this picture will explain you
the answer is 10
What is the equivalent of pi over 3 radians in degrees?
2 answers:
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This question is incomplete.
The complete question says;
The two-way table shows the number of hours students studied and whether they studied independently or with a study group.
What is the relative frequency of students that studied independently for more than 2 hours to the total number of students that studied independently?
a) 0.4 c) 0.25
b) 0.33 d) 0.11
Table is attached as image
Answer: C (0.25)
The number of students that studied for more than 2 hours as given in the table are 4.
The total number of people that studied independently include those that studied less than 2 hours and those that studied for more than 2 hours.
Those that studied less than 2 hours independently are 12.
Those that studied more than 2 hours independently are 4.
Hence the total number of people that studied independently is 16.
Therefore the relative frequency of students that studied independently for more than 2 hours to the total number of students that studied independently would be = 4/16 = 1/4 = 0.25.
Answer:
35.2% probability that the sample mean will be 246 pages or more
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 normally distributed samples are 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.
In this question, we have that:
What the probability that the sample mean will be 246 pages or more?
This is 1 subtracted by the pvalue of Z when X = 246. So
By the Central Limit Theorem
has a pvalue of 0.6480.
1 - 0.6480 = 0.3520
35.2% probability that the sample mean will be 246 pages or more