0.1170 = 11.70% probability that the bag we selected contains more than 12% blue M&Ms.
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal Probability Distribution:
Problems of normal distributions can be solved using the z-score formula.
In a set with mean and standard deviation , the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean and standard deviation .
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean and standard deviation
Mars Candy claims that 10% of all M&Ms are blue.
This means that
The particular bag we examine contains 320 M&Ms.
This means that
Mean and standard deviation:
What is the probability that the bag we selected contains more than 12% blue M&Ms?
This is 1 subtracted by the pvalue of Z when X = 0.12. So
By the Central Limit Theorem
has a pvalue of 0.8830
1 - 0.8830 = 0.1170
0.1170 = 11.70% probability that the bag we selected contains more than 12% blue M&Ms.
0.1170 = 11.70% probability that the bag we selected contains more than 12% blue M&Ms.
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal Probability Distribution:
Problems of normal distributions can be solved using the z-score formula.
In a set with mean and standard deviation , the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean and standard deviation .
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean and standard deviation
Mars Candy claims that 10% of all M&Ms are blue.
This means that
The particular bag we examine contains 320 M&Ms.
This means that
Mean and standard deviation:
What is the probability that the bag we selected contains more than 12% blue M&Ms?
This is 1 subtracted by the pvalue of Z when X = 0.12. So
By the Central Limit Theorem
has a pvalue of 0.8830
1 - 0.8830 = 0.1170
0.1170 = 11.70% probability that the bag we selected contains more than 12% blue M&Ms.
Step-by-step explanation:
15 red, 12 green, 15 blue, 18 blacktotal of 60 swimsuits
probability of picking a green ...
so there is 12 green out of 60 swimsuits
P(green) = 12/60 which reduces to 1/5 <===
Step-by-step explanation:
15 red, 12 green, 15 blue, 18 blacktotal of 60 swimsuits
probability of picking a green ...
so there is 12 green out of 60 swimsuits
P(green) = 12/60 which reduces to 1/5 <===
Blue
1 / n
Red
n-1 / n = 1 - 1 / n
7 red containers
Step-by-step explanation:
If there are "n" counters in total but we know that one is blue it means that there are "n - 1" red counters, which means that the probability for when one of them is:
Blue
1 / n
Red
n-1 / n = 1 - 1 / n
for part b, we have that the probability is 0.125, that is:
1 / n = 0.125
if we solve for n:
n = 1 / 0.125
n = 8
knowing that of the 8 one is blue, it means that the rest are red, that is to say that there are 7 (8 - 1) red containers
Your answer would be B) 3/11, hope this helps!
Remember there are 11 muffins in the bag
The odds of getting a green M&M is and the probability of getting a green M&M is
Step-by-step explanation:
Red candies = 14
Blue candies = 10
Green candies = 5
Brown candies = 11
Orange candies = 3
Yellow candies = 12
Total No. of candies = 14+10+5+11+3+12 = 55
(a) the odds of getting a green M&M
Green candies = 5
Total number of candies excluding green or unfavorable = 50
Odds of getting a green M&M =
=
=
(b) the probability of getting a green M&M
Green candies = 5
Total No. of candies = 55
So, the probability of getting a green M&M =
=
Hence the odds of getting a green M&M is and the probability of getting a green M&M is
The odds of getting a green M&M is and the probability of getting a green M&M is
Step-by-step explanation:
Red candies = 14
Blue candies = 10
Green candies = 5
Brown candies = 11
Orange candies = 3
Yellow candies = 12
Total No. of candies = 14+10+5+11+3+12 = 55
(a) the odds of getting a green M&M
Green candies = 5
Total number of candies excluding green or unfavorable = 50
Odds of getting a green M&M =
=
=
(b) the probability of getting a green M&M
Green candies = 5
Total No. of candies = 55
So, the probability of getting a green M&M =
=
Hence the odds of getting a green M&M is and the probability of getting a green M&M is
It will provide an instant answer!