Nhật Gia
Mathematics
University
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16 questions
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1.
FILL IN THE BLANK QUESTION
45 sec • 1 pt
How many variables below are DISCRETE random variables?
1. Number of students in CCDS
2. Number of steps you take in 1 day
3. Amount of food one eats in a day (in kg)
4. Marks a student get in a MCQ test
5. Average mark of Quiz 1's test
2.
FILL IN THE BLANK QUESTION
45 sec • 1 pt
A student conduct a survey form which has these question:
1. How much do you use the Air Conditioner in Hall in 1 day? (in minutes)
2. On a scale of 1 to 10, how much do you like using Hall Aircon app?
3. Do you see the excess use of Air Conditioner might have an effect on the Environment?
4. Do you have any other remarks you want to share?
How many questions above would have their answer as CONTINUOUS random variable?
3.
FILL IN THE BLANK QUESTION
1 min • 1 pt
A magician has a trick machine. This machine will draw a fair dice 90% of the time. For the rest 10%, a weighted dice is drawn which has a 6 for all six faces. Let X be the random variable denoting the value of the dice when drawn. What is the variance of X?
4.
FILL IN THE BLANK QUESTION
1 min • 1 pt
A coin which has either value 0 or 1, and a fair dice, is rolled together. Find the variance of the sum of their outcome, if the outcome of the dice and the coin is statistically independent?
5.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
Which of the following PMF is impossible? Given X is a discrete random variable.
p(X) = 0 for all X < 0
p(X = 1) = 0.2
p(X = 2) = 0.3
p(X = 3) = 0.4
p(X) = 0 for all X > 3
p(X) = 0 for all X < 0
p(X = 1) = 0.2
p(X = 2) = 0.3
p(X = 3) = 0.4
p(X) = 0.1 for all X > 3
p(X) = 0.1 for all X < 0
p(X = 1) = 0.2
p(X = 2) = 0.3
p(X = 3) = 0.4
p(X) = 0.1 for all X > 3
p(X <= 0) = 0
p(X = 1) = 0.1
p(X = 2) = 0.2
p(X = 3) = 0.3
p(X = 4) = 0.4
p(X > 4) = 0
6.
FILL IN THE BLANK QUESTION
1 min • 1 pt
7.
FILL IN THE BLANK QUESTION
1 min • 1 pt
How many statements below are correct?
1. Variance of the Binomial distribution equals to its mean
2. The Geometric distribution calculates the probability of an event failing n-1 times and successful 1 time
3. Mean of the Poisson distribution is the average number of success in a given amount of time
4. Variance of the Binomial distribution will approximate to its mean when n is large and p is small
5. If we do something with a success rate of 0.05, we will definitely success after 20 tries
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