What is the lcm of 56 and 136
1 answer:
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Answer:
4.01% probability that the cable company will keep the shopping channel.
Step-by-step explanation:
For each subscriber, there are only two possible outcomes. Either they watch the shopping channel at least once a week, or they do not. This means that we can solve this problem using the binomial probability distribution.
However, we are working with samples that are considerably big. So i am going to aproximate this binomial distribution to the normal.
Binomial probability distribution
Probability of exactly x sucesses on n repeated trials, with p probability.
Can be approximated to a normal distribution, using the expected value and the standard deviation.
The expected value of the binomial distribution is:
The standard deviation of the binomial distribution is:
Normal probability distribution
Problems of normally distributed samples 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.
When we are approximating a binomial distribution to a normal one, we have that ,
.
In this problem, we have that:
So
The cable company has decided to keep the shopping channel if the sample proportion is greater than 0.27. What is the approximate probability that the cable company will keep the shopping channel, even though the true proportion who watch it is only 0.20?
This probability is 1 subtracted by the pvalue of Z when . So
has a pvalue of 0.9599.
So there is a 1-0.9599 = 0.0401 = 4.01% probability that the cable company will keep the shopping channel.
Answer:
Alternative hypothesis: "AT LEAST ONE" of the population means is different from the others
Step-by-step explanation:
Analysis of variance (ANOVA) "is used to analyze the differences among group means in a sample".
The sum of squares "is the sum of the square of variation, where variation is defined as the spread between each individual value and the grand mean"
If we assume that we have n groups and we want to check if the population means are equal, th best way to check this it's with an ANOVA test.
The hypothesis for this case are:
Null hypothesis:
Or in words:
Null hypothesis: All treatments/samples come from populations with the same mean
Alternative hypothesis: Not all the means are equal
Or we can say:
Alternative hypothesis: "AT LEAST ONE" of the population means is different from the others